Day One: Placebo Workshop: Translational Research Domains and Key Questions
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Segment 1 (00:00 - 05:00)
all right we'll go ahead and get started um on behalf of the co-chairs and the NIMH planning committee I'd like to welcome you to the NIMH Placebo Workshop translational research domains and key questions before we begin I'm going to quickly go through a few housekeeping items all attendees have been entered into the workshop in listen only mode with cameras disabled you can submit your questions via the Q&A box at any time during the presentation and be sure to address your question to the speaker that you'd like to respond for more information on today's speakers their biographies can be found on the event registration website if you have technical difficulties hearing or viewing the workshop please note these in the Q&A box and our technicians will work to fix the problem you can also send an email to NIMH mn. com and we'll put that email address in the chat box this Workshop will be recorded and posted to the NIMH event website for later viewing now I'd like to turn it over to the acting NIMH director Dr Shelley aan for opening remarks good morning I'm excited to be here today to kick off the NIMH Placebo Workshop I am currently the acting director of NIMH and I look forward to serving in this role while NIH conducts a national search for the next NIMH director today we are bringing together experts in neurobiology Pinacle trials and Regulatory science to examine Placebo effects in drug device and psychosocial interventions NIMH has long understood that the placebo phenomenon is highly active in studies of mental illness understanding how to design and interpret clinical trial results as well as parse neurobiological mechanisms have been important research questions that still have significant GS consequently I'm eager to learn what you believe are the most important questions in Placebo research and how they might be answered this is no small charge I understand but our organizers have designed a carefully thought out agenda to help facilitate our success the workshop is organized into domains that aim to identify those important questions I'm looking forward to hearing the historical review of the successes and failures around mitigating the placebo response in both academic and Industry research this includes historical perspectives and drug and device trials understanding psychosocial aspect of the placebo response and measuring and mitigated the placebo effect clearly several perspectives will be discussed during these presentations it will be exciting to hear your individual views as well as the panel discussions I would like to thank DRS T wager and Christina kusen the co-chairs of the workshop as well as the rest of the planning committee for their work in organizing this excellent agenda I will now turn it over to Dr spor later thank you okay hi everybody um sorry the audio didn't turn out as well as we had hoped but I hope you could still hear um hear that to some degree and I just want to say I'm really delighted um to have you all here and I'm really that nmh has decided to organize this workshop and has worked so hard in planning it I'd like to thank my co-chair Christina and also the nmh co-leads Aon King and Doug Miki um as well as the rest of the team that's been working really hard on preparing this meeting including uh M grab and Laura Roland and um Alexander Tavi Mia Hill fores and Arina nton um my job for the next few minutes is just to give you a brief overview of the uh some of the main Concepts in the placebo field Al together and I'm going to start really at the very beginning um the workshop goals are um really to understand how Placebo and nobo effects impact clinical trial design and outcomes to understand some of the psychological neurobiological and social mechanisms that underly thebo effects and we'd like to think together to use this understanding to help to identify uh and maximize therapeutic effects of drugs and devices and that means a better clinical trial designs better identification of outcomes and also to harness Placebo mechanisms in clinical care alongside active treatments so that we don't think of uh only specific treatments we think of treatments as having psychological and psychosocial components as well as uh active drug or device components
Segment 2 (05:00 - 10:00)
and to go back to the very beginning my colleague Ted Krick once wrote that the history of medicine is the history of the placebo effect so this is the ibrus Papyrus Circa 1500 BCE and it documents hundreds of ancient medications that are now thought to be uh little better than or no better than Placebo effects um some of them we' recognize today like um for example opium uh ingredient of opiates and um wormwood ing gradient of absent for headache if you were poisoned you might be treated with crushed up Emerald or bzour stone which is undigested material from the intestines of animals you might be treated with human sweat and tapeworms and feces uh Moss scraped from the skull of a hung criminal or powdered Egyptian mummy among many other uh treatments and what all of these have in common is that none of them or very few of them have active ingredient inred uh in terms of specific effects but they all act on the mind and brain of the perceiver and so there's something about the beliefs and imaginations of the person that has made these treatments persist for many centuries um and this provides both a challenge and an opportunity and I'm going to introduce the challenge with this clinical trial which is a gene therapy for Parkinson disease a neurot Trin um which was an industry funded trial and they went out two years and this is a um a genetic manipulation intervention for um Parkinson's disease and what you see here is the Improvement in motor scores updrs3 on Parkinson's and if you see people getting the uh the active treatment they got substantially better within the first six months and they stayed better for two years and this seems great but the problem is that this trial failed and the failure resulted in the drug company being sold P off and this treatment may never see the light of day and that's because people in the placebo group also got better and stayed better for two years and there was no drug Placebo difference um and this is really shocking to me because Parkinson's is a neurod degenerative disorder U and so it's very surprising to see changes of this magnitude last this long um so the opportunity is in harnessing these psychosocial processes and the active ingredients that go into the placebo effects like this um or Placebo responses like this I should say and the challenge of course is that Placebo responses can mask effects of vum treatment in the way that we've seen here and this is not a unique um a unique occurrence in many cases uh there are treatments that are widely used that are Medicare reimbursed uh that turn out after they're tested later to not be better than Placebo in clinical trials randomized trials and this includes arthoscopic knee surgery uh for arthritis vertebroplasty epidural steroid injections which are still practiced widely every day um uh some other interesting ones like Sten for Angina uh turns out which is chest pain um and also some um recent high-profile failures to beat Placebo after very initially promising results in emerging treatments like gene therapy for Parkinson's disease that I mentioned before uh and deep brain stimulation for depression um an a really a recent interesting uh case is the reversal of FDA approval for fenel Eon um which is a very common nasal decongestant it's been the most widely used um decongestant on the market almost $2 billion doll in sales um but it turns out um there it may not be better than Placebo um one of the problems is that in some areas like for example in chronic pain Placebo effects are growing across time but drug effects are not and so the drug Placebo Gap is shrinking and fewer treatments are uh then getting to Market and getting through clinical trials um and that's particularly true in this uh study by Alex tutel in the United States um so as an example surgery has been widely practiced first in an open label way where people know what they're getting uh and it was only much later that people started to go back and um do trials where they would get a sham surgery that was uh blinded uh or the just a superficial incision then so the person doesn't know that they're not getting the real surgery and those sham surgeries in many cases have effects that are substantial and in some cases as large or nearly as large as the active Placebo effects s active drug effects so this is U what we call Placebo response which is overall Improvement on Placebo it doesn't mean that the Sham surgery or other Placebo treatment cause them to
Segment 3 (10:00 - 15:00)
get better U and so if we think about what the placebo response is it's a mixture of un of interesting and uninteresting effects including regression to the mean people fluctuate in their symptoms uh over time and they tend to enroll sometimes when the symptoms are High um and there's a sampling bias and selective attrition there's Natural History effects and then there's the placebo effect which will Define as a causal effect of the placebo context and the simplest way to identify a placebo effect is to compare Placebo treatment with a natural history or no treatment group in a randomized trial uh and so here in this three arm trial a parallel groups trial what you see is the typical way of identifying the effect is the active drug effect comparing active treatment to Placebo and you need to compare Placebo to the Natural History group to identify the placebo effect here and if we look at those studies that do such comparisons um we can see that there are many effects across different areas and those effects uh are active brain body responses or mental responses to the treatment context um and so there are many ingredients it's not the the placebo drug or stimulation or device itself of course that has the effect it's the suggestions and the context surrounding that um and there are many types of cues there are verbal suggestions and information there are Place cues there are social cues in ter including body language and touch uh there are specific treatment cues that are associated with drugs as and there is a rich internal context uh expectations about uh treatment outcomes uh interpretations of the meaning of what symptoms mean and the meaning of the therapeutic context and um and the care context um as well as engagement of emotions and memories and what I'm calling here precognitive associations that are learned or conditioned responses in the brain and the body so there's a large family of placebo effects not many uh not one but many Placebo effects um they operate both via conscious and unconscious means they are embedded in the nervous system through uh learning processes and an idea here is that the meaning of the response to the per the treatment to the person in the symptoms is really the key what are the implications of the cues and the symptoms and the whole context for future well-being so if we look at studies that have isolated Placebo effects uh compared to no treatment um we see that there are many studies and many systematic reviews and met analyses including in many types of clinical pain in uh depression in Parkinson's disease and motor symptom Syms as well as other symptoms uh in anxiety um including social anxiety in particular and general anxiety um substance misuse and perceived drug effects uh some effects in schizophrenia potentially some effects in asthma um and that's a sort of a tricky thing with the conflicting results that we could talk about um and effects on sleep and cognitive function more so these effects are really widespread and if and there have been some attempts to decompose these into you know how large are the effects of placebo versus the effects of active drugs and so if you look at pharmacotherapy for depression at least in one analysis here by Irving kersch um half of the overall benefit the placebo response uh or the active treatment response I should say is Placebo um a very small proportion is specific drug effects and about a quarter of it is people would have gotten better anyway they recover spontaneously from depression that's natural history so the placebo effect is a large part of the overall therapeutic response and this mirrors um what's called common factors in Psychotherapy and com and this is for mood and anxiety disorders substance use disorders and more and common factors are those therapeutic elements that are shared across many treatments and really particular to None they include forming a Therapeutic Alliance providing uh listening and social support positive engagement and positive expectations and in this analysis um here the common factors also were responsible for a line share of the theer therapeutic effects of psychotherapy um so in one sense you can say that Placebo effects are really powerful they can affect many kinds of outcomes um but there is a continuing controversy I would say even though these competing New York Times headlines are somewhat old now um and this a latter headline um came out after a
Segment 4 (15:00 - 20:00)
landmark meta analysis by herin and Goa in 2001 which they've updated several times since then and what they found is um consistent with what I said there significant Placebo effects in the domains that they were uh powered to detect but they discounted those uh they said it's probably due to reporting bias um and other kinds of other kinds biases so this is a key question is outcomes count as important so here's an example from a fairly recent study of expectancy effects and anxiety they compared uh people getting an SSRI in the typical open label way which is in the blue line with people who got a hidden SSRI they didn't know that they were getting the SSRI and that difference is a placebo like effect or an expectancy effect um there was a substantial drop and anxiety that was caused by uh getting the knowledge that you that people are being treated so the question is does that actually count as a meaningful effect and um you know I think there's it's right to debate and discuss this um and it relates to this idea of what I'll call heuristically depth that um this effect might simply be people telling us what we want to hear that's a communication bias or a so-called demand characteristic that's been studied since the 50s um it could be an effect on how people feel and their decision making about how they report feelings it could be an effect on the construction of anxiety in the brain it could be uh an effect on uh a deeper effect in potential potentially on some kind of lower level pathophysiology some kind of effect on the organic causes of anxiety so the gold standard has been to look for these organic causes um and it gets very tricky when you define outcomes in terms of symptoms like uh is true with pain with depression related uh um symptoms uh anxiety related symptoms and more mental health um in pain what the field has been trying to do is to look at Pathways that are involved in uh early perceptual effects um no susception and on um those Central circuits that are involved in constructing the pain experience to ask if those are affected uh and what we've seen this is sort of the most veloped area I think in human Neuroscience of placebo effects and we see reduced responses to painful events in many relevant areas um including in the spinal cord areas in some studies that that um are known to give rise to no susceptive input to the brain um there's increases in activity in punitive pain control systems that send descending projections down to the spinal cord um and there's release of IND genous opioids with Placebo treatment in some of those pain control systems and other areas of the frontal cortex and forbrain so these are all causal effects of placebo treatment that seem to be relevant for the uh the construction of paint and what is remarkable is that the effects in the frontal cortex that are the most reliably influenced by Placebo including the medial Perell cortex and the insula and other areas um really are not just involved in pain of course they really effects on systems that are involved in highlevel predictive control of motivation decision-making and perception so an emerging concept is this idea that uh what these circuits are for uh and what a lot of our brain is for in general is forming a predictive model of what's going to happen to us what situation do we find ourselves in so these cortical circuits are important for representing hidden states that we have to infer and that's another way of saying uh meaning it's therefore understanding what the meaning of events is right if it's an eye gaze what's the meaning of that look uh if it's a movement what's the me what's the underlying meaning of the movement and it's that underlying situation model or predictive model that guides how we respond to a situation and what we learn from experience so these systems in the brain that are influenced by Placebo provide joint control over perception over behavior and decision making including whether we choose to smoke or not smoke or eat more or eat less uh and the body through the autonomic and neuroendocrine and immune systems so broadly speaking um there's this joint control so this is one example where we can get closer to pathophysiology with some forms of placebo effects and this is for brain control over all of the various brain
Segment 5 (20:00 - 25:00)
stem and um spinal uh centers that are important for particular kinds of regulation of the body the muscle the respiratory muscles the heart the intestines and uh immune responses as well and when we look in the brain um the most consistent correlates in metaanalyses of um of immune changes in the body are those that seem to play Central roles in placebo effects as well like the ventro medial prefrontal cortex um and another important um development in this and aspect of this is the idea of uh parallel models in non-human animals and in humans um in particularly those that use classical conditioning uh so there are many kinds of pharmac pharmacological conditioning in which a queue is paired with a drug uh over time usually over several days and then the cues alone like the injection alone can come to uh illicit effects that sometimes mimic drug effects and sometimes are compensatory responses that oppose them and one of the most famous was the phenomenon of conditioned immunosuppression that was first published by Bob ader in 1976 in science and has since been developed quite a lot um so this is a from a review by man Shadow's Group which is a very comprehensive review of different kinds of immunosuppressive responses and the point that I want to make here is that um there's Emer there's increasing evidence that the insul cortex as an example is really important for storing memories about context that then get translated into effects on cellular immunity that are relevant for the trajectory of health and disease in Broadways and um those areas and insula are similar to those that are involved in Placebo effects in humans on pain itch cough disgust and other uh other conditions as well um so there is uh the potential here for memories that are stored in the cortex to play out in very important ways in the body um and that can influence mental health directly and indirectly as well um and I want us to move toward wrapping up here with um a couple of ideas about why these effects should exist why do we have Placebo effects in the first place and two ideas are that we need them for two reasons one is for predictive control the idea about what we need an evolved brain for a highly developed brain is to anticipate those threats and opportunities in the environment and respond in advance um so it's not that we don't respond to the world as it is we really um as it could be or as we think it will be um and the second principle is um causal inference uh that we what's less relevant is the particular sensory um uh you know signals that are hitting our apparatus at any one time and what's really more important is the underlying state of the body and the world what's happening and just to illustrate those things one example from Peter Sterling is this very complicated machinery for regulating blood pressure when you stand up and when you are under psychological stress and we need this complex um set of Machinery in order to predict what the current what the future metabolic demands are so our blood pressure essentially like other systems responds in advance of challenges and that's why we get stress evoked um autonomic physiology and an example of the second is a simple example from Vision if you look at these two squares that we've circled here you can see that they probably look like they're different colors um one's brighter and one's darker but if I just take away the context you can see that the squares are exactly the same color right um and so you don't see the color of the light hitting your retina what you see is your brain's guess about the underlying color of the paint or the color of the cubes that discounts illumination and factors it out as a cause so what our perceptual systems are doing is causal inference so with pain itch or nausea for example other symptoms uh you don't um or mood or motivation you don't feel your skin or your stomach or your body in a direct way your brain is making a guess about the underlying state from multiple types of information and this really starts with our memories and past associations and uh our projections about the future so I'm using pain as an example because we study it a lot but the idea is that the pain really starts with these projections about the future and there's a representation in the brain of the current state of threat and safety if you will no susceptive input from the
Segment 6 (25:00 - 30:00)
body plays some role in that but it's really the Central Construction uh that integrates other forms of context what's the look what's the what kind of support are you getting um that together determines what we end up feeling uh and there are different kinds of responses that are linked to different parts of that system but the idea of of suffering and well-being of fatigue and motivation uh all those things I think are related to the current uh state um there are many open questions um you know one is which outcomes count as important for determining whether intervention is Meaningful um can we separate changes on decision-making and suffering from a response biases that we really shouldn't consider uh important for clinical research um secondly can we identify outcomes that are affected by real treatments drugs and devices but not placebos and how can we use those outcomes in clinical trials and Advance uh both you know are sort of Advance on the regulatory front as well as on the uh the scientific front um third what kinds of experimental designs will help us separate specific effects from these broader context effects and is this a reasonable goal can we actually separate them or do they often work together or synergize with one another so do they interact um fourth can we predict who will be a placebo responder from personality genetics perhaps or brain responses can we use this to maximize our treatment effects in clinical trials and improve the pipeline um and yes it's unclear whether that's possible um and finally um how can we use all of these factors we've discussed alongside other treatments that are um current Medical Treatments to improve outcomes um with that I'm just going to uh introduce are the next the rest of today I realize we're a little bit long um getting started hopefully we can make up some time here um but now I'm we're going to start our first session which is about um perspectives on Placebo and Drug trials from um Michael deki and N Ken and uh Tiffany fion uh and so this is going to be about the sort of history and state and um of how Placebo effects interface with the regulatory environment then we'll take a break and after that we'll continue to uh the rest of the sessions so without further Ado I would like to turn it over to Mike thank you I think NE is going before me correct me yes I am ah okay me thank you yeah because I'll do the first part uh for the historical uh perspective um hi I'm nikin and I'll be uh talking about uh historical perspective on Placebo response in uh drug trials this is my disclaimer slide um even although I'm currently an employee of uh neurocrine uh biosciences uh the part of this present uh main part of the presentation today is the work that uh conducted uh during my tenure with us Food and Drug Administration the presentation reflects view of my view and it's not be quoted with all the oran organizations that I was affiliated with and currently Affiliated let me start with a brief overview of what FDA require for drug approval FDA regulation defines that there should be substantial evidence consisting of coming from adequate and Well Control trial the usual interpretation is that it would require two positive randomized control clinical trials however in terms of drug approval process we use holistic approach in review of clinical efficacy and safety coming from uh clinical trials so in FDA uh data from both successful and non-successful study positive and negative studies as a package when the uh industry or the drug sponsors
