My name is Jacques Ambrose. I'm the senior medical director at Columbia. And it is my distinct honor and pleasure to introduce Dr. Joshua Gordon. He has a very, very long bio, as you can imagine. So I'm going to try to truncate it. Dr. Gordon has been the director of the National Institute of Mental Health since 2016. He obtained his MD and PhD from UCSF, where he completed his residency in psychiatry at Columbia, where he served on the faculty between 2004 and 2016. His research focuses on neurobiological mechanisms of psychiatric disease. The NIMH is the principal federal agency responsible for conducting and supporting mental health research in the US and the largest funder of mental health research in the world. So please join me in giving a round of applause to Dr. Gordon. Thank you, Jacques. And thank you all for coming, both those of you here in the room and those of you who are online. I'm not sure where the camera is to look at you, so I'll just look out into the distance. It's a real pleasure to be here back in San Francisco and to give you a bit about our priorities in mental health research from the NIMH. And there should be significant time at the end for questions from the audience, either here or online. The agenda of my talk first acknowledges the fact that we are in what is actually a really exciting time from the national perspective. And that excitement, of course, is born out of tragedy, as I'll get into in a moment, but it has led to the increase in needs for mental health across the United States, has led to an increased national focus on mental health. So I'll talk a little bit about that. I'll talk some about NIMH's priority areas for mental health research. Let me just say at the outset that if your favorite area isn't represented there, it's unlikely because we are not interested in it, but more that I can't fit everything that we do or that we support into this talk. So it's really just some hand-selected areas of research. I'm then going to move from the general priority areas into really a focus on improving health in the here and now and in the near term, whether we're talking about mental health research that has had an impact on mental health care, whether we're talking about potentially near-term changes as we move towards precision psychiatry, or whether we're talking about research into mental health services, which is having that near-term impact. So let's talk first, though, about the current time and what it means for mental health and mental health research in the United States. Most of you know that the Surgeon General of the United States has taken it upon himself, in particular, to call out the current crisis in mental health, especially as it affects our youth. And you all know this crisis because you're living it on the front lines. The US Surgeon General put out a report in 2021 on protecting youth mental health and additional reports on factors that shape the mental health of young people, and in coming this week, another report, as well, that's of relevance. So I encourage you to pay attention to the news. The Surgeon General's not the only one in the current administration with a focus on mental health. Even the president has, really, for the unprecedented first time in the State of the Union address, both in 2022 and again in 2023, addressed the national mental health crisis with a bipartisan strategy that he includes as part of his unity agenda. This attention on the mental health crisis has resulted also at the level of the White House in a recognition that if we're going to make mental health a priority, we have to also make mental health research a priority. And so the NIMH and other of the institutes at the NIH with portfolios in this area have been working with various offices in the White House to help articulate what research we need to make an impact on mental health in the near and immediate term. And the Congress is also quite interested in trying to address the needs of the mental health research community. They requested in last year's budget, and we submitted this spring, a professional judgment budget on serious mental illness to supplement the president's own budget request, which was submitted in March and which called for a near 10% increase in NIMH's budget. In addition, the Office of Science and Technology Policy, working with the Domestic Policy Council at the White House, released a report on mental health research priorities that we and other institutes, as well as other agencies across the federal government, helped craft. So this is really an unprecedented moment in terms of federal attention to both mental health and mental health research. And hopefully it bodes well for the future in terms of resources being devoted into our field, which, according to many anyway, has been chronically under-resourced. I want to focus for a moment on elements of priority that we have articulated with the White House and to Congress. It's listed here as a professional judgment for serious mental illness as presented to Congress, but the same four focus areas are also included in the president's budget plan. The first focus area is on advancing learning health care to improve mental health outcomes. As some of you may know, NIMH has been investing in collaboration with the Substance Use and Mental Health Service Administration in a learning health care system focused on early psychosis called EpiNet. And with an increase in resources, we have the hope to be able to expand that into additional areas, including creating learning health care systems and certified community behavioral health clinics. I'll tell you a little bit more about EpiNet as we move forward in the talk. The second focus area of our professional judgment budget and of our efforts with the White House is research that's focused on transforming a system of care for youth mental health, which includes priorities in digital health, suicide prevention, and reimagining treatment models. The third focus area is less immediate term and more near term, which is trying to leverage our ability to do precision medicine within psychiatry and therefore to transform the way we treat patients. And then finally, the fourth area is building on the tremendous amount of genetic discovery that we've made to try to advance that knowledge in genetic risk into knowledge in treatment targets. So within that general area, I want to talk to you about some specific priority areas for mental health research that we've articulated at NIMH. As was mentioned, we are the lead federal agency for research on mental illness, which actually makes us the largest funder of mental health research