Segment 7 (30:00 - 35:00)
submitted new drug application packages to the agency and then these uh mainly the efficacy results generally would come from shorter term efficacy data and safety data will be according to the I requirement uh 1,500 patients 3 to 600 for 6 months and uh at least 100 patient for year uh generally the maintenance efficacy or also uh relapse prevention trials are conducted mostly post approval in the US so uh the data that I'm presenting was uh conducted as a kind of a pool analysis from uh the data that was submitted to uh a agency in terms of in support of uh new drug applications why we did that uh data mining effort and as you know High rate of placebo response and Decline and treatment effect is overtime in Psychiatry was the main major concern at the time when we did this uh analysis um in there were increasing conduct of uh trials at clinical trial cite outside the US and we are looking into applicability of such data from non us sites in the US population so uh we did uh exploratory analysis of pooled efficacy data uh from two different uh psychiatric indication major depressive disorder and schizophrenia uh we have a data level coming from trial level and uh subject level data and we uh for uh depression uh across the uh application package we have uh Hamilton depression rating scale as the common uh primary or key secondary or secondary efficacy rating scale and schizophrenia um uh application packages we have pens which is positive and negative syndrome scales so we were looking at those two uh endpoint measures uh and then um did some exploratory analysis and then summary from these findings and the processes and challenges experienced in our effort looking into these databases will be shared today uh let's let me start with M uh depression trial level data that we looked at uh it consisted of 81 RCT short-term trials so it's a it spends about 25 years so these are mainly uh ssris and snris uh an anti-depressant um from that 81 uh clinical shortterm control trial uh total number of sub subject was over 20,000 subject 81% enroll in US sites and uh as you could see here majority were uh quite Caucasian female and mean age was uh around 40 43 years of age and Baseline HD scores were approximately 24 and dropout rate average dropout rate in these trials were approximately 33% um we explored treatment effect and trial success rate based on the questions raised about applicability of data from non- us side to the US population this is the overall results that uh we uh we published in uh 2011 paper we noticed that uh both placeo and Drug group from non us uh tended to be larger uh change from Baseline in hemd 17 total scores than those observed in the US uh you can see on the left hand column non USI Placebo response is approximately 9 and a half and us is 8 uh but uh drug effect were also larger
Segment 8 (35:00 - 40:00)
slightly in non- US sites and uh us is uh slightly lower so if you substract drug plus eval differences it's average is about the same for both us data coming from both us and non- US side so it's about uh two and a half points hemd total difference so uh what we see overall over 25 years of uh anti- uh depressant trials is that there is increase in highly variable Placebo responses across trial slight decline in treatment effect moving uh from approximately three points difference in HD total towards two points drug and Placebo difference uh and a trial success rate was slightly lower 55 versus uh 50 and as part of that analysis we also look at uh any difference in uh data between fixed and flexible doses so 95% of the trials that is in the database you utilize flexible dosing re uh design uh regimen and so Placebo responses it were quite similar treatment effect was slightly larger for flexible doses as compared to fixed dose uh and we pointed out that in our analysis we use uh data versus a data coming from the treatment arms versus number of Trials uh as a denominator in the C uh in the calculation so slightly higher trial success rate for uh for um for fixed dose trials if which is 57 plus vers per versus flexible dose uh 50% so and some of you may already know that there was a earlier paper published by Arif Kon and his group uh the same dat similar database but the uh it was uh data sets coming from trial conducted between 1985 to 2000 and from that analysis it was showing that 65 61% of the flexible do studies uh versus 33 for fixed do uh results for in terms of success rate and the uh and cons use uh number of treatment arm as the denominator and uh and um and if you use if you look at the uh results uh it's a flexible dose is also uh 60% compared to 31% of fixed however in our larger database data included conducted after 2000 that's 2001 to 2008 our findings are in favor of still fixed dose design with uh success rate around 60% for fixed dose arm compared to uh 34% for flexible do um so we think that uh the more recent trial with you uh fixed those studies s the success rate is slightly higher um so in addition to trial level data we also look into uh subject level data from these trials for so from subject level data we initiated with 24 randomiz control trial data from uh then we expanded to 45 and uh and the main thing that we were looking at was the uh what could we use in terms of responder definition do we need a HD total cut off and uh so from that analysis we noticed that overall 50% change for Baseline is a sufficient to Define uh respond status and uh and um HD total cut off is not necessary the
Segment 9 (40:00 - 45:00)
whether you use percent change or HD total cut off or both they we would capture uh same more or less the same folks as the responder meetings responder uh status and then another item that we looked into was for optimal trial duration and we if you from generally from eight weeks trials at the ones that would give overall successful uh trial results and we looked into whether if we shorten it to 6 weeks whether we'll get uh similar results so it was like somewhere in between that maybe shorten if you could see it the two points difference at week six and uh and the another item that uh we look into was time to treatment discontinuation as a uh instead of change from Baseline as a primary efficacy endpoint and uh the data support not supportive of time to treatment discontinuation as a alternative primary endpoint for drug trials so I I'm going to cover a little bit about uh efficacy results from maintenance efficacy trials also known as relapse prevention trials and we where we usually use uh randomized withdrawal design um and they are generally uh not regulatory requirement in the US to do maintenance efficacy study uh but uh if the agency is would see it would be needed uh then uh we'll communicate with the uh drug sponsor uh before coming in with the application so um in as you could see on this slide um this uh longer term uh maintenance efficacy study generally designed as open label treatment uh for approximately 12 weeks and if once they meet the stable responder status will be randomized into double blind uh R randomized withdrawal phase to either continue on the drug or uh or the other half will be into Placebo the end point generally used is the time to relapse or relapse rate and we did uh overall look at Tri level data from 15 randomized uh control maintenance uh randomized withdrawal trial uh between that was conducted between 1987 and 2012 and um and you can see demographic disposition is more or less the same for these trial average number of uh subject per study is in the 500 and H HD score at Baseline prior to open label is more or less the same uh randomization after they meet responder status to drug and Placebo uh hemd total score is about 9. 4 and then uh relapse and response and relapse criteria used in these studies are varied across the study and stabilization period is also varied regardless of that these are uh anti-depressant approved uh based from short-term study and what we noticed that once you get approved uh for uh based on short-term efficacy you will also see uh maintenance efficacy uh based on the results from this uh study and this is just the overall uh um slide that shows uh the duration of open label uh open label response criteria response rate double blind study period relapse criteria and uh difference between Placebo relapse rate and relapse rate in the drug group and percent reduction and you could see that at least 50% reduction in terms of uh relapse difference you will see with the drug treatment
Segment 10 (45:00 - 50:00)
yeah these results were uh published and overall I just want to summarize the results saying that almost all the trials are successful uh open label phase uh mean treatments response is about 52% and uh and when the those be meeting respond status going into double line randomized withdrawal phase there's a average 50% reduction in relapse rate for drug treatment group as compared to Placebo and uh and in the in that paper we have side by side comparison of uh subject level data uh in terms of uh relapse uh Survivor analysis keplan Meer curve uh and uh let me summarize a little bit about schizophrenia trial data we did uh have a pool analysis of 32 R randomized Placebo control short-term clinical trial that was conducted between 91 and 2009 uh and those are main mainly atypical antic psychotics and this slide shows the number of subjects along with uh mean age and uh demographic distribution along with the mean Baseline and Pen's total score and uh and we we uh provided The observed in increasing Placebo response uh St stable drug response and declining treatment effect over time in North America uh region one thing we would notice was that treatment effect decreased as body weight increased in uh North americ trial uh patients and um and this is uh another uh FDA also conducted uh post 2009 period uh analysis and this slide shows uh so comparison between pre2 2009 trials and post 2009 and you could see that PO uh po predominantly multi-regional clinical trial in recent years uh dropout rate is higher slightly higher but uh continuing trend of increasing Placebo and decreasing treatment effect when you look at uh in combination of two uh two different uh pool analysis is that it's it still persists over 24e period so those um both MDD level uh pool data analysis and schizophrenia analysis data analysis is for TW uh 25 years period yeah so uh I'm just going to let folks know a little bit about challenges in doing these type of pool analysis is the data sets uh data standard issue and uh it was uh because of the technology in those times difference we do not have subject level data trial conducted before 1997 in the database um uh and of of course always the resource is an issue and the main point that I would like to bring it for everyone's attention is the collaboration in terms of uh solving this major issue of uh Placebo response uh I'm going to stop here and uh I'll let Dr Mike de key uh continue with this topic from uh industry uh perspective Mike uh thanks NE and uh oh I sorry just second here having problems sharing my screen I got to make this full screen
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first okay great and then oh sorry minor technical problems I will be have it fixed in a few seconds there we go yes uh thanks for the introductions and and thanks to H for inviting me to present here uh as ni said very well my background is industry I'll be presenting this from a kind of an industry perspective um I've spent 25 years working at a clinical trial site uh at Big Pharma small biotech and a vendor company all in CNS clinical development um uh mostly drugs um and I'll uh um I'll uh I'm also a board certified psychiatrist and practice for about 20 years at IU School of Medicine part-time um and I'll talk about relevant disclosures as they come up during my talk um because I have worked in this field uh a fair bit um so that being said let's there we go this is just a high level overview of what I'll talk about um and again from the industry perspective in contrast to the um Rich intro on your camera's off now if you want to turn it on I will it on I apologize thank you there we go um so um the U um as I said I'll be presenting from the industry perspective and for the most part my definition of placebo response throughout this talk is if the patient got seven points better on Placebo and the patients got 10 points better on drug the placebo response was seven points and we'll be focusing on that perspective and uh um Tor gave a great overview of of many other aspects of understanding Placebo and we'll talk and my uh esteemed uh co-presenters will talk more about that too but again I'll give you the a historical perspective and mostly I'm G to try to go through some data um some of it a little older newer that um of things that have been tried to reduce Placebo response and or improve signal detection drug Placebo separation which especially in a in a proven effective therapeutic is probably the better way to look at it and this is just a list of some of the topics I'll cover I've got a lot of ground to cover um and this won't be exhaustive but um I'll do my best to get through as much of it as possible for you today um Dr Ken already talked about um designs including the randomized withdrawal design uh important to keep those in mind I'll briefly mention a couple of other major designs here that are worth keeping in mind the crossover design has an advantage that it's much higher statistical power because in uh the ideal way to use this is to use the patients themselves as their own control groups so you're doing within subject uh statistics which make this much more powerful you can have do a much more statistically powerful study with far fewer patients a couple of important cons are there can be wash out effects in the drugs both pharmacokinetic or even if it's completely washed out the patient's depression or whatever might have gotten to a better State and that might be lingering for some time and um and because of these U uh over lap effects there you can't be totally certain that the Baseline of phase two is is the same as the Baseline of phase one and that's an important issue um uh and those overlap effects are important but diseases with stable baselines and I think in the CNS space things like adult ADHD um could be things that you would consider for this perhaps in proof of concept rather than confirmatory but I'll leave that to U my colleagues from the FDA um sequential parallel design um this has been uh presented a long time ago and has been uh published on much um this is a design where some of the patients get drug in the phase one and others get Placebo they're randomized just like a typical parallel arm randomized study um however in the a second phase the placebo nonresponders specifically are then randomized to receive Placebo or drug so this has a couple of advantages is one is that there are two phases from which you can combine the data and the other is that this second phase enriches for Placebo nonresponders um just like the randomized withdrawal enriches for drug responders so um and this has been published on a fair bit in the literature this is a slide that hasn't been updated in a while but the results um even back uh a few years ago were you know out of you know quite a few trials that have been reported on there was a ction and Placebo response in phase two the drug Placebo difference
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improved and the P values were better and so forth so um the so this is a a an important trial design to know about um Dr Faron will talk about I think one example of this having been used recently um it's a little bit hard because you can't really do this within trial comparisons of different trial designs that's a limitation the uh so these are all cross trial comparisons really um but the try and there are some advantages and disadvantages um it um by using patients twice you might be able to do the trial with a somewhat fewer patients save money save time um on the other hand there's two phases so that in that sense it might take a little longer so various pros and cons like anything um and then um I'm gonna talk about Placebo leadin so historically people did single blind Placebo lead lead-ins where all patients would get Placebo for the first week or so blinded to the patient not to the staff and then uh if they had a high Placebo response they'd be excluded from the study um typically it was about a week and about a 30% placeo response but it varied travetti and Rush did a great review of this over a 100 trials as you can see and um little evidence that it really improved Place reduced Placebo or improved drug Placebo uh separation um this is some uh work from my early days uh earlier in the 2000s at Eli Lily when I worked on simala duotine for about seven years we did something we call a variable duration Placebo leadin um where we this was the design as it was presented to the patients and to the site uh Personnel that randomization would incur at any time between uh week uh visits two and four which meant they were on Placebo for either zero to one to two weeks usually in fact they were on for one week um this has some pros and cons again practically um the this the the placebo leadin adds a week or two of timeline and cost um the patients that the way this is designed and to maintain the blind the patients that you quote air quotes throw out for um having too out ofo response have to be maintained throughout the study which costs money and means that your end overall end might need to be higher um so uh time and money implications when we looked at this uh Craig malen ICI um uh published on this and um we found that the average effect side did go up pretty substantially this is Cohen's D effect size um but you also lost some n when you excluded some plba responders so the the frequency of significant differences did not go up substantially in this power in this analysis um moving on Dr Ken referred to this study by RFC con where flexible dose trials did better than fixed dose I would say that you know the database that Dr kin presented from the FDA bigger database um you know less publication bias and things like that so I would I would lean in favor of of um preferring that but I would also say that my if you focus on my last bullet point there's the clinical intuition about this and and ask yourself the question if you had a case of depression and you could go see a doctor that would only prescribe 20 milligrams of Prozac to every patient or a doctor that would prescribe 20 milligrams and if you're having side effects maybe titrate down and if you're not having aacy might titrate up you know which doctor would you rather go to so I think on some level it seems to have good faith solidity that adjusting the dross to individual patients should lead to better efficacy and better assessment of of true um tolerability and safety and that should do a better job than adjusting the dose of placebo um uh but importantly the because Flex dose studies are typically two arms one drug with a flexible dose and one Placebo and fixed those studies are frequently um dose finding studies with say uh one arm of placebo and maybe three arms 10 20 and 40 milligrams of drug um so the number of treatment arms is is practically it's very it's confounded with fix versus flexible dosing and likewise and and that may matter and the percentage randomized to Placebo and again this is confounded with number of arms if you do equal randomization in a two arm study you've got a 50% chance of placebo a forearm study you've got a 25% chance of placebo and again it makes good face valid face solidity good sense that if your chance of getting Placebo is much higher that you might have a higher Placebo response rate you might be or your chance of getting active drug is higher and that's what pop cost has found in a metaanalysis in depression and malr again in a Mal in a metaanalysis of some Lily schizophrenia data um so uh so
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those are all confounded I um and and they have pros and cons and you do need to do some dose finding with your drug anyway so um uh they're all designs that have um pros and cons to lead to better outcomes um better scales this is a simple um analysis taken from that same paper that did the double blind Placebo lead in with malan cot and um we just looked at a a pulled set of 22 rcts I think these were mostly or all duotine studies and depression studies and the hamd1 17 item scale had an average effect size of about 38 um but some of these subscales which are you know five six seven or eight items long of items among the 17 in the hamd if you in other words if you throw out half of the data from the hamd you can actually get a better effect size and so this is something to think about at least in proof of concept obviously these subscales would need to be validated for Regulatory and other purposes um but uh good to know that there are different approaches and too if you have a drug that you believe based on earlier clinical data or pre-clinical data that are more likely to be efficacious in certain domain symptom domains that's important to um statistical approaches this is a little bit dated at this point in time but there a lot of uh important statistical uh issues to take into account when I entered the industry last observation carried forward llcf was the gold standard there have been a lot of papers published on mixed model repeated measure that protects better against both false positives and false negatives um uh gives you better effect sizes here um and here almost you know 30 or so percent bigger which is pretty substantial and I'll show you uh that later um so uh better protection against false positives and false negatives mean we've got more false we've got more true positives than true negatives which is exactly what we want in in therapeutic development um and um I'll talk here now about different implementation uh strategies during the trial Central Raiders and and a lot of people use different terminology here so my terminology for Central ratings is when a Raider is remote and actually does the assessment they're asking the questions they're hearing the answers they're asking for clarification they're doing the scoring Etc and these Raiders can be more easily B blinded to protocol criteria more easily uh independent of pressures to meet enrollment and so on and so forth uh note here I was a previously an employee and stockholder and consultant to metavante which was one of the companies that pioneered doing the central ratings um so uh I'm not no longer I don't have any stock no uh Financial conflicts of interest now but I uh did work with them for a while one advantage to centralized ratings on the right is that you can simply use fewer Raiders which reduces the variance that all of us humans are going to contribute um these people can be trained together um uh more frequently and and more consistently and uh that can reduce variability too um just a some perspective um and Tor presented some nice stuff from other therapeutic areas too um is that you know uh in Psychiatry and CNS most of our outc are subjective and highly variable and um and probably need to be um improved upon in some ways despite that in other areas where there's there's probably less inherent variability they've already um standardized the fact that you know centralized BL blinded review or assessments by at least one a second or a third uh person for lots of other types of Therapeutics and these are relatively old guidances from both EMA and FDA uh mandating this in other therapeutic areas so then to get back to the data on centralized ratings um metavante was able to conduct about seven studies where they did do within study comparisons of site based ratings and centralized ratings and across these seven studies I my interpretation and you can look at the data are that about five of seven were um green they were clearly uh clearly showed better lower Placebo responses or if there was an effective drug better drug Placebo separation um with centralized ratings and two showed uh pretty uh equivocal or not impressive um uh differences uh and again I I'm a former uh employee and consultant of metavante here's one example a large Gad study um with uh that had sepram as an active comparator um this is a site qualified and rated patient Central qualified and rated and um and you can see the effect size was about twice as big in ham a points the Cohen D effect
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size here um was about twice and with and this chart we put together when I was at metavante uh illustrates that a doubling of the coen's def effect size means that you can either reduce your sample size by uh by 75% and still have the same statistical power or you can select a sample size of say n of 100 and your power goes up from about 60 to almost 100 the more important way to read these Powers is that your chance of a false negative your chance of killing your drug when you shouldn't have is 38% uh with this effect size and and less than 1% um so then there are other approaches than having doing having a central Raider really do the assessment remotely and um you can review the work have a third party review the work of the site based Raiders uh metavante their competitors verisi signant and and others all offer these Services now and other companies do too I'm not trying to and and I don't know of any uh reasons to prefer one or versus the other um so you can review The Source documents audio or video recordings um this looks like it should work it has good face validity I've run trials with this in it and um but I'm just not aware of any controled data I haven't seen studies where people have done thirdparty remote feedback um in say half the sites or half the Raiders and not the other half and shown restiveness so any of you have those data please send them to me I'd love to incorporate those uh but as I said it has good faith vality um you know if you're giving people feedback on the quality of their assessments all the time the Raiders should do nothing but improve um there's a an effect called the hawthone effect that people behave differently when they know they're being monitored so that's so this should work and let me talk spec a little bit about operations doing central ratings is pretty burdensome you've got to coordinate ratings with a Raider that's somewhere else maybe in a different time zone um and the patient and the site um it's expensive it's labor intensive um this is less labor intensive because you don't have to viiew all the recordings um it can be done not in real time um and so it's it's less burdensome it's less expensive um not clear exactly how efficacious it is but it has good facility um or just to replace those human Raiders with computers um there have been lot of different groups that have done work on this um and I'm G to jump right into some data um these are uh data from you'll recognize duotine again and um John Grace was one of the early Pioneers in this and a company called Healthcare Technology Solutions and this was done with patient self-report using ivr um and so just basically a a uh an old-fashioned keypad on a phone is good enough to do this and the patients have report this and um for those of you who don't know this separating 30 and 60 milligrams of duotine is really hard we never really saw this with clinical rating scales um but patient self-writing using a computer um in days uh sh really saw really nice signal detection um uh and really rapid signal detection um and this is just another example of a different measure P GI um and again really impressive Separation on these or uh humans are good and computers are good why not uh combine the both and uh Gary Sachs founded a company called con concordance um many years ago and it's been merged into other companies he's that he's and this is part of signant now and um it showed that if you did a clinician rating and a patient self- rating by computer and compared them you could learn a lot from the points that were not um were discordant and um and you can learn a lot about um both uh severity ratings but also uh inclusion exclusion criteria diagnosis things like that um so that's valuable let's talk about professional patients quickly um this is just an anecdote and I generally State wife anecdotes but I found this is really compelling this subject returned to the site um with their unused pills from their pill bottle unfortunately he had a pill bottle from a different clinical trial it same sponsor and protocol um and this is um this is probably a common problem this is uh a phase3 program in depression where they had up to 4% uh duplicate subjects at least in screening um could be higher we don't really know how big the problem is but we know it's a kind of a it's a tip of the iceberg issue because you can look you know there probably aren't too many patients that are bold enough to try to enroll twice at different in the same study but um they might en recall enroll sequentially they might go through
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multiple screenings until they get in they might be in different Studies by different sponsors for the same or even different as Tom shivitz has shown um uh indications they'll be in a bipolar study this week and a schizophrenia study next month and a depression study the one after and these patients may or may not be compliant with medication and all sorts of other protocol features um anecdotal data on subject selection there are lots of websites out there that will teach you how to be a bad patient in a clinical trial um and I just want to note not that it's a bad thing I love clinical trials. gov I use it a lot but any tool can be used for for good or bad things or almost any tool and uh the reason I mentioned this to you again as you are posting your trials on clinical trials. gov you want to be transparent enough to share what you need to share but you might not want to help them too much with specific details of certain inclusion exclusion criteria that are subjective and can be for lack of a better reward fate um these are the top three of these are all companies that do um uh duplication check um uh for duplicate patients that might be in your study and another study that they're having in their database um I I've worked with all of them they um and worth noting this is relatively minimally expensive you just have to get a few demographics on each patient at screening so the also the site and patient burden are pretty minimal um and AI cure is really more of a um medication adherence platform but of course the really bad uh professional patients don't want to take the medications either so there is some overlap in between professional patients per se and medication adherence um medication adherence I'm going to go through this rest of this quickly in the interest of time um uh difficult to know with certainty um not as helpful done after randomization certainly if you need intent to treat um but a PK collection is important it's one way to do it is just PK collection that is a gold standard that tells you that the drug is in the patient's body um uh and I'm gonna skip this slide too if half the patients don't take their medicine you can imagine that the power is very bad and I did consult with um AI cure previously and that's an important disclosure too the reason I like AI cure not so much because I consulted with them there are many medication adherence uh platforms out there on the market this is the only one where I've seen um uh evidence that their platform is consistent with correlates with predicts PK values so if I were you that's an important question to ask and then you have to also ask about all the operational issues too biomarkers I mean when we've got biomarkers they're great you know if you've got a pet in and you can um help you narrow down the dose and and really demonstrate that you're uh engaging the target that's fantastic um this is just a an example of a pet Lian this is another biomarker This was um this is hot off the press this was presented just a few weeks ago at ascp and the idea here is basically um taking Baseline demographics and putting them all into an AI model to see what predicts Placebo response and Drug placebo separation um this is another company that I work with and I work with currently so that's take that disclosure um with as many grains of salt as you believe um we did a a blinded analysis of Baseline eegs and identified three clusters in a um a placebo controlled Zola study in the whole overall study it just failed to separate and we identified three distinct clusters one of which um has a huge Co D effect size and P value even in a um a little less than half the population another cluster that really weren't responders at all and a cluster the third cluster that's less than 20% of the population that had fantastic Placebo responders and ter responders and terrible drug responders um so this needs more validation like all biomarkers um and I just want to leave this with the point that uh biomarkers are great as we continue to understand the biology and the pathophysiology better um but at first we are going to have to validate these against the gold standards and the current gold standards are um are are variable and biased and imperfect um so to close on a relatively optimistic note this is a uh red green yellow um green is good yellow is questionable red is red is probably not that worth it um uh my own personal subjective assessment of some uh but the takeaway is that a lot of these things can be helpful especially when fit for purpose with the
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therapeutic that you're developing the phase of development and your strategic goals for that uh therapeutic um so I'll end there thank you very much for your attention look forward to questions and uh and so forth great thank you Mike for time reasons we're going to go on to our next speaker but just to let everybody know um there's a Q&A and people are posting questions there and our panelists can answer the questions in the uh Q&A panel as well as in the um uh during the discussion phase so keep the questions coming thank you right Dr fion thank you great thank you let me just get this all queued up here and you're seeing the um the actual slide right because I'm in the presenter viw and can't see the zoom anymore oh when I'm not seeing it yet oh wait a second hang on oops let me try again ah there we go helps if I click share first before I are there yes let me move this out of the way oops and here we go all right so thanks everybody and good afternoon as we've already said my name is uh Tiffany Faron and I'm the director of the division of psychiatry in the center for drug evaluation and research at the Food and Drug Administration um so because I'm bed I have no conflicts to disclose and this afternoon I'm gonna be providing a regulatory perspective on placea response and psychiatric trials so far today you've heard a little bit of a historical perspective from um Dr kin who's actually my former team leader when I was a new reviewer um and she showed us that not only do we have um a high rate of Poa response and Psychiatry trials but the extent of that problem has actually been increasing over time and then Dr de just presented some of the strategies that have been proposed for dealing with this problem and in some ways uh you know they're somewhat limited utility in some examples um so I'm going to talk a little bit about the importance of placebos for regulatory decision-making and give a few examples of placebo response mitigation strategies and registration studies and then I'll go on and talk a bit about Placebo response in other disease areas and end with some thoughts on what may ultimately help us to um to resolve this issue all right so I want to start first by expanding a bit on Dr kin's presentation and just quickly presenting some updated data um I saw that there was a question in either in the chat or the Q&A about depression studies and honestly we don't have too much more from what she presented in um in depression and also the things that we've approved more recently have um different designs different um uh lengths of treatment and things like that so it makes it hard to combine them with the um existing data set but here um I've got figures for schiz frenia and bipolar and they look a little different from each other because I pulled them from a couple of different presentations but essentially the data points in each figure represent the change from Baseline to end point on either the pans on the left or the ymrs on the right in clinical trials of atypical anti-yo medications for the treatment of either schizophrenia or bipolar one disorder and the drugs included in these figures are ones for which we have both adult and pediatric data so on the left you can see that the trend for increasing Placebo response over time is also evident in the Adolescent trials and then on the right we have data from adult and Adolescent bipolar one studies which Dr kin didn't present um so there are a few data points in this side um fewer than in schizophrenia um but the trend is less obvious from the dots alone but if you throw on the trend lines which are here on the figure that allows you to see that the same phenomenon is also at play in the bipolar disorder studies all right so let's go back to basics for a minute and talk about why we need placebos and clinical trials in the first place so simply put Placebo controlled studies are bread and butter um and in order to support a marketing claim companies need to provide substantial evidence of Effectiveness for their drugs um KN went over this a little bit as well this is generally achieved with two positive adequate and well-controlled clinical studies and the characteristics of adequate and well-controlled studies are outlined in the code of federal regulations so there's seven different characteristics that are listed in the CFR but one of those states that the study has to use a design that permits a valid comparison with a control to provide a quantitative assessment of the drug effect so more often than not that's a proo control um and basically we just need some way to determine that the drug itself is actually doing something so if the treatment response in the drug arm is greater than the response in the placebo arm then that difference is assumed to be evidence of a drug effect but that may be oversimplifying things just a little bit um it's important to remember that the difference between an effect and a response so the response is the observed result like the change from
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Baseline on a pans or a m score and the drug effect can be one component of that but adherence to the drug timing of the assessment other factors also influence the observed response and yes a portion of the drug response is probably attributable to placebo effect same thing with Placebo response yes the placebo effect itself is a component of the response observed but you also have things like the natural history of the disease or regression to the mean or you know when we talk about adjunctive treatment you could be that the other treatment as part of that effect all of those play a role in The observed response in a study so what exactly is it that can account for the placebo response rate in our clinical trials so Dr deki went over several of these examples earlier but let's start with expectancy and this is a big one if folks expect to have some benefit from a drug that they're taking they often times do experience some benefit um the structure of a clinical trial can also contribute to the placebo response folks are being seen on a regular basis they have a caring clinician who they interact with routinely those things can in and of themselves be somewhat therapeutic um the fact that we use subjective outcome assessments is another aspect of this that I want to highlight um because in Psychiatry trials we can't draw Labs or order a scan to ensure that we have the right patients in our trials or to objectively assess their respon to the drug what we have are clinician interviews and patient reported outcomes and oftentimes these outcome assessments involve a report from the patient that is then being filtered through a clinician's interpretation and then translated into a score on a scale so there's a lot of room for variability in that and the distal nature of that assessment from the actual biological underpinnings of the disease can be problematic and it certainly prone to misinterpretation of and antibiosis of all kinds so again Dr deki also mentioned how um enrolling in appropriate participants can impact Placebo response um if you have folks in the trial who don't actually belong in the trial whether that's the professional patients that he kind of finished with or whether it's folks who just don't quite meet the inclusion criteria or who have been misdiagnosed somewhere along the line um any number of things that's going to increase the variability in your study and could potentially result in increasing the placebo response so of course there's lots of other factors that can contribute to the placebo response but because Dr Dei spent a lot of time on this already I just wanted to highlight these few all right so next I want to talk a little bit about ways in which we could potentially manage the placebo response in clinical trials and first I want to present one option that we actually have not yet accepted for new drugs and Psychiatry but it's an option that actually takes the placebo out of the equation entirely we have a bunch of approved anti-depressants antis psychotics so at this point you might be asking why we can't just do non-inferiority studies and attempt to demonstrate that the new drug is no worse than some approved drug so the complicating Factor here is that conducting a non-inferiority study requires defining a non-inferiority margin and in a non-inferiority study you're trying to show that the amount by which the test drug is inferior to the active control is less than that pre-specified non-inferiority margin which is M1 and M1 is estimated based on the past performance of the active control but unfortunately because of this secular increase in Placebo response over time we can't really estimate N1 it's a moving Target it so even though we have things that have been approved in the past we don't know that the margin by which the active drug was Superior to Placebo in the clinical trial that supported its approval is the same margin that would be observed today under similar circumstances so because we can't set a non-inferiority margin we can't do non-inferiority trials at least not for regulatory purposes in psychiatry another strategy that's been employed um in a few trials at this point um is sequential parallel comparison design and again Dr deki went over this briefly so you have some idea of the principles behind this already now recall that this is the design in which you have two stages and the first is intended to weed out the placebo responders so that in the second stage the drug Placebo difference is Amplified so there's some statistical concerns with this type of study design related to the relative weights of the two stages and the impa of dropouts but we have had one application where trials that employed the kind of trial design made it to the new drug application stage and this application was presented at an advisory committee meeting back in November of 2018 so there is publicly available information for me to share even though the application ultimately was not approved um this was for a fixed dose combination of BU orphan and sad dorphin that was intended for the adjunctive treatment of major depressive disorder now the figure on the right hand side was taken directly from the AC briefing book and it shows diagrams of the three studies in which spcd was employed of
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part of as part of the clinical trial design the important thing to observe here is that you do in fact have a large Placebo response in stage one and a much smaller two but what we don't see is the expected amplification of the drug Placebo difference in stage to so as I said at the advisory committee meeting either spcd isn't working or the drug isn't working so regardless of the outcome here the important take-home point is that we were able to file an application with spcd in it we had reached agreement with the applicant on the weights for the two stages in the analyses and there weren't many dropouts in stage one of the studies so we were able to overcome two of the big hurdles um for this design in this program but if we receive another application with spcd in the future we're going to have to look at those issues again because they really are trial specific so we'd advise sponsors um to use consistent stage lengths and to reach agreement with us in advance on the primary endpoint and other CL critical trial features and then even if we reach agreement on all of those things we're still not going to be able to agree a priori that the study will be acceptable because of some of the things that we're concerned about will remain open questions until we have that data in hand I already mentioned that here there weren't many dropouts in stage one you don't know that until stage one is done so even if we do accept the design and the study is positive and all of these issues are resolved labeling is still going to be super complicated if you have an sdcd stud because we didn't end up writing a label for this one all right so moving from complicated to something much more straightforward this is a table taken from the clinical study section of the valbenazine label this is the data that supported the approval of alazine for the treatment of discinesia um the studies that supported this application really provide a good example of one of the strategies to mitigate Placebo response that has been you know successful and that's the use of blinded Central Raiders um in this study the Raiders were blinded to treatment assignment and also to visit number and using the blinded Central Raiders was feasible here because the symptoms of discinesia are directly observable and can even be captured on video so they can be rided by their remote Central ra Raiders fairly easily and then you'll note here that the change from Baseline on the As and the placebo arms was basically negligible all right so I think it's also important to bear in mind that this phenomenon of placebo response in clinical trials is not something that's unique to Psychiatry we see it in multiple other areas of medicine it's ultimately the reason that we have Placebo controled studies in the first place we do expect to see some response in a proo group folks get something that they think could be an active drug and lo and behold they have some response it's important though if you want to understand that the observed response is in fact related to the active treatment that you do show that folks on the investigational drug are doing better than folks on the placebo so for the next couple of slides I'm going to show some examples um of what we see in other disease areas and speculate a bit on why the placebo response rate in those trials is higher or lower than what we're used to seeing and I'll caveat this by noting that I pulled my examples from the most recent office of new drugs annual report and I haven't done a deep dive to see if other drugs behave similarly or if my speculation here Bears out consistently but with those caveats in mind um I'm also going to try to draw some parallels to circumstances in Psychiatry trials all right so the first example I have here is from the clinical study section of labeling for Zant which is an internasal calcitonin Gene related peptide antagonist that's approved for the acute treatment of migraine with or without Aura in adults um the point I want to make with this example is that the end point here pain is very subjective so similar to a lot of what we do in Psychiatry the endpoint is relying on patient report of their subjective experience now in this case it probably helps somewhat to have a dichotomous Endo of painfree versus not rather than asking participants to rate their pain on a Liker scale that would introduce more variability and honestly as somebody who gets migraines I can tell you that painfree is what matters like a little bit of migraine pain is still migraine pain like I don't want to deal with it anyhow with that kind of subjectivity um it's not too surprising that about 15% of the folks in the placebo group were responders now if you think back to that slide I showed earlier about contributors to the placebo response some of this could be placebo effect some of it could just be that their migraines will resolving spontaneously within two hours anyways um regardless we have a pretty high pobo response rate here but we also have a responder rate of almost 24% in the