in the globe by a fair degree. We support more than 3,500 research contracts and grants at universities and other institutions, mostly in the United States, but also across the globe. And we have our own intramural research program, which is the size of a large psychiatry department located on the Bethesda campus at the NIH. We have a vision in which a world in mental illnesses are prevented and cured, and a mission to transform the understanding and treatment of those illnesses through basic and clinical research, paving the way for prevention, recovery, and cure. And that mission is articulated in a strategic plan document, which has four distinct priority areas, defining the brain mechanisms underlying complex behavior, examining mental illness trajectories across the lifespan, striving for prevention and cures, and advancing mental health services to strengthen public health. These four areas are each in and of themselves broad. And so I cannot talk to you about all the different priorities that are articulated in the strategic plan. But those of you who are interested in learning what we focus on from the research, I encourage you to visit this document. It is a living document that we update every year. In general, we have a priority-setting system that first looks at good science. What are the scientific opportunities that are out there? What are the projects being proposed? Do they have strong study design, a high standard of rigor? And importantly, do they have the potential for significant impact at the level of public mental health? In addition to good science, our second way of setting priorities is to ensure diversity within that portfolio. And diversity takes many forms. Certainly, we need a diversity in subject matter to make sure we're covering the full breadth of mental illness and how it affects people and communities. We also are concerned with the diversity of workforce, both for science quality reasons and also because that helps make sure that the full diversity of subject matter is covered. We also require diversity in our research participants to ensure that the knowledge generated by our research can be used to help individuals, regardless of who they are or where they come from. And importantly, a diversity of timeframes. That is, we recognize we are in the midst of a mental health crisis, and we need research that has the potential to change how we provide care in the here and now. We also need to ensure that we're constantly striving to improve and develop novel treatments that will help the next generation of patients. And finally, we have to continue making fundamental investments in science that will pay off in terms of transformative approaches in the more distant future. So the diversity of timeframes is an important consideration. Accordingly, I want to talk to you about three priority areas that are focused in that diversity of timeframes, short-term, medium-term, and long-term. In the short-term, suicide prevention is a priority area because, of course, of the continuingly rising rates in suicide deaths in the United States. In the medium-term, we want to take mathematical and theoretical approaches to improve upon our ability to treat patients in the next decade. And then in the longer-term, we want to be able to harness the tremendous explosion in genetic and neural circuit knowledge to be able to identify novel therapies that could truly transform how we approach patients. We try as much as possible to be transparent in how we are investing your dollars. The dollars, of course, come from Congress. So they come from your taxes and those of your patients. And although it can be challenging to define what is short, medium, or long-term investments beyond some specific examples like those that I just gave you, we roughly group things into short, medium, and long-term by using these three categories. Fundamental basic research that's aimed at understanding how the brain and other parts of the related biological systems work. And that includes fundamental behavioral research as well in orange. In green, a set of research that one might describe as basic science research, but that is focused on translation, that is focused on understanding disease or identifying targets for treatment. And then in blue, research that's either focused on innovations in therapy, or novel therapies, or novel mechanisms of service delivery. And you can see that although there is some fluctuation in time, roughly half our dollars are spent on therapeutics development and services, a little bit less currently in disease-related basic research. And over the time, there's been a significant increase in our investments in fundamental basic research. Our current budget in this fiscal year is something north of $2 billion. That allows us in this fiscal year, we anticipate to be able to fund about a fifth of the grants that come in the door. And that's been fairly consistent over the past five or six years as grant costs have risen and as our budget has also risen. In fact, our budget has been keeping up with inflation over the last half a dozen years or so. You can see that illustrated here in real dollars and in inflation-adjusted dollars in the dark blue. As I mentioned, one of our priorities in the area of diversity is the diversity of the people who do the research. And we, along with many others, were quite concerned that individuals from different communities faced inequity in applying for NIMH research dollars. This is a study that I asked my team to produce, looking at 10 years of grant data from 2008 to 2018, showing that individuals who are Hispanic or Black, when they applied for grants as principal investigators over that time period, had a lower rate of success than their white colleagues. We set about, actually in 2017, to try to make changes that would affect this process and restore equity. We did this in a number of different ways, including diversifying our reviewer pools, changing some of the scientific areas that we emphasize for priority, including enhancements in our portfolios, looking at health disparities, and looking at social determinants of health, which attract a disproportionate number of applications for members of minority groups. And I'm really pleased to say that, as of the last year where we have full data, 2021, we have dramatically narrowed the gap in success rates by race, although the gap in success rates by ethnicity, not shown on this slide, remain there are also substantially narrowed. Again, one of the ways that we do that is by emphasizing the priority area of mental health disparities. And in particular, Congress has been quite