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active treatment group and a statistically significant difference on the primary end point of painfree at two hours on the secondary of relief from the most bothersome symptoms so things like photophobia phonophobia nausea both the placebo and the active groups had even higher response rates but again a significantly higher response in the active treatment group than in placeo so this is from the clinical pharmacology section of that same label and I want to point out that this is very similar to what a lot of our drugs look like in Psychiatry we describe what the drug does at the receptor level then we say that the relationship between the action and that action and the clinical effect on depression or schizophrenia or whatever is unknown and until we have a better understanding of pathophysiology that's going to continue to be our approach in labeling all right the next example I have comes from the clinical study section of labeling for uh linaclotide oral capsules and you know I have to say when I'm talking outside of my own disease area hopefully I'm getting these pronunciations right but anyways it's a um guate cyclace C an sorry Agonist um the data here supported the irritable bowel syndrome with constipation indication um and I think this is a really interesting example because we have two different end points here like our last example one is a pain Endo that's likely to be highly responsive to place again it's subjective um but unlike the last example it's not dichotomist so it requires a bit more interpretation um the other Endo is something that's a bit closer to objective csbm is the complete spontaneous is complete spontaneous bowel movement so clearly the number of bow movements is something that can be counted um but the endpoint itself is a little bit of a hybrid because it also involves a subjective report of the sense of completeness of evacuation so interestingly you see a much higher percentage of placebo subjects meeting the criteria for responder on the fully subjective pain endpoint than you do on the csbm endpoint and I got to tell you section 12 of this label is something that I dream about being able to do for Psychiatry we can only aspire to this frankly at this point the language here very clearly lays out the pathway between the action of the drug and the downstream physiologic effects on constipation and it even presents an animal model to support the Drug's effect on pain so this suggest that the drug acts on some aspect of the underlying pathophysiology of ibsc all right so far I started with an example of a trial with a subjective endpoint then went to something that's a little bit more objectively measurable here I'm going to show data from the bism uh label and the studies that supported its indication for the treatment of moderate to severe plaxer IIs in adults so bism AB is a humanized interlan 17A and F antagonist um the end points in the study were investigator Global assessment which is an overall assessment of psoriasis severity and the psoriasis area and severity index now you might think that these things are somewhat subjective because they are investigator assessments and of course require some interpretation to get to the score on these scales but these are assessments of the size and extent of the is plaques things that are directly observable and both scales have anchors that describe what type of appearance the plaques of a given severity would have um so you know it kind of like gives you a framework for how to you know rate these different lesions so even though these are Global assessments and you might think of clear and almost clear as being analogous to something like improved or much improved on a CGI we're really talking about very different things here both what the patient is experiencing and what the clinician is observing are things that you can see and measure you're not asking the patient if the patient feels like their skin is redder you can see athema and here you can see a much lower rate of placebo response in the studies when you're directly observing the pathophysiology in question and it's something that is objective or relatively objectively measurable you get less Placebo response all right in section 12 of this label isn't quite as definitive as the linaclotide label in terms of directly linking the drug effect to path of physiology but it's pretty close um and again it's probably a combination of the relatively objective outcome measures and the tight link between drug action and pathophysiology is contributing to the low Placebo response in these trials finally I want to put up an example that of course has been in the news a lot lately um this is from section 14 of the tepati label and this is one of the glp1 inhibitor drugs that's indicated for chronic weight management as an adjunct to reduceed calorie diet and increased physical activity now there are all sorts of things that can contribute to cber
Segment 20 (95:00 - 100:00)
response in weight management studies so for example the folks who are in these studies are likely to be motivated to lose weight in the first place um they're required to engage in diet and exercise as part of the study and even though it's difficult sometimes folks just lose weight um so even though weight is something that is objectively measurable there's multiple physiologic and behavioral factors that may contribute to changes weight so there's a lot of variability and it's been traditionally pretty difficult to show Improvement in weight loss trials or at least to show enough Improvement that it overcomes the Adverse Events that are iner of the trials anyway the primary outcome in these studies was the percent of patients losing at least five now you'd think that would be pretty difficult to surpass but these studies still manage to show a treatment difference because the active treatment work for works like Gang Busters so another way to overcome concerns about placeo response is to find something that really has an impressive treatment effect then even if you have a massive Placebo response rate you'll still be able to show a difference and so far we don't have much of anything with this kind of an effect in Psychiatry unfortunately and then again once again in section 12 we have a mechanism of action description that links the drug action directly to the clinical effects the drug binds to a physiologic regulator of appetite the person taking the drug eats less it's pretty um straightforward all right so what lessons can we take away from all of this ultimately the point I want that I want folks to take home from the examples I've shown in Psychiatry and in other disease areas is that there are things that we can do to help mitigate the placebo response in our clinical trials for things like spcd or other non-traditional study Design Elements I would advise sponsors to talk to us early and often um there are still some methodological issues that you know that need to be overcome but we're willing to consider sbcd studies as long as we're able to agree on specific aspects of the design and Analysis um folks can also do things like trying to improve Raider training and to mitigate some of the variability that's just inherent in asking human beings to assign a rating to something that is subjective um still related to measurement but maybe more of a medium-term than a short-term solution um it could be worthwhile to Dev velop better clinical outcome assessments the scales that we use in clinical trials now have been around a long time you know they were mostly expert consensus and um you know just they're face valid for sure and obviously we have precent for them but they've been around longer than modern psychometric principles quite frankly um I'm so developing new ones would potentially be welcome anyways in terms of other sources of VAR I'd refer back to Dr dei's presentation and his comments on the number of sites enrollment criteria and so on essentially quality controls on study design and implementation But ultimately what's really going to be the real GameChanger here is when we can develop drugs that actually Target pathophysiology that's when we'll finally be able to take some of this variability and subjectivity out of our clinical trials and really get much more objective measures in the best of all possible worlds we would have a much better understanding of pathophysiology of psychiatric disorders we'd be able to develop drugs that Target the pathophysiological underpinnings of our diseases and we would even be able to Define study entry criteria more appropriately because we wouldn't be relying on subjective assessments for diagnosis or inclusion we'd be able to get that blood test or get that scan that could tell us that yes this is in fact what's going on here and this is a patient who is appropriate for this clinical trial and I understand that we're you know a long way from that today but I hope that folks will think of this as an aspirational goal um that our current state of understanding is less of a roadblock and more of a call to action um and so with that and recognizing that I am the one thing standing between you and our break I will just say thank you very much for your attention okay wonderful thank you to all of our speakers and panelists in this first um session um let's take a short break we have some questions in the chat more questions are coming in but we have a break now until um 150 and so I suggest that it's a short break but we can uh get back on track and start then in about seven minutes okay thank you
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e
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e okay hi everybody it's uh it's a short break but thanks for um hanging with us here and um coming back after this short break uh our next session is going to be led off by Dr Holly lisenby and Z de Deng um on the current state of placebo effects in device trials and then we'll go for a series of uh Placebo effects and psychosocial trials and then after that a panel discussion Dr lizenby thank you TOR uh and so um these are my disclosures and uh as Tor said I'm going to be talking about Placebo and device trials and so although up until now in the worksh we've been talking about Placebo in drug trials which are typically given either by mouth or intervenous or internasal we're now turning your attention to how you would you do a placebo in a device trial and that's where we use the term sham so we blind device trials typically by doing a sham procedure and the idea of sham is that the mode of application of the device and the ancillary effects that the device elicited elicits are meant to be as closely matched as possible but without having active stimulation of the body or the uh brain specifically now one of the challenges in blinding device trials using sham procedures is that one sham does not fit all or even most and let me explain what I mean by that there are growing range of different devices uh here you see the landscape of neurom modulation devices on the x- axis is how invasive they are and on the y- axis is how focal they are and uh they all use different forms of stimulation applied to the head or the body uh some are surgically implanted others are not um and those are just the devices that directly apply energy uh to the head or cranial nerves but there's another space of devices that deliver audio or visual stimuli to affect brain activity indirectly and these include prescription digital Therapeutics and neur feedback devices now even within one modality of device uh here I'm going to use transcranial magnetic stimulation or te as an example we have a broad range of different TMS devices here I'm showing you uh just a few of them and while they all uh use rapidly alternating magnetic fields they differ in how they apply that to the head so this device for example uses an iron core figure8 coil this device uses an air core figure8 coil now those are pretty similar in terms of the electric field induced in the brain but this device uses uh three different types of coil that are U called H coils with different Coral windings that stimulate very different parts of the brain and have different ancillary effects the device on the left uses an air core figure8 coil but it has
Segment 23 (110:00 - 115:00)
some additional bells and whistles to it uses neuron navigation so there's a camera in the room and a Tracker to be able to navigate the TMS coil to a specific spot in the brain that was identified before treatment on the basis of fmri and so there's an additional aspect of this procedure and also it's given with an accelerated schedule where 10 treatment are given a day each day for five days now that brings us to some of these ancillary effects of TMS one is the Intensive provider contact in a high-tech environment and I'm showing you here just a few pictures from our lab and this is intensive contact it can range from either one session a day for six weeks to 10 sessions a day over five days and um this really highlights the importance of blinding not just for the patient but also the coil op operator and the Raiders now there are also sensory components to TMS it makes a clicking noise which is induced by the vibration of the coil within the casing and this is quite loud even with earplugs uh you can't mask the bone conduction of this sound uh and so that in addition to the sound uh which can um it also can induce scalp uh Sensations and these Sensations can range from just feeling a tapping on your head to feeling uh something that's a scalp discomfort even to scalp pain and the TMS can also evoke movements so if you're even if you're not over the motor cortex if you're over the frontal cortex which is the for depression treatment this can cause movement in the face or the jaw which can be from directly stimulating scalp muscles facial nerves or cranial nerves you can also depending on the shape of the coil get some evoked movement from the motor cortex and this is more common with the more um diffus coils such as the H coil configurations now not only are these ancillary effects important for blinding of clinical trials they also represent important confounds for physiological studies that we do with TMS where we want to understand use TMs to probe brain function such as coupling TMS with EEG to study of O potentials or coupling TMS with fmri now shamam TMS has evolved over the years I'm showing you in the center of this Photograph active uh TMS and in the corners are four different types of early forms of sham TMS which were called coil tilt uh TMS configurations where you tilt the coil off the head so that the magnetic field is sort of grazing the scalp you get some sensation you get the noise uh but you're trying to not stimulate the brain now while this coil tilt sham does induce some scalp stimulation and clicking it lacks operator blinding but even worse than that what we showed from intro cerebral recordings of the electric field induced in the brain by these different forms of coil tilt Sham in non-human primates is that compared to active TMS which is the top line the one of these four sham coil tilt configurations was almost 75% uh strength of active TMS and that's the second line from the top with the black circles and so some forms of these Coral tilt Shams were actually biologically active and that represents a compound when you're trying to study the older literature uh trying to look at do met analyses of TMS clinical effects the next evolution in the step of sham TMS was shielding uh and for example figure8 coils could have a metal shield between the coil and the head that blocked the flow of the magnetic field uh and here this uh e Shield has both the magnetic Shield as well as a printed circuit board on top of the coil that was meant to be fired antiphase with the TMs in order to try to cancel out the magnetic field at the surface of the head these types of approaches look and sound like active TMS and they provide operator masking however uh and they're biologically inactive however they don't feel like active TMS here you're looking at subjective ratings of scalp pain muscle twitch and facial pain with active TMs in the red and Sham in the black so there's um not appropriate masking or matching of these ancillary effects but that sham the e-shield Sham was used in the pivotal trial for depression in adults and that pivotal trial missed its primary endpoint which is shown here in the yellow box uh where active TMS is in the blue line and Sham is in the gry line ultimately TMS became FDA cleared uh in 2018 for a limited indication based on this post Hawk analysis which I'm showing you here where about half of the patients of the pivotal trial who had failed only one anti-depressant medication uh in the current episode showed a significant separation between active in the black line and Sham in the Gray Line however those who had more failed trials in the current episode from 2 to 4 did not
Segment 24 (115:00 - 120:00)
separate between active and Sham subsequently the label was expanded and CMS coverage um determinations uh have been provided but that was on the basis of additional evidence which came from additional randomized control trials as well as open label experience and literature reviews now uh that same sham has been used in a pivotal trial for TMS for adolescent depression which also failed its primary endpoint and failed to separate active from sham here you see the anti-depressant RIS um scores on the y axis with active TMs in the blue and Sham in the red and they uh were indistinguishable and this the Sham is described in the paper as I'm showing here in the quote uh and this is another one of these metal shield uh or e-shield Shams uh that did not provide scalp stimulation now ultimately FDA did clear TMS down to the age of 15 on the basis of retrospective analysis of real world data that were derived from a registry of over a thousand adolescents over a span of 15 years all of whom were obviously receiving off-label treatment as well as a literature review and the status of insurance coverage is to be determined the next step in the evolution of sham TMS was scalp stimulation and that's what we used in the opt TMS trial of almost 200 patients and this was the first study to use scalp stimulation and you see those little patches on her forehead those are um electrodes through which we administered weak electrical stimulation to the scalp along with auditory masking in order to better mimic the ancillary effects of TMS and here you can see the ratings of scalp discomfort and headache were similar between active TMs in the red and this scalp stimulation Sham in the black this uh we did assess the Integrity of the blind in the Optus trial and we found that the blind was preserved um very low percentage of extremely confident correct responses and we found a separation between active and Sham in this study with a 14% remission with active and 5% remission with Sham that was St statistically significant Shams in the modern era have kept this idea of scalp stimulation and oratory masking uh but they come in different um versions that are now available um as TurnKey systems for example ex Le this sham which has an active magnetic stimulation on one side of the coil and no stimulation on the other side but the sides are identical in appearance uh and this comes along with an adjustable output for electrical stimulation of the scalp which is synchronous with the TMS pulses that's built into the system now I'm going to shift from TMS to a different form of stimulation transcranial direct current stimulation or tdcs this is from one of the randomized control trials that we conducted of active versus sham tdcs for depression in 130 patients which failed its primary endpoint now I'm showing you the uh depression response on the Y AIS for unipolar patients on the left and bipolar patients on the right and although we did not find active tdcs to be better than sham we found something curious which was that sham was better than active particularly in the unipolar patients and that caused us to ask well what is going on in our sham tdcs intervention here's what our active intervention looked like we stimulated at 2. 5 milliamps continuously over 30 minutes the Sham which we thought was biologically innocuous actually had these U brief ramp ups and then ramp Downs intermittently during the 30 minutes but in addition to that it had a weak current of 032 milliamps that was continuous throughout the stimulation uh we had we weren't aware of this uh continuous stimulation uh and it begs the question whether this uh waveform might have had some biological activity and certainly when you find sh better than active one has to ask that question uh now this question of how to Sham tdcs trials has been addressed in the literature in this study um uh in 2019 they reported that there were uh a great U multiplicity of sham approaches that were being used in the field uh and some of these might have biological action now in 2018 we had conducted an NIMH sponsored workshop and published a report from that Workshop in which we urged the field to um present the rationale and the effectiveness of sham stimulation uh when you do studies and we observe that this is rarely documented we also encourage the field to do blinding checklists uh during the study design reporting and assessment uh of study validity and we still encourage this it's still timely now I'm going to move from tdcs to another form of implanted stimulation so TMS and tdcs are nonsurgical now we're dealing with a surgical implanted device Vagas neres stimulation so it's surgically implanted pulse generator and Sham is done by implanting the device but not turning it on the pivotal trial
Segment 25 (120:00 - 125:00)
of VNS for depression failed its primary endpoint which is shown in the yellow box here but it was subsequently FDA cleared on based on a non-randomized open label comparison with treatment as usual uh as you see here insurance coverage was frequently denied which limited utilization more recently uh there was a um study called the recovery trial which for randomized control blinded trial to demonstrate the safety and effectiveness of VNS as an adjunctive therapy versus no stimulation control this recover study was designed in accordance with the CMS coverage with evidence determination decision memo the study is not yet published to my knowledge but according to a press release from the company that sponsored it after one year of active VNS versus sham which was implantation but not being turned on this study failed as primary endpoint and I'm quoting here from the press release that it failed due to a strong response in the Sham Group which they said was unforeseen in the steady design and I would say that we might have foreseen this based on the original pivotal trial which also failed to Chef differentiate active versus sham now I'm going to move to deep brain stimulation uh and this is the randomized control trial that we conducted on bilateral uh subal singulative DBS for depression sham was done by implanting but not turning it on and this study uh in a futility analysis failed to differentiate between active and Sham uh so you can see this has been a recurring theme in the studies that I've shown you uh now there's some specific challenges to blinding DBS trials uh by the time you get to DBS you're dealing with a very severely ill uh depressed population and clinical severity uh may represent some dangers when you try to think about um the relapse that occur may occur from crossover designs like crossing over from active to Sham uh there are unique things that may unblind the study such as battery recharging or batteries that don't need to be recharged that could cue a patient uh and also there's a need for rigorous safety protocols to protect patients who are so severely ill during their sham phases due the due to the risk of clinical worsening so to conclude uh sham methodology poses a lot of complex challenges for device trials one size does not fit all the interpretation of the literature is Complicated by this variability in sham methodology across studies and across time as the Sham approaches have evolved measuring the biological activity of the Sham intervention before using it in a clinical trial is important and it is seldom done and assessing the Integrity of the blind is important for patients operators and Raiders and that's why with Sham procedures we need to think about triple blinding not just double blinding and the shortest Pathway to regulatory approval which I gave you in an example of BNS does not guarantee insurance coverage nor clinical adoption some thoughts about future directions uh we could focus on developing Next Generation active devices that lack these ancillary effects that need to be M mimicked by sham some examples that you hear about from Z Deng who's coming up next include quiet TMS and controllable PST TMS we could conduct studies to validate and characterize the biological actions and expectancy effects of sham interventions and there's a role for active stimulation of a control brain area uh as a comparison condition these are the members of the non-invasive neur modulation unit in our lab at NIMH and I'll just show you the slide that we're recruiting uh for jobs as well as for patient center trial and uh thank you very much and let me hand it back to you tour wonderful thank you Holly all right um I think we have Z up next so please uh take it away Z I will share screen and maximize it good day everyone uh thanks for having me here today and for the next few minutes I will discuss the challenges and strategies in implementing effective sham stimulation for non-invasive brain stimulation trials uh Dr lisenby has already gave a very nice overview as to why this topic is crucial as we strive to improve the validity and reliability of our neuros stimulation device trials I'll be discussing in more in depth the physical Char character characterizations computational modeling as well as some measurements that we took of various sham strategies and discussed their tradeoffs uh in case you are interested in uh picking or implementing a sham technique or improving one and I'll be focusing primarily on TMS and tdcs before we proceed I need to disclose that I am inventor on patents and patent applications uh owned by various institutions some of them are on brain stimulation technology additionally this work is supported in part by the NIMH intramural research
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program so when we talk about is this panel in the way let me Mo that aside it looks good I don't think we can see it okay good uh so when we talk about uh creating a valid sham TMS uh Dr lisenby has already mentioned that there are several critical elements that we need to consider firstly the Sham should look and sound like the active TMS to ensure blinding this means that the visual and auditory cues must be indistinguishable between sham and active conditions secondly the Sham should reproduce the same somatic Sensations such as coil vibrations and scalp nerve and muscle activation this sensory mimicry is essential to maintain the perception of receiving active stimulation and finally perhaps the more important one uh that there should be no active brain stimulation which means that the electric field induced in the brain should be minimized to avoid any uh therapeutic effects for TMS there are several categories of ways to implement sham which are Loosely categorized into the coil til techniques uh two coil configurations and uh dedicated sham systems uh and going to describe each of them in some detail next uh so Dr lisenby has already covered the coil till technique and this is one was pretty popular in the early days of TMS uh by angling the coil 45° or 90 Dees relative to the tangential plane of the head U one can minimize the stimulation uh to the brain at least they thought so uh it turns out through modeling and also int cranial recordings of induced voltages that some of these coil til techniques remain biologically active here you see simulations on a spherical head model of various coil manipulations in coil tilt uh up here we have the active uh figure of eight stimulation producing a single F focus of electric field directly underneath the center of the figure of eight coil um when you tilt the coil 45 degrees or 90 degrees and when you look into the brain there is considerable residual electric field that is still induced with these coil tilt techniques a better way uh a very clever way and this is popularized by some folks in Europe who's doing motor uh excitability studies uh involve two coil configurations you use two TMS coils that are attached to two different TMS stimulators and you would position these coils perpendicular to each other one in the active tangential configuration and one that is 90 degrees on top of the active coil and with this technique the advantage is that you can interleave active and Sham TMS pulses in the same protocol because you are dealing with two different TMS stimulators so in active mode you will simply fire the coil that is closer to the head which is tangential in the active configuration in sham mode you will simply uh fire the coil that is on top of the active coil however this technique like the coil tilt um it there is a spacer involved in this perpendicular coil setup uh so the feel that is induced in the brain is less compared to the 90° coil tilt um but it does also not induce any scalps stimulation uh that means that the sensation at the scalp level is uh decreased and not uh felt by the participants uh another implementation involves uh a sandwich design also involving two coil setups that are sandwiching a metal shielding plate in active stimulation mode one would fire the coil that is closer to the head and in sham mode one would fire the coil that's further away and this shield and assures that you have uh the limits the penetration of the magnetic field resulting in no scalp stimulation as well as no brain stimulation the final category of sham systems are these dedicated sham systems manufactur by different companies uh the first of which is a reverse current sham um Maxim has an implementation of this concept uh in active stimulation the coil current in the coil is such that uh you there is a same coil current direction underneath the center of the coil summating the field underneath the center in the Sham stimulation setup the
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coil current in one of the loops is reversed such that at the center of the coil the field is cancelled this effectively creates a larger uh circular or oval type coil um which is a larger coil that has a lesser Feld decay and so when you actually look into the brain uh there remains substantial electric field stimulation there uh another technique that was mentioned earlier is shielding uh by again putting a metal shield or mu metal shield underneath the coil you can effectively block out all of the field penetration but one would also completely eliminate any scalp stimulation uh making the sensation uh feel different uh another implementation strategy uh involves using a spacer and a passive shielding uh this is an implementation of the MC Venture coil for example using a large block coil and the coil winding inside that large block is only built into one side of the coil and so during active stimulation one would flip the coil such that the active winding is closer to the Head in for sham stimulation one would flip this coil over such that the passive shielding is closer to the head and the active winding elements are further away from the head uh this Shield technique plus the spacer would completely eliminate any brain stimulation but it also would eliminate any scalp stimulation a final uh coil setup uh was uh invented by our lab several years ago uh which we called the quadripole coil uh this implementation splits the figure of eight coil into four loops and by reversing the coil current direction on the outside Loops during sham stimulation effectively you make it into a smaller figure of eight coil and as we know with smaller coils it has a lower field penetration and therefore the scalp stimulation is reduced as well as the brain stimulation is reduced how do all of these different sham stimulation strategies Stack Up on each other um the criteria we want to achieve is uh basically 100% scalp stimulation compared to the active electric field so when we quantify this sham electric field at the scalp one would like to achieve 100% uh compared to the active e field in the active configuration when it comes to brain stimulation in sham e field should be zero you don't want any uh electric field induced in the Sham condition and so one would like to maximize this contrast between scalp stimulation and brain stimulation but looking across the coil till techniques the two coil configurations and dedicated sham systems none of these techniques perfectly achieve what we want either you have uh no scalp stimulation uh but it also has no brain stimulation or you have residual scalp stimulation and brain stimulation at the same time uh confounding uh clinical trial results so these are the primary challenges in implementing sham systems there is a incomplete mimicry of sensory experience that is the scalp stimulation or uh that you have too much of this residual possibly biologically active brain electric field that is induced uh so why don't we take a coil that does not produce any brain stimulation uh and produce no scalp stimulation and add to it some scalp stimulation back uh and this is a proposed technique using concurrent cutaneous electrical stimulation uh which was used in some of the early clinical trials of TMS uh utilizing two electrodes that are placed relatively close together approximately 1 cm EDG toed distance underneath the center of the coil and the placement of the electrodes is such that you maintain the current direction induced in the head uh compared to active TMS and the current is mostly shunted in the scalp but a little of it enters the brain the early implementations of this technique would use a customized uh ECT T device and the device would deliver low amplitude Square pulses that are synchronized to TMS pulses uh in more modern
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configurations this electrical stimulation module is incorporated into uh a dedicated sham coil for example such as the M Venture setup there are several ways to use this electrical stimulation uh one way is to carefully titrate the stimulus intensity for this electrical stimulation to match the active TMS sensation or some laps maximize the intensity of the electrical stimulation in and the electrical stimulation would be delivered in both active and Sham TMS conditions to entirely mask scalp sensation in both conditions now there are some problems with uh this cutaneous electrical stimulation uh the first of which is waveform considerations what is the waveform of these electrical pulses uh that are accompanying this sham TMS pulses first of all the manufacturer specified triangular waveforms with a uh two Mill with a 200 uh microsc rise time and a 2 millisecond fall time when we actually make measurements of these current pulses though the waveform deviates substantially from this triang angular waveform that manufacturers specified in their manual what we actually measured are these exponential decaying waveforms that has a much longer tail compared to the 2 millisecond fall time of the Triangular waveform what's more um is that uh if one were to characterize the Decay constant of this exponential decay and plot it as a function of the intensity um of these pulses one would find that for pulses that are more intense you have a shorter decaying constant and therefore it's more pulsatile if you reduce the uh electrical intensity uh you would end up with a pulse waveform that is longer and I'll tell you why that's important a little bit later a second feature that is uh peculiar of this system is that uh the current amplitude is not linear with the dial setting that is if you were to increase the intensity from rotating the dial on the machine um a increase from setting of one to two is not the same as uh a setting jump from 8 to a nine for example and the maximum current at a maximum stimulator setting is upwards of 6. 7 7 milliamps which is uh considerably higher compared to other electrical stimulation uh such as tdcs which typically uses 2 milliamps there's another uh issue with this electrical stimulation intensity which is that this Electrical uh eem intensity was advertised to scale with TMS intensities that is as you dial up the intensity of the TMS pulses the intensity of the electrical stimulation should also increase and this is not the case uh from our measurement as you can see here at two different electrical stimulation intensity settings as we dial the TMS pulse intensity up from 50% to 90% the amplitude of these electrical stimulation wave forms uh they don't really change um why is pulse shape matter why do pulse shape matter this has to do with the strength duration property of the sensory fibers underneath the TMS coil uh sensor F fibers are classified uh you know in this uh rudimentary drawing that of sensory nerves that I put up here uh there are a Beta nerves which are these larger diameter uh melinated nerves uh and usually typically they have faster conduction time and so they carry information uh about uh vibrations uh pressures and touch uh ad Delta nerves are slightly smaller about 1 to five microns in diameter and they typically carry information about Shopper pain uh and then we have these sea fibers that are unmyelinated uh and there are smaller in diameter and because of the lower conduction time uh they would carry information about Burning Sensations and thermal pain um I know this is not a very professional drawing of these nerves and
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of course when it comes to drawing I am no rembrand but uh neither was Picasso this is actually a more professional drawing but if the important thing about uh you know the different pulse shape is that they act they preferentially activate different kinds of fibers with different time constants uh so one can actually model that using a nerve model which I have done here and we can show that the proportional nerve activation is different across different waveforms uh on the left cluster of bars we see what the profile of the proportional nerve activation is like for various types of TMS waveforms including basic sinusoids monophasic sinusoids and controllable pulse width which are near rectangular pulses uh these TMS waveforms preferentially activate a beta and a Delta fibers and contributing to this tapping Sensation that you feel with TMS but when it comes to electrical stimulation uh using these exponential decaying waveforms you see that these waveforms preferentially activate CA fibers not only that as you change the intensity of the stimulation uh from Maximum to minimum you preferentially stimulate more and more of SE of the sea fibers um that is if you decrease the amplitude the tail here gets longer and you stimulate more and more of these sea fibers and you create more and more uh burning sensation and this tingling sensation that sometimes people report uh with tdcs for example which is uncomfortable to some people uh but as you increase the electrical stimulation intensity yes the pulses become shorter and it feels more pulsatile but then the intensity is increased so now it feels more painful and so that does not seem to be a way to achieve a very comfortable uh setup with this electrical stimulation and uh what's more important is it does not feel like TMS that the profile of these nerve activation is very different from a TMS waveform so um we did not find any perfect sham uh the next order of business is that we look into the clinical literature um might there be any other stimulation parameters such as intensity or stimulation site or stimulation protocol that are predictive of sham response something that we can U modu modulate and modify um so we looked into the literature um and we replicated and extended a previous meta analysis uh looking at depression trials that are randomized control Trials of TMS um the average sample size across these trials are 35 subjects um in terms of stimulation protocol a predominantly high frequency stimulation uh and the second largest group would be low frequency stimulation in terms of intensity um we have a mixture of intensity uh with most uh protocols administering either um 100% 110% or 11 120% of motor thresholds uh in terms of stimulation site most of these clinical trials use left dorsal lateral prefrontal cortex as the treatment Target uh that as a single size stimul ulation combined with bilateral dlpfc account for close to 80% of the clinical trials in terms of targeting approach uh I was surprised to find that we were still using the scalp based targeting strategy of the 5 cm rule uh which U uses uh just measurements on the scalp uh 5 cm on the scalp anterior to the motor hotspot and that's where they determine the location for the left doors so lateral prefrontal cortex in terms of sham type uh a lot of the earlier studies as Dr lenb mentioned uses the coil tilt configuration either 45 degrees or 90 degrees and so uh in this analysis they still account for majority of the studies and only about a third of the studies included uh uses a dedicated Shams coil setup um manufacturers um you know it's um in terms of coil types they're predominantly a figure of eight coils and in terms of the number of sessions uh that are in these studies uh the
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median is 12 sessions of treatment so what did we find what are the correlates of uh sham response in these clinical trials the first thing we found was that the number of sessions uh is correlated with Sham response so here on the Y AIS we're plotting the percent change uh from Baseline for the pre for the primary outcome of the study typically a depression severity rating uh so down is actually uh good anti-depressant um and here we s see a weak correlation between the number of sessions in a typical clinical trial with improved sham stimulation um and uh this uh you know over a longer treatment course participants May develop stronger expectation of improvement and this continued engagement with the treatment process plus regular clinic visits and interaction with the health care team uh can reinforce these expectations uh contri contributing to this sustained and enhanced Placebo response um which can also accumulate over time the second uh correlate that we found to be uh significantly correlated with Sham response is active response so any given clinical trial the higher the active response the higher the Sham response and the correlation between sham and active responses may indicate that the mechanisms driving the placebo effect are also at play in the active treatment response uh and this correlation might also reflect underlying trades or states in participants that enhance their responsiveness to any form of inter prevention uh and this finding underscores the importance of effective blinding and management of participants expectations and account for Placebo effects in clinical trial design and interpretation and the final correlate uh is effect of time something that was also mentioned uh in relation to pain medication a little bit earlier so Dr wager has mentioned this um earlier that sham response appears to be in increasing over time and over the Decades of TMS clinical trials we also observe this effect now this increase in Placebo response with drugs uh you know is sometimes hypothesized to be associated with societal changes in the attitude towards certain types of treatments and perhaps greater awareness in medical research and increased exposure to healthcare information and also more advertising in general particularly post approval of a drug or a device and all together can enhance participants expectations and uh believe in the efficacy of certain types of treatments contributing to Stronger Placebo response um here we see the same thing with Device devices uh there are Al also other um interpretations of this increased Placebo response uh perhaps the demographics and the characteristics of the participants in clinical trial Tri might have changed over time um perhaps participants today are more healthc conscious they're more proactive in engaging Health Care uh leading to Stronger expectations of uh treatment options it could also be that uh sham respon sham devices and procedures are becoming more realistic uh changing from the earlier coil till techniques and to now more dedicated sham systems that can enhance the belief that one is receiving an active treatment the good news though is that active response is also increasing although not quite at the same rate uh active response may be increasing over the years as well likely attributed to improvements and uh dosing and targeting techniques speaking of similarities between drugs and devices and their reable response there are also some key differences uh a study was published last year in neurom modulation pointing out the differential Placebo responses between neuros stimulation techniques and pharmacal therapy in late life depression uh the time course of this uh sham Placebo response is different between sham rtms and Placebo pills specifically at the four-week time Point participants receiving sham rtms showed a significantly greater reduction in their Hamilton depression rating scale compared to those receiving Placebo pills and this suggests a stronger early Placebo response to neuros stimulation compared to pharmacotherapy but when we
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look at 12 weeks um the placebo response for drugs start to catch up and by the end of the 12 at trial at 12 weeks uh there are no significant statistical difference between the placebo pill response and the Sham TMS response uh this is important to consider if we're designing clinical trials to compare drugs versus devices for example um so we must take care of uh think about when to assess primary uh outcome and also employ statistical techniques to account for this time dependent placeable effect uh touching on tdcs for a second uh we don't really have a lot of work on tdcs uh iCal sham protocols in tdcs is implemented by uh changing the time the temporal waveform of the stimulation uh by ramping up during the beginning phase of the stimulation and sometimes a ramp up ramp down uh at the towards the end of the stimulation to uh to give a transient uh sense of the brain is being stimulated uh there are some protocols that maintained a constant low intens as shown in Dr L's slides there are these micro amp stimulation which may or may not be biologic biologically uh active and that may confound results of clinical Dr D sorry but we're gonna need to wrap up okay not for to give enough time for our following speakers sure sure final slide and we're just going to be talking about the some of the det determinant of sham response in tdcs Trials there seems to be a large sham effect uh and there are some protocols that has better uh blinding compared to the others and there are certain Electro placement that has lower sham response uh and that uh again similar to TMS the Sham response and tdcs uh is correlated with the active tdcs response uh with that I think I will uh skip the rest of this talk and you know allow questions uh if you have any okay thank you um great we'll keep putting the questions in the chat and uh for our panelists please keep answering them as you can um we'll move on to the next session right now which is going to cover uh Placebo effects in psychosocial trials and interpersonal interactions so our two speakers are Winford reath and Lauren Atlas and I believe Winfred you're going to go first so please take it away thank you first I want to send you some greetings from Germany uh and uh I'm pleased to be invited to this exciting conference I was uh asked to talk about Placebo effects in Psych social trials and this is uh certainly a quite critical question whether we can really apply the blo construct to uh treatments on psychological uh therapies uh and trials and psychological therapies so I want to just try to highlight why this is complicated to transfer this concept to psychological treatments and uh but then I will dive into details how Placebo mechanisms might apply and how we might be able to control them in psychological treatments so what what's the problem is about the definition of psychological treatment these are interventions that utilize psychological mechanisms to treat clinical conditions but if we consider the definition of placebo effects in medicine this is pretty similar or highly overlapping with the definition of psychological treatments themselves so the impact of psychological and contact factors are typically considered the placebo mechanisms in medical interventions so we can switch to other attempts to ENT to Define placebo mechanism but then we need the concept of what are specific what are unspecific mechanisms uh and this is quite difficult to Define if we use psychological interventions because we don't have this very clear ingredient as we have in uh track trials and then old definition defined Placebo mechanisms as uh mechanisms of conditioning and expectation uh but this is already a definition of psychological interventions and as you know CBT started with the concept of using learning mechanisms to improve uh clinical conditions so there is an overlap in the definition what Placebo U mechanisms are and what
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psychological treatments are uh and therefore it's quite difficult to disentangle the effects I to provide more insight I reanalyzed a met analysis of Stephan Hoffman's group on depress anxiety trials and uh because they only included Placebo controlled uh trials on SE psychological interventions for some of these trials they were able to have some Placebo pill conditions uh if they all also integrated some uh psychoactive drug arms uh but most of the trials used arms that used some uh psycho education Parts information about the disorder or some supportive therapies which means just to reflect the emotional well-being and to support uh emotion emotional well-being but some other trials used interventions that are known to be effective such as interpersonal psycho therapy or cogn restructuring or reran therapy uh so they used therapies as control conditions that are known to be effective in other conditions and this shows how difficult this is it is to Define what a good Placebo condition is in psychological interventions and in this meta analysis in a first version of it six years ago the authors defined a good psychological PLO conditions as someone as a condition that use an intervention with the uh and excludes the specific Factor only including the non-specific factors and uh these mechanisms that are used in the non in the placebo armor should have shown uh to be non effective for uh the treatment uh under consideration for the clinical condition under consideration uh and then this is already a point that will be pretty hard to Define in detail uh if we uh develop and uh if we develop placeo conditions in psychological treatments another attempt was already mentioned by tor uh is to uh disentangle the variant parts of uh of treatment outcome and uh this attempt this approach is associated with names of like Bruce wampold or Michael Lambert and others uh and i' I show here the results of uh Mike Lambert's analysis and you see that he defines Placebo effects as the mere treatment expectation effect and declares that this is about 15% % and also allocates uh other parts of the effects to other factors we have to be aware that this kind of uh variance uh disentangling uh analysis this is just about statistical modeling this is not about causal investigation of factors and uh a second shortcoming of it is also that it does not consider interactions of these factors and therefore the Insight that we get from this kind of analysis is only limited but coming back to psychological treatments we can say that uh patients expectations are powerful predictors of outcome as we know from medical interventions already uh Here Comes data from a psychological treatment study on chronic pain conditions uh which shows that you find responder rates of 35 36% uh but only if patients have positive outcome expectations before they start treatment uh and uh those who have negative outcome expectations have much lower success rates like 15% and the relationship between uh positive and uh more negative expectations uh remain stable over month and years so what's the major challenge if we try to Define control conditions in psychological treatments uh the first point is are unable to un to do a real blinding of psychological treatments at least psychotherapist should know what he or she is doing uh and uh the placebo groups in clinical trials often are different from the active interventions in terms of credibility or as we call it of being a bona feeded treatment a treatment that is as credible as the active treatment is and for some uh control conditions it's even question whether they are uh kind of noo conditions that such as standard medical care or waiting list group if you are
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randomized to standard medical care or waiting list you might be disappointed you don't expect much improvement uh while being in a natural course group might be even better you try to do some self-help strategies for instance and another aspect is that uh the non-specific effects can sometimes switch to become specific effects depending on what your treatment is and what your treatment rational is I will show at least one example of one of our studies for this effect uh we investigated the treatment expectations in patients undergoing heart surgery and before they had the heart we did a few sessions to optimize treatment out outcome expectations that means outcome expectations were moved from being a noise signal of a placebo effect to being the target mechanism of our intervention like in this case the therapist is working with the patient to develop positive outcome expectations what happens after I manage to survive the heart surgery so we did that with a randomized clinical trial with that expectation optimization in the major group when compared it with two control groups and we were able to show that if we optimize treatment out expectations in card in heart surgery patients uh these patients really did better six months after surgery uh standard medical care has little Improvement it's mainly providing survival which is important enough no question about that but whether patients are really feeling better 6 month after surgery depends on whether they got some psychological pre-operative uh preparation and we also use this approach of optimizing expectation to develop complete psychological treatment programs also for patients with depression and with other uh mental disorders so let's come to the other part of the placebo mechanisms and noo effects and I would like to report about noo effects in psychological treatments but the major problem is uh side effects unwanted effects are only rarely assessed in psychological treatments and this is really a shortcoming here's just an overview on the top 10 side effects uh from psychological treatments many of them are just increasing conflicts and problems but some are also about uh new Sy symptoms that develop and in some of our other studies we even found that uh symptoms such as suicidal ideas are increasing sometimes for some patients in psychological treatments so negative effect side effects are an issue in psychological Tre treatments and uh we need to assess them and to better understand afterwards whether nobo effects occur how do they develop these treatment expectations be it either positive or negative one major effect is already uh show was already shown in many Placebo trials and that is about pre-treatment experience here are data of about 300 uh former Psychotherapy users who plan to attend another psychological treatment and you can see that how much improvement patients expect mainly it depends on how much improvement they experienced during the last treatment and the same with negative expectations side effect expectations uh of note positive treatment outcome expectations are not correlated with negative outcome correlations that means people can be optimistic and worry the same time so a critical role about patients treatment expectations has the clinician and uh we wanted to evaluate the effect of the clinician using an experimental design and here's our clinician I will call him Tom who is explaining to a critical patient whether psychological treatments can help or not and we wanted to modulate this situation and therefore we first brought all our participants in the situation of developing negative treatment outcome expectations we were quite successful in uh establishing negative treatment out outcome expectations or as you see here a reduction of positive outcome expectations after that Tom explained to the patient that psychological treatments are helpful for his or her condition uh but uh Tom changed his behavior he always used the same information psychological treatments are uh powerful to improve your clinical condition but he sometimes was more warmth and empathetic sometimes he showed more signs of competence sometimes both and you can see that it
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mainly depends on the these Behavior patterns of the therapist whether the information that he wants to transport uh really has some action if the therapist is low in competence and low in warmth the same information doesn't have any effect while the same information can has have a very powerful effect if the therapist shows Warth and competence so let me conclude these few insights into our Placebo research um the distinction between specific treatment mechanisms and uh unspecific uh mechanisms is less clear than in biomedical interventions but we can still say that expectations also predict outcome in psychological and psychosocial treatments and the main determinant of treatment expectations are pre-treatment experiences but also the clinician patient relationship and many other factors that contribute to the development of treatment expectations can be an unspecific factor to be control for but they can also be the focus of an intervention and can really uh booster treatment effects uh and uh therefore they are it's really valuable to focus on them and forly side effect assessments are typically overseen factors in clinical trials uh and I'll come to this back in a moment we want to recommend that uh Placebo control trials are needed in psychosocial uh intervention for psychosocial interventions uh but it's more difficult to decide what to include into them the major idea is to exclude the active mechanisms but uh this is not that easily to be defined and therefore we need some psychological attention conditions that are credible uh in our control conditions uh that psychological treatments are compared with um I would say that we need a variety of trial designs maybe if you start with the very new interventions it might be justifiable to start with a waiting L control group or with a standard Medical Care Group but if you want to learn more about the Tre M you need more control group uh designs and there's not one perfect control condition but you need variations of it and last not least uh we have a strong uh emphasis on side effects and Adverse Events and non unwanted events need to be assessed in psychological treatments as well finally let's make two comments I think Placebo uh controlled investigations are developed and have to be developed to better understand the treatment mechanisms from the patients you they are less important the patients want to know whether what the overall efficacy is of a treatment that means the combination of specific and unspecific effects the overall package uh and we shouldn't uh lose that out of mind and second all this mechanisms we are talking about they are not really to be separated one from the other but they are typically interacting expectation effects are interacting with the development of side experience of improvement that can go back to uh the drug or to the psychological treatment so far from my side and I'm happy to hand over to uh Lauren who will continue to talk about this issue wonderful thank you and Fred right now we have Lauren Alis thank you um so it's really an honor to be wrapping up this uh first exciting day of this workshop and to kind of I guess in a way bring it back to some of the um themes that Tor highlighted in his introduction um so I'll be talking about why um I think that we as a field would benefit from taking a social Neuroscience approach to preso analgesia and PBO effects more generally um so uh to us the same figure in his introduction to the day and I think one of the things that I really want to highlight in this is the distinction between intrapersonal factors so things like Expectations Learning history of associations with different treatments and different clinical contexts um and this really has kind of been the foundation of most studies of how stable effects Works work really because it's quite easy to manipulate things like expectations learning in the lab and understand how those affect clinical outcomes um but there's been far less work on the interpersonal processes that support CBO and in some ways I'd like to say this is
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really where we need to be going as a field because it could be a lot easier to teach clinicians how to enhance patient outcomes rather than sort of being beholden to what a patient brings into the table although of course these factors interact and um are both important in determining clinical outcomes um and so the way I like to think about this interplay is really from a social aspect of Neuroscience standpoint um so the term social aect Neuroscience really has come about um over the past couple of decades talking about how we can use Neuroscience techniques to understand emotional and interpersonal processes um across a variety of domains and where I think about this in the context of placebo is first of all through Neuroscience techniques we can understand how Placebo effects are mediated whe whether that be supporting specific um different types of outcomes or more General processes that shape Placebo effects AC cross domains from an asec of Neuroscience standpoint we can determine whether the mechanisms of different types of placebo are shared or unique so for instance in the context of placebo analgesia we can ask whether placebo um effects are really supported by pain specific mechanisms or are we looking at the same mechanisms that might also be relevant in Placebo effects for depression and then finally from a social standpoint we can really isolate what the role is of the social context surrounding treatment um and so I a couple years back um wrote a riew kind of looking at CBO effects from this um social affect of Neuroscience standpoint Focus on the role of expectations affect and the social context today I'd like to focus first on magntic work using Neuroscience to understand how Placebo effects are mediated and secondly um to address the role of the social context surrounding treatment which I think has implications not only for the study of placebo and clinical outcomes but also for reducing Health disparities more generally and I think I do want to say that I think the study of Placebo can really point to all the different features of the psychosocial context that influence clinical outcomes so this is why I think um there's so much we can take from the study of placebo more generally so turning first to how Placebo effects were mediated so of course throughout the day we've been talking about how expectations um associated with treatment outcomes can directly influence clinical outcomes in the form of placebo and tour mentioned um if we not only compare um treatment arms to Placebo groups to isolate drug effects but instead also include Natural History control groups we can isolate Placebo effects on treatment outcome by controlling for things like regression to the need now again this came up earlier but a metaanalysis of clinical trials that compared Placebo with no treatment revealed that there was no placebo effect on binary outcomes or objective outcomes but there was a substantial placeo effect on continuous subjective outcomes and especially in the context of pain the authors concluded that the fact that placebos had no significant effect on objective continuous outcomes suggests that reporting bias may have been a factor in the trials with subjective outcomes so the idea here when we talk about kind of our model of placebo traditionally we think that things like social dynamics psychosocial context surrounding treatment cues associated with treatments lead to changes in one's sensory processing or in one's bodily State and based on that one makes a subjective decision about how one is feeling for instance a placebo effect in depression might lead to shifts in emotional processing or a placebo effect in pain would lead to someone um reporting less pain and if this is really driven by report biases the idea is that rather than expectations changing that sensory processing they affect subjective responses directly perhaps by changing our Criterion for calling something painful so for over two decades now the field has really focused on asking to what extent are these effects mediated By changes in sensory processing and Placebo effects in pain are a really ideal way for us to ask this question because we can objectively manipulate pain in the lab so we can use this device called the thermode heat it up to different temperatures and measure how much pain it elicits and the targets of Asing no receptive signals are well
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studied very well known and we know the traps that transfer this um information to the uh cortex and these can be visualized using functional magnetic resonance imaging or fmr so we see reliable activation in response to changes to no acceptive stimuli um in a network of regions often referred to as the pain Matrix including insolid or Solan singulate Thalamus mat sensory cortex um and uh brain stem and cerebal now we used um machine learning to identify a pattern of Weights which we call the neurologic pain signature but is sensitive and specific to pain and can reliably detect whether something is painful or not and which of two uh condition is more painful so this really provides an opportunity to ask when cbos affect pain so for instance if we apply an inner topical uh treatment to a patient's arm before administering noxious stimuli that they believe will reduce pain does this pain reduction come about through changes in pain specific brain mechanisms or do we see shifts in more General mechanisms such as shifts in aect things like emotion regul a or value based learning so maybe people just feel less anxious but there's nothing specifically about pain this isn't really a problem because this would also mean that what we're learning about might transfer to other domains so um couple years back uh nearly all Labs that use neuroimaging to study Placebo analgesia um in the brain combin patient level data and what we found is that there was a reliable reduction in pain reports during uh FM scanning when people uh had a top an analgesic treatment or a placebo sorry um relative to control treatment that they didn't believe would reduce pain um with a moderate to large effect size but there was no reliable placebo effect on The NPS so this suggests that really we're not seeing Placebo effects on this kind of best brain based biomarker of pain what do we see Placebo effects uh modulating oh sorry uh it's important for me to say that even though we don't see Placebo effects on NPS there are other psychological manipulations such as mindfulness who's that predict different levels of pain or administering treatments that reduce pain um both uh when subjects know they're receiving it or when they believe they're not receiving it and these all did affect NPS um responses so it is possible for psychological uh treatments to modulate The NPS but we didn't see any placebo effect on um NPS responses um we also conducted a meta analysis of placebo analgesia looking at other published studies and what we found is that there were reliable reductions during pain um with Placebo Administration in the insula Thalamus and dorsal anterior singulate now these regions are indeed targets of those asending no receptive Pathways that I mentioned however these regions are also activated by pretty much any Salient um stimulus in the fmri scanner um as well as by uh anything involving inter reception or attention to the body and so I think an important point for the discussion is to what extent are these mechanisms or any of the principles we've been talking about today unique to pain or depression or any specific clinical end point um when we looked for Regions that showed increases with Placebo we saw increases in the vent medial prefrontal cortex dor lateral prefrontal cortex and the straum regions that really have been implicated in domain General shifts in affect things like emotion regulation and um learning about valued outcomes so in this first half of my talk I've demonstrated that poo effects seem to be mediated by domain General circuits involved in salience affective value and cognitive control we did not see any Placebo effects on the neurologic pain signature pattern and this really points to the idea that these Placebo mechanisms are unlikely to be specific to pain um however you know this there's many different Labs working on different mechanisms of placebo and so I think this is an ongoing question that really demands um further trials uh and different comparisons um within and across participants um so now I'd like to turn to the second half of my talk addressing
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the role of the social context surrounding treatment and I'm going to talk about this in terms of patients expectations providers assessments of patients pain and um patient pain outcomes themselves so um we were interested in asking whether P patients perceptions of providers impact pain expectations um and we know from work that uh Winfred and many others have conducted that indeed um Placebo responses depend on many different um factors in the patient provider relationship including um uh how a provider treats a patient so Ted kuk and his group showed that a warm provider can lead to um reductions in uh IBS in a open label Placebo trial um we just heard um data on how providers warmth and competence can influence outcomes and this has also been shown in experimental context um by Ali Crums lab and finally um and I'll present this briefly at the end of my talk we also know that if patients perceive similarity to their provider um also influences pain and Placebo effects in um simulated clinical interactions so a former postto in my lab Liz NECA was interested in studying this by asking not only whether interactions between patient provider influence pain expectations but also whether our first impressions of our providers mainly in terms of their competence and or similarity to US influence expectations even without actual interactions and the reason Liz wanted to do this is because we know from social psychology that people's first impressions are really um important for a lot of different behaviors so simply looking at people's faces can predict um and judging competence can predict the outcomes of Elections um and this is work that really has been led by Alex todorov and his group um so these faces are morphed along a dimension of competence and so you can kind of see um moving from three standard deviations below the mean to three standard deviations above the mean that there are certain features that are sort of associated with competence and dominance and that we use to make judgments about that person's trait and so Liz asked whether these types of First Impressions also influence expectations about pain and treatment outcomes we conducted five studies on using Amazon's me mechanical T and the first studies used those morph faces from Toops group um importantly these were just male faces in the first two studies in our third study we used the same competence Dimensions morphed onto either male or female faces we conducted another study in which we removed any cues like hair or um clothing um and gestured the face the more male or female face itself between subjects and in the final study we used real individual spaces that varied in race and ethnicity um and again had a between groups manipulation of sex on each trial participants first went through a series of trials in which they saw two faces that varied in competence um and told us which provider they would prefer for a potential uh painful medical um uh intervention and then they were asked to imagine that provider were performing a painful medical procedure on them how painful will the procedure be and after the procedure are you more likely to use over-the-counter or prescription medication assuming that if the procedure is less painful they would assume they would um expect to be more likely to use over the counter medication we also asked about similarity but I won't be focusing on that today um so across all of the studies um so this is chance this is that first decision How likely are you to select and more competent face what we found is that participants chose the more competent looking provider based on those facial features um in the first study replicated that in the second study and in the third study we found no difference as a function of the features related to competence in part because people preferred doctors who female doctors who looked less competent based on these features um in the fourth study we used uh other individuals ratings of perceived competence and again found that people selected more competent faces but they also preferred this uh particularly only in the male faces and when we use these real
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individuals we again found that other people's ratings of competence predicted somebody's likelihood of selecting that person as their provider um and this was strongest uh when it came to White providers we found that competence um directly influence pain expectations in all of the studies except for study three so here this is the association between ratings of competence and pain and so you see higher competence is associated with less pain across all the studies but study three and again all the studies showed that the stronger the competence the more likely somebody was to say they would have um an over-the-counter relative to prescription um treatment in that study um but we found an interaction with sex such that competence predicted overthe counter treatment only for male participants whereas competent female providers were associated with higher likelihood of having um prescription medication rather than over the counter um finally we found that uh stereotypes or these kind of uh information about race ethnicity and gender which we were able to test in the fifth study also impacted pain expectations so in study five we found that expectations about pain VAR as function of Provider race we found that people expected the Le least amount of pain and the highest likelihood of overthe counter Med medication from the Asian providers relative to all others and we also found sex differences in the expected medication use and finally when we ran a meta analysis across all the studies we found that effects of similarity unexpected analgesic use were strongest in weight participants um and this is likely to be kind of an ingroup preference um namely because studies one through four all included weight providers and we found no other effects of the perceiver demographics themselves um just with the last like three minutes or so um we know that not only do patients stereotypes impact per uh perceptions of providers but we also know through studies on health disparities that providers um beliefs also impact uh assessment of patients pain um so Peter Mani has really run a series of beautiful studies looking at how um race bias um on pain assessment may be mediated through perceptual changes um Peter had black or white male actors um depict pain or neutral Fe and he created morph uh images ranging from neutral to painful and what he found is that white receivers um needed more evidence of a pain expression before labeling pain on Black Faces relative to White faces and the more of a difference they had in terms of um likelihood of seeing pain on white relative to Black Faces also pres predicted prescribing more um analgesics to weight Rel to Black targets across a number of studies we asked whether we saw similar biases and evaluations of real pain um by measuring facial reactions and acute pain in 100 healthy individuals who um label rated pain uh in response to heat shock or cold water bath and what you can see is people have very different reactions to pain this is all kind of the same level of pain but you see differences in expressiveness and we're going to be um creating a public database that will be available for other researchers to use to study um pain assessment in diverse individuals we had other healthy volunteers view these videos um and assess pain um and critically we selected pain so that there were no differences across Target race or gender in terms of the pain or its intensity th all the videos we presented were matched and subjects saw videos and rated whether this the target was in pain or not and how intense the pain was and what we found is that perceivers were less likely to ascribe pain to Black individuals relative to White individuals so again um uh so black is here in Canan and white is in um pink and the women are with the hash lines and the male far as they solid um and these are all again selected for trials where everybody was feeling the same amount of pain and this is really driven by a failure to ascribe pain to black male participants when they were
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experiencing pain and this was supported by signal detection analyses we found that these race-based differences in pain assessment correlated with scores on a modern racism scale but did not veryy dependent on perceiver race or gender um and we're now doing a study basically looking at how this type of bias might be reduced through learning and instructions so basically we find that when people are told about a participant's pain after every trial they are more accurate in judging other people's pain and that whether or not people receive feedback um pain assessment accuracy improves over time as people practice suggesting we may be able to um reduce these pain assessment biases um through training and perhaps in clinical samples um and finally I just want to acknowledge that in this kind of dietic interaction we really ultimately also want to look at the direct interpersonal interactions that shape witho anesia and this has been done by a series of studies um uh of simulated clinical interactions where healthy volunteers are randomly assigned to act as doctor or patient and they administer a placebo to somebody else um so Andy Chen and Chen showed that telling a doctor that a treatment was analgesic um affected the patient's pain and that this was likely to be mediated through nonverbal communication Liz loon's lab showed that or Liz loen when she was in tours lab showed that the more similarity or trust somebody had for a clinician the lowest pain they experienced and finally Steve Anderson a grad student with Liz losen showed that um racial concordance between the patient and the provider in a placebo context could reduce pain particularly in Black individuals um and this was also associated with reduced physiological arousal so just to summarize the second part on the role of the social context surround treatment I've shown you that first impressions shape pain expectations um stereotypes impact pain expectations and pain assessment um and that concordance can enhance um treatment outcomes finally just to kind of um make clear where I think the path forward is from this kind of social aspect of Neuroscience approach I believe that further research on how social factors shape clinical outcomes including Placebo effects and placebo anesia can help us improve patient provider interactions reduce Health disparities in general and maximize beneficial patient outcomes and that we need more work distinguishing between domain specific and domain General mechanisms of placebo in order to isolate um general effects of the clinical context versus targeting disease specific end points and identifying these kind of domain specific mechanisms and the features of both patients and providers can really help us address the goals of personalized medicine so with that I want to thank the organizers again for the opportunity to present um our work and acknowledge my former posttop Liz Neta my former PhD student Troy zign my current postto El xia and mention that we have positions available in my lab you all right wonderful thank you Lauren um so that concludes the series of presentations for this webinar for today but we're not done yet now we're moving into a phase where we have a panel discussion and um so it's going to be very exciting um and we'll get a chance to sort of talk about some of your comments you brought up and other things uh so this is moderated By Carolyn Rodriguez and Alexander tski so uh hi thank you for doing this and please lead us off oh yeah definitely so it's my pleasure to do this with Alex my name is Carolyn Rodriguez I'm a professor at Stanford and I see it there has been a very Lively uh Q&A already um and some of them are being answered um so well maybe we'll just popcorn a little bit um there is one question here which you know I think gets it what we presenting is a lot of human data and so I maybe it's just worth noting are studies and animals free of placebo effect and Tor I see that you're typing an answer but I don't know if you wanted to answer that uh sure yeah I just finished typing my answer but yeah um it's a good discussion point I mean I think that um
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one of the first um studies of placebo effects was by hernstein in 1965 in science called Placebo effects in the rat I think it was called and there uh there's a Resurgence too of modern Neuroscience work on Placebo effects in animal Greg quter is going to give a talk on this tomorrow as one of the group of investigators doing this um so long story short I think that um that there are conditioned or learned Placebo effects um so pharmacological conditioning pairing with the drug queue or conditioning with Place cues can change the um response patterns of animals as well it's difficult to know what animals are expecting but there's quite a bit of circumstantial evidence or other evidence from other places um even from Robert roscorla years back or from Jeff shbomb that really used clever paradigms to suggest that animals it's really a lot about the information value and that they're sort of expecting uh you know and predicting a lot more than we might at first assume so even in those conditioning paradigms there might be a lot of something very similar to what we call an sort of internal mental model or expectations that are that's happened so that's my first any of the panelists the panelist feel free to just you know uh turn on the your videos and we'll be sort of uh um you know asking about anybody else want to weigh in on animals and Placebo uh go ahead Dr Atlas I'd be happy to do so um actually there's a study I love um from a former postto who worked with me instantly during her PhD um that we haven't really talked about the roles of dopamine and opioid so far today which is interesting because those often dominate um our conversations about mechanisms of placebo but um inen had a really lovely study in which she showed that dopamine was necessary for learning the association between a context and Pain Relief while op opioids mu opioid receptor system was necessary for actually experiencing that pain relief and so that's a really nice kind of dissociation between that Learning and Development of expectations and the actual pain modulation um so that was a really lovely uh place where I thought that the preclinical work had some really nice findings for those of us who are doing human studies yeah wonderful thank you and I think there there's still a day two so stay tuned there's I'm I can see in the agenda there'll be more on this but a question I think specifically for you was how does nstone influence The NPS so if there's any I think you answered it but if there's any additional things I think that's a great question and um I actually don't know of any studies that have administered Noone and looked at NPS responses um the Noone effects on fmri responses in Placebo actually um I think we may have I'll just say a bit of a f problem there are a lot of studies that haven't found effects we really need everybody to kind of publish their data um but I think we've shown that there are studies of opioid or their effects of opioid analgesics but I don't think we know about blocking the opioid um system and its effect on The NPS but that would be really interesting and important so that's a great suggestion question yeah I look forward to that's very exciting uh question I'm gonna hop over to neuromodulation um Dr lizen and Dr Deng I think you guys had already answered a question which I found fascinating about whether when you try and get the motor threshold um what like does that unblind people so I loved your answer and I just wanted you guys to just say it out loud yeah thank you I can start and Z might want to comment as well so as uh you may know we uh individualize the intensity of transcranial magnetic stimulation by determining the motor threshold where we stimulate with single magnetic pulses over the primary motor cortex and measure and muscle twitch in the hand and um this is real TMS and we do real TMS for motor threshold determination uh regardless of whether the person is going to be getting active or Sham in order to give them the same level of intensity and so on and you might think uh plausibly speaking that this might unblind them if then you give them sham rtms with repetitive pulses it turns out that single pulses um do not cause the same amount of scalp pain uh or discomfort that repetitive trains of stimulation can cause also the motor cortex is farther away from the uh facial uh muscles and facial nerves so there's less of a noxious effect of stimulating over the motor cortex and because of these differences it is very a common occurrence that people think they're getting active rtms even when they're assigned to Sham but maybe uh Z
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might want to comment no I totally agree with that the different protocols feel very different and so uh being uh non naive to one protocol may not necessarily mean that you break the blind wonderful thank you so much and Dr Ding as always I always appreciate your humor in your presentation so thank you for that um we're going to move over um Dr deki um I think you had um U messaged um that you have a couple slides that may address some of the questions and particularly um Steve Brennan had asked a question about covid interference and there was a question about excluding sites with unusual response patterns um so would love to hear more about that I think you're on mute though we'd love to hear you there we go um I have one kind of interesting uh slide on Co it's it kind of doesn't it doesn't get directly at the placeo response let me walk you through it's a weird slide because we've been looking at slides all day that like from left to right is changing is the duration of the study uh or the treatment this is actually as you can see at the on the um the xaxis is actual calendar months and then focus at first on the blue line is the adcs ADL which is a scale of activities of daily living and there are actually questions in it about you know have you gone to the grocery store recently um are you able to do that by yourself have you gone to you know attend to doctor's appointments um things like that and the the reduction from um the from early 2020 to kind of the peak of the pandemic this change of like five points or so this would be kind of the biggest this is an Alzheimer's study and this would be the biggest drug effect in the history of Alzheimer's and then this change back even faster um of a similar actually slightly larger magnitude was also a huge change this is pool drug and Placebo patients so there's nothing in here that tells you anything about drug effects or not but you can see this ADL um was really impacted by the peak of covid cases um and I'm actually surprised this came out as clean as it did because we had about 30% of our patients were in Europe Italy France Spain and as you may recall the peak of cases there was at a different time in the US but the I think the takeaway here is that obviously things like Co can certainly impact a su scales um and they're certainly going to impact scales that specifically say hey have you gone to your doctor's office when you can't go to the doctor's office um uh scales like that are going to be really more impacted obviously than you know maybe just a and moods and things could be too obviously but um but that's at least one piece of data I know that that Co had a whopping effect on at least one scale um as for the the sites over time there's been a lot that's been talked about and thought about um you know uh excluding sites with high Placebo response excluding sites with low drug Placebo separation of course if you do that post ha talk it's certainly not valid there's a band pass approach where you exclude the extreme sites on both ends high and low placeo response is a somewhat more valid um but my understanding from statisticians is that any of those things increase false positives if you're doing it post Hawk um the other the other thing to think about when you're thinking about site performance is a sites change over time they have different Raiders you know that might be there for 10 years or maybe a week 10 months or um the um and maybe the single most important point on this response is realize you know the average depression trial 100 150 patients per arm 80% power to see a separation and it's really 50% power as n kin has shown and others um effectively um now imagine you're looking at a clinical trial site they have 10 patients five per on what's the statistical power there it's it's close to zero um and this is so these are some data that uh my colleague Dave deoda at Lily put together a long time ago um huge database of I think these were proac depression studies and they had the same you know over many studies and me in and many of them went back to the same sites that um performed well um and you can as you can see here the same site this the each chart is a site that was in multiple different uh studies and there
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and their uh um performance over time and hamd change was no different um th this study is another study that just looks at um these are different investigative sites um in the same trial um and this is a little bit of a build but you can see that this site and this site have virtually identical drug responses the yellow bars uh sorry that's supposed to be a little higher but oops oh man um they have almost identical uh efficacy response but this one has a huge PBO response and that one has a tiny PBO response which is probably because they only had five or six subjects per site and if you get just you know two or three huge Placebo responders so the um trying to assess site performance in the context of a single trial is is pretty hard just because of the ends um a and um and then so evaluating performance by sites um is challenging and then excluding them for reasons like hleo responses is also challenging um so thank you those are just a little bit of context on that yeah appreciate that um question for your colleague um Dr but maybe for everyone right so there's a question here that says isn't it difficult to say that a two-point difference on a 52 point scale is clinically significant so I know a lot of slides we were trying to say well you know is this is going to be significant and what's the difference between um you know these two scales so you know at the end of the day we're you know wanting to help patients and so what um you know what can we say about a two-point change in significance so two-point change is the difference between drug and the placebo so each individual might have 10p Point change or 50% change depending on the individual response and mostly drug approval is based on statistical significance so if there is a two points difference between drug and Placebo for example Hamilton depression score generally that's the uh that's the approximate total point change between the two groups that most of the drugs get approved so uh so of course uh statistical significant changes basing we based for drug approval but for in real world uh we don't really know what clinically meaningful uh change or difference right so that's still an issue so Tiffy might be able to add more on this topic yeah I mean I can add a little bit you know so in terms of like the depression studies again those were conducted before our sort of what we do now like if we have a new indication a new endpoint something like that we're going to ask companies to give us an aiori um definition of clinically meaningful within patient change and we're looking like n said at the difference for a an not the difference between the drug and the pobo but what matters to patients how much change do they need to have and then you know they can have that they can power their study to see you know some amount of difference that they think matters but ultimately you know we have them anchor their studies to um you know things like Global assessments of functioning we have sponsors if they're using new endpoints um do qualitative work so that we can understand what that change means on that given scale there's a lot of additional work that goes into it now but yeah it's the within patient change not the between group changes that ultimately matters the most thank you so much I I felt like it was worth saying out loud and Dr fion I know you've um done a lot of wonderful work I heard you speak at acnp about you know kind of more Global uh measurements of functioning and really you know thinking about patients more globally right you can change a little bit on a scale but does that translate into life functioning work functioning these are the things that we care about for our patients so thank you uh both for that I see Dr Reef has a wants to weigh in and then Dr lisenby yes just to add a little point I think the smaller the benefit is of between the truck and the placebo arm the more the question has to be asked about the benefit arm ratio and therefore it is an important issue and it was very good that this question was asked because I would really say if the difference is just two points we have to compare it with the risk and potential side effects it's not only that we can focus on the benefits we always compare it to the risks regardless of the size of that difference all right Dr
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liiz so this is an opportunity to talk about outcome measures and how sensitive they are to the intervention and also how proximal with respect to mechanism and these are some points uh that Dr fion raised in her talk as well uh in Psychiatry the degree to which we can have outcome measures that um are more proximal to what our intervention does to engage mechanisms that this might help us be able to uh measure and differentiate uh active treatment effects versus uh non-specific Placebo effects and this is part of the um uh rationale of the research domain criteria or er do research platform to try to look at domains of function to look at them across levels of analysis uh and have measurements uh that might not just be a clinical rating scale it might be a neurocognitive task that's related to the cognitive function that might be the target of the therapy uh or a physiological measure uh that might be uh an intermediate outcome measure uh and so I was hoping we might generate some discussion in the panel uh about uh regulatory Pathways for these other types of outcome measures and how we might think about um selecting outcome measures that may be better at differentiating real treatment effects from a non-specific Placebo effects thank you I see Dr wager I don't know if you had something to add on to Dr lnb's point or you had a separate question I would like to add on to that if I may I think that's a really important question I'd love to hear people's opinions about it especially um the FDA You Know Tiffany perspective on it because for me to add to that I'm just was wondering um how strongly the FDA considers um pathophysiology and mechanism of action and what counts as a mechanism of action so there's certainly certain pharmacological changes and cellular level changes that obviously seem to matter a lot but what about fmri EEG other kinds of indirect measures do they count or have they counted as a you know mechanistic evidence yeah so there they haven't counted yet and in part because we just don't have you know so far in EGF MRI stuff like that we see group differences but those aren't the kinds of things that can help you to predict something for an individual um patient um you know it just goes back to the whole point about understanding pathophysiology and being able to um you know not just describe that you know this drug works on you know this receptor but also that working on this receptor has that relationship Downstream to you know X Y and Z effects um and in a clinically meaningful way I think ultimately you know a lot of the things that we do in terms of our biomarker qualification program and things like that understanding not just um that a drug has some action or interacts with some sort of biology but in what way and what kind of information does that give you that can help inform the trial or help inform um you know your assessment of drug effect that's also important it's um we're a long way off from being able to put things like um like that into a drug label I would say right Dr liby um certainly agree um with Dr F's uh comments and I would like to talk for a moment about devices and there might be different there are different regulations uh and different um considerations in drug uh design versus uh device uh trial design and we are already at a stage in the field of devices where individual physiology is on the label and that's the case with um the saint uh technology uh where individual resting state functional connectivity MRI is used to Target on each patient basis where to put the TMS coil and um I would say that we the jury is still out about um you know studies that unpack Saint to show whether that individualized targeting is essential or whether it's the accelerated intermittent Theta burst and the 10 treatments a day and so on but it regardless it is actually on the label uh it's in it's uh in the instructions for how to use the product um and so I think that might be uh a sign of where things may be going in the future and when we think about the way um uh focal brain stimulation is administered whether it's non-invasive or surgically
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implanted we're targeting uh circuits in the brain uh and being able to measure the impact of that targeted stimulation on the functioning of that circuit EEG or fmri might be the right readout and that might give uh some evidence I think even still though those measures uh which may be useful in uh identifying uh treatments and optimizing their dosing ultimately I understand um from my FDA colleagues that we'll still need to demonstrate that intervention whatever it is uh improves uh the quality of life um uh and the uh the clinical aspects for those patients um but it may be an important part of getting the treatments uh to that phase uh where they could be reviewed by FDA thank you so much that's a good point any anyone else to contribute to that I don't see any other hands raised so maybe I'll pass it to Dr um uh chalk kosi and see if there are any other questions that you see on the um qu Q&A um that uh we could continue to ask the panel yeah there was one that jumped out to me a bit earlier there was a bit of a discussion about warmth and competence as well as a perceived tradeoff between the two and also some uh ideas about manipulating them as experimental variables that I thought was interesting I saw Dr Reef you had jumped into that discussion too uh but I thought that was an important enough topic that would be worth spending a little bit more time uh here in the group discussion uh making sure that everybody sees so uh I'll throw it back to you Dr Reef uh if you could maybe even elaborate on the answer you gave in there about warmth and competence and those is experimental variables too yes so the major point I want to make is that we have to control these variables if we don't control them we risk that they are different between our two arms or three arms in our trials and then we don't we cannot interpret the the results that means we have to assess it and we have to make sure that they are comparable between the different treatments so this is something I can really recommend I think this makes lot of sense there's there are other points I'm not sure what to recommend there some people suggested shall we limit themselves shall we minimize warmth and competence to minimize potential Placebo effects and this is the point where the tradeoff comes into the game that means if you minimize warmth and competence people are not motivated to participate uh and they might discontinue treatments and they are not willing to cope with side effects uh but if we maximize warmth and competence we risk that the bbo effects is really boostering everything um so I at this level I would at this stage I would say uh let's try to keep it in a in an average level uh but uh really assess it and make sure that it's comparable between the different treatment arms Dr Alice I see your hand up yeah I love this question because I think it depends what the goal is um so the goal is to reduce Placebo to find the best benefit of the drug then yes you know in clinical trials when people never see the same Raider for instance that reduces the likelihood of building a relationship and there's all these different kinds of features that if you really want to minimize Placebo then we can use these things um in that way on the other hand if the goal is to have the best patient outcomes then I think we want to do the exact opposite and essentially identify by exactly how those features um improve patients wellbeing and uh heighten them and so I think really that's part of why I think talking about Placebo is so fascinating because it both tells us how to improve patient outcomes and then also um uh reduce them in the context of Trials so I think it really depends kind of what uh context you're talking about Dr ree yeah may I chest test a point because I missed it and Lauren reminded me to that point most of us assume that we have to reduce the placebo effects to maximize the difference between placeo and track effects and this is an assumption this is not something that we really know that means if we have studies for instance we have seen studies on on anti-depressants on SSRS we know studies from analgesics if you reduce the placebo mechanisms to minimum then you are not able to show a different to the drug uh afterwards because uh also the drug effects are really reducing and in other words a good drug needs some kind some minimum of placebo mechanisms to show its full action and therefore the
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assumption that minimizing Placebo mechanisms to increase the difference between Placebo and drugs is an assumption and we have to be concerned about that and maybe for some drugs it's much better to have a kind of average uh amount of placebo mechanisms uh Dr wager let's go to you then I think uh we have another question that we want to tackle in the chat after uh you wrap up yep that sounds good I see it too um but just to weigh in this because I think this is one of the most important issues to me and I think uh Winford also just wrote a review about this and there's there have been a couple of others which is that um if you there's always this tendency to want to screen out Placebo responders it doesn't seem to have worked very well most of the time in clinical trials and um and if you have a synergistic interaction over additive interaction between a active drug element and a placebo Factor motivation or expectation then um then screening out that's when screening out placeable responders also screens out the drug responders and um so I think there's this opportunity to test this more to test you know jointly the effects of active treatment whether it's neuromodulation or drugs or something else and a um and factors like expectations or um perceive warmth and competence of the of care provider so I guess I'm wondering if um in the neuros stimulation world are there many studies like that or any studies like that because they seem to be very separate worlds right you either study the device or you study the psychosocial aspects um well I can comment Maybe others can as well it's a good point you know Lauren your talk was really beautiful and um the my take on point from that is uh in a device trial um even if we're not studying the effect of the device operator the effect is occurring in the trial and so measuring these aspects of the whole context of care uh I think can help us uh sort that out and uh in order to do that I think it could be helpful for um investigators who are designing device trials to partner with uh investigators who have that expertise uh also in terms of the expertise I was listening very carefully to the talks about um you know psychosocial interventions uh and you know maybe the ancillary effects of the procedure is like a psych psychosocial intervention that you know we might be nefit from having mixed methods approach es that pull from both Fields uh to really better understand what we're doing um and then there are also trials that use drugs and devices together uh so being able to have cross-pollination uh across the fields um I think would be very useful both with respect to our selection of measures to test the Integrity of the blind as well as uh looking at expectancy and even measuring anything about the provider which is usually not done uh in and I would just say for device studies we're usually not even reporting anything about the provider or the um uh perceptions of the subject about uh their the context of care I wanted to um also jump in terms of um you know just in terms of topics um for psych psychedelic assisted therapy Harriet dwit has a very good question here um in terms of commenting about special considerations and testing of placebos this is something that has come up a lot um and um Boris hits um among others has you know really uh gotten us to think about different kinds of designs to disguise the effects of ketamine for example with general anesthesia there's other designs um but questions around the space so how important um is it when you have um a very active um uh Placebo that can have empathogenic effects or psychedelic effects um in terms of the placebo effect yeah I figure I should probably jump in on this one first so you know I will say that when it comes to the psychedelics whether it's the classic psychedelics like you know like psilocybin or if it's the you know empathogen intogen types like MDMA um blinding is practically impossible folks know if they're on active drug or Placebo um and and that makes it really challenging to have an adequate and well controlled study right on the one hand we still need to have Placebo controlled study so that we can get you know a fairly AC well as accurate as you can get um assessment of safety of the drug um on the other hand you know
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we've really been struggling with trying to figure out what is the best design trying to add some kind of an active comparator you know choosing something that might mimic some aspect of the Psychedelic effect without actually having a a treatment effect of any kind is next to Impossible people still know you know you've talked about anything from n or benzes or a little bit of this that it's just they know they just know so um the best that we've come up with so far is you know again asking for at least one Placebo controled study so that we can really get a clear idea of safety and then we've suggested trying to use complimentary designs so for in um you know it is still possible to have a dose response study serve as an adequate and well-controlled study so then there's no Placebo there and if you can see that a lower dose a mid dose a high dose if there's a sort of linear increase in treatment effect in that kind of a study that's helpful to us um if we have uh one of the other things we ask for is to have some assessment of you know like an unblinding questionnaire do you think that you got the active drug yes or no do you think you got Placebo and then um one of the things that we're starting to ask for now in addition to that is not just an assessment at the end of whether folks thought they were on active drug or not just from the patient but now also like from the Raiders trying to see because we can and a lot of times that the Raiders can figure out what the person was on to so that could introduce some bias but now we're also starting to think about you know asking for um like a pre-dose expectancy questionnaire of some kind um and so you know even if we can't necessarily control for the unblinding issues and the expectancy and everything at least we can try to um we can have more data to assess the impact on the study and use those as maybe you know covariates in the analyses but yeah we we don't have the right answer yet we are learning as we go and we are learning very rapidly so there may be a plug for NIMH to do another you know this Placebo panel is amazing we could keep going um I see we have nine minutes left I'm going to pass it back to H Dr chalk kovski and but I know Dr lizen be and Dr wager um have their hands up so I'll pack it pass it back to Alex uh thank you uh there because we're short on time uh with apologies Dr elizia Dr wager there's a question I want to uh address from the Q&A box that I saw a couple of our panelists already uh just addressed in text but uh seems worth bringing up here as a group uh are we confident that the placebo effect in specific effect are additive and not interactive so I'll just can I oh sorry Dr Atlas yes that was quick you w the buzzer I had already responded Ann was putting something in the chat um kind of addressing the Asing dose in the same context so basically one approach for kind of testing additivity is to use the balanced Placebo design so people receive drug or control and that is um uh cross with instructions about Drug Administration so basically people receive the drug under open Administration um and they also receive tobo and they receive a drug that they believe they're not getting um treatment relating to Hidden Administration and this has been tested with nicotine um effects on uh so nicotine caffeine we've done it in the context of Remy fanel and there's been a couple other trials of different analgesics it was really developed in the context of um studies of alcohol we found for instance that depending on the end point we have different conclusions about additivity so when it came to pain we found additive effects on pain but we found pure drug effects on neurologic pain signature responses um during Remy regardless of whether people knew they were receiving the drug or not we found interactions um when we looked at effects on attention um and other groups so Christian bule's group has found interactions when they did the same exact trial but used lioc so and then furthermore this is where I think what we were just talking about in the context of aing doses if people have unblinding at higher doses then there's going to be less of an effect of the context surrounding it so expectations could grow with um higher drug effects so I think that the question of activity or interactions really may depend on the dose the specific drug and the specific endpoint I don't think we can really um conclude that and so even though doing
Segment 47 (230:00 - 235:00)
balanced lbo designs do require a level of deception um I think there's really an urgent need to kind of understand how expectations combin with drugs to influence outcomes so um yeah I'm really glad somebody asked that question thank you Dr Atlas and um I just want to acknowledge Dr Christina kusen who's the other um co-chair for the panel she's on um and I want to be mindful of the time and make sure that she and um Dr wager um have the final words or thoughts or if you want to give the panelist the thoughts but we wanted to just pass it back to you so that you had plenty of time to say um any of the things that you wanted to say to wrap things up I will leave to Thor if he has any concluding remark my job will be to summarize the wonderful presentation from today and a brief overview at the um at the beginning of the meeting tomorrow so I thought it was amazing Thor thanks Christina um I know since we have a few minutes left um I would like I go back to uh what Holly was going to say think we have like about five minutes and so um yeah I'd love to just use that time to continue that conversation uh I'm assuming that you're referring to the Psychedelic question so um one of I agree that there's no perfect answer to that and it's very complicated um and there are different views on how to address it um one of my concerns is therapist and blinding um and the potential impact of therapist and blinding on the therapy that's being administered and um because as we've heard it's very likely that the patient receiving a psychedelic intervention may be unblinded so might the therapist because they know what a patient going through psychedelic assisted therapy typically experiences and one thought I have about that could be to measure the therapy uh record it um quantify adherence to the manual uh at least document um what's going on in the therapy interaction H that would give you some data that might help you interpret and better understand whether therapist and blinding is impacting the psychosocial aspects of the intervention because we do we've heard from the field that the set and setting and these other aspects of the context of the use of the Psychedelic are an important part so let's measure that too um that's yeah it's really interesting I wanted to note that there's another Boris hitz has put in the chat something that's a sort of a different take so there might be more things to discuss about um you know whether it's possible to Blind these things in some ways and some diversity of opinions there but you can see the chat comment and we can think about that um I have one other question about that which is that to me I um understand the unblinding problem and that seems to be something we're all really concerned about and what about what you call a sens sensitivity uh analysis type of design which is if you can independently manipulate expectations or context and maybe some of these other kinds of um drug manipulations that induce another kind of experience right um that is not the target drug then um then you can see whether the outcomes are sensitive to those things or not so for some outcomes they might it might not matter what you think or feel or whether you had a you know crazy experience uh or not and if it doesn't then that's ignorable right so you can manipulate that independently um you don't have to Blind it out of your you know main um manipulation um and or it might turn out to be that yes that outcome is very sensitive to those kinds of manipulations so I was wondering what you think about this kind of design yeah not quite sure that I followed it entirely yeah it's really like it so you have one that's the psychedelic drug and you don't unblind it but then you do an independent manipulation to try to manipulate the non-specific factors but if it's you know having a a you know so unique experience or having a um yeah or or just treatment expectations I guess that's the piece I'm not quite understanding because not sure what you would be manipulating and how you would accomplish that um in the simplest with the expectation piece is um simpler because you can induce expectations in other ways as well um right by you know giving
Segment 48 (235:00 - 237:00)
people suggestions that it's going to really impact them or for example a design that we've used is to say okay everyone's you know if you get this drug it's going to make you I don't know you know it's going to give you these sort of strange experiences but if it gives you those experiences that means that it's not working for you that's bad right in other group you say this is a sign that it's working so you take that you know the subjective symptoms um and give people different instructions that those are going to be either helpful or harmful um and see if that matters yeah I mean I think if you're giving different people different instructions now you're introducing a different source of potential variability so that kind of makes me a little bit nervous I guess what I would say is that if somebody had you know some sort of like creative problemsolving approach to dealing with this I would love to hear about it see a proposal and a protocol I would say it's probably best to do that in kind of like an exploratory proof of concept way first before you know trying to implement a bunch of fancy bells and whistles in a pivotal study that would you know try to support the actual approval of a product but um you know again like because we're learning as we go we do tend to be pretty open to um you know different uh design ideas here in different strategies you know as long as people are being monitored appropriately because that piece we don't really budge on yeah I see we're at time and um maybe give uh Dr lizen be the last word but maybe just a some food for food for thought is it maybe be nice to have like a little toolkit to help clinical trialists um have some consideration about how to minimize Placebo effects would be uh something nice wish list yeah and I just wanted to add uh to that last question that this is part of why we're sponsoring this Workshop we want to hear from you what are the gaps in the field what uh research needs to be done uh because we are interested in developing safe and effective interventions be they psychosocial drug device or some combination and the research studies that we support use placebos or other forms of control so we're very interested in hearing from you where the research gaps are what sort of manipulations like to you were talking about manipulating expectation to figure out how to do that all of that is really interesting research topics um whether that's the design of a pivotal trial or not doesn't necessarily need to be that but really we're really interested in mapping that research Gap space so that we can figure out how to be most helpful to the field wonderful that's a great last word we still have tomorrow to solve it all so um hope you all join us tomorrow and looking forward to it
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