concerned, and as I'm sure many of you are, with the rapidly rising rates of suicide deaths and other indices of poor mental health among minority youth. They requested, and we carried out, a separate strategic plan, specifically focused on youth mental health disparities, that emphasizes community engagement, paying attention to the problems of underserved and underrepresented youth, as well as diversifying the workforce to make sure that we continue to have the ability to address these issues. This report was produced in collaboration with several other institutes at NIH, including the National Institute on Minority Health and Health Disparities, and the Eunice Kennedy Shriver National Institute of Child Health and Human Development. So hopefully that brief overview gives you a sense of the breadth of priorities that we have at NIMH. And now I want to delve a little bit deeper into three of those priority areas. Again, the first, trying to ensure that we have mental health research that improves mental health care, the second, precision psychiatry, and the third, mental health services research. Is this out of order? Let me see. Yeah, I think I'm just missing the first section. Well, we'll cover it in the last piece. Yes, all right. So it looks like, sorry, my agenda is a little bit wrong, so we're jumping right into precision psychiatry, and then we'll come back to improving mental health care afterwards. All right, so if we want to do a better job in the near term, treating our patients, yes, there are novel therapies out there on phase three trials, and in large trials of digital therapeutics and psychosocial interventions that can make sometimes significant impacts in patients' lives. But often, even if we were to start trials today, you know that those drugs or therapies wouldn't reach the public for some time. Number one. Number two, as you all experience in caring for patients, right now, we don't have a good way of knowing who's gonna respond best to what treatment. And so there's a lot of time, money, and importantly, burden of mental illness that is wasted during those periods of time when people are searching for the right therapies. Right now, though, we have developed, mostly in academia and some in the private sector, a number of tools which could, could, if properly adapted, help decide who's gonna respond best to what treatment we have to offer. And so I wanna take some time and talk about this precision psychiatry approach because, number one, it's important for us to be able to serve our patients better, and number two, it has the potential to really change how we work. So those of you who see patients with depression, for example, in your practices, will know that when someone comes in to your office complaining of classic symptoms of, say, major depressive disorder, that you have a lot of different treatments to offer. But you'll also know that you don't have a lot of guidance in terms of what treatments are gonna work better for what patient, and so you often talk about the side effects that those patients might want to avoid or the relative costs, be they in time or dollars, of the therapies that you have available instead of the potential efficacy of those treatments for that patient because all our treatments are essentially, essentially similar in efficacy. Well, this study by Conor Liston and colleagues, Andrew Drysdale, it's already a number of years old, was suggested that if we took brain scans from our patients, we might learn something about the propensity to respond to a particular treatment. So I'm showing here an image from their paper in 2017, which represents data from a resting state functional magnetic resonance imaging scan. The details of it are not so important, except the right-hand side of this graph illustrates a map of one of 2,000 individuals' brains in the study. It's a map of connectivity, of synchrony across the brain, and the hot colors are places that are more tightly synchronized and the cool colors are places that are less tightly synchronized. Again, the details are important, except to say that we can construct such a map for each individual. We don't know necessarily what that map means per se about the neurobiology of that individual, or I should say we don't know a whole lot about what that map means, but we can also construct this map for lots and lots of individuals separately and ask how similar are the maps across different individuals. And that's what Andrew Drysdale did. He took data from a large number of collaborators who had done fMRI scans in individuals with depression and showed that using this one particular method of clustering those maps, that you could roughly divide that group into four different brain map types, illustrated on this graph as clusters, on the next graph as biotypes. And what is interesting to me about this study, is the graphs here on this page, which suggest that biotypes one and three are more likely to respond to a particular kind of antidepressant treatment. This is from a subset of those 2,000 individuals, a few hundred of them. Transcranial magnetic stimulation to the medial prefrontal cortex, which is still an experimental TMS. And if you had biotypes two or four, you were less likely to respond to that one treatment. This is a step in the right direction, but it's unfortunately incomplete, right? Because we don't know that biotypes two and four are gonna respond to some other treatment. We just know that they are not likely to respond to this one treatment that was used for this one study. Another pathway, rather than using neuroimaging data, is to use EEG data. And that's a pathway that's being pursued by a number of NMH grantees, including Amit Etkin, through a company, Alto Pharmaceuticals, which is probably presenting here in some other sessions, that use machine learning to try to ask, if you took EEGs from a lot of people with depression and treated them with sertraline, can you build a machine learning model that predicts an individual's improvement in depression scores based off of that EEG? From the graph in the middle there, you can see that this model predicts reasonably well the degree of improvement in depression for these individuals on sertraline, as well as, I think, another treatment. This is the same problem as the previous study, right? So folks on the right-hand side of the graph, with one sort of part of that EEG signature, are more likely to have a bigger response, whereas people on the left side, a smaller response, we don't know if they're gonna respond better or worse to another one. So Amit and his group took a look at a separate dataset of people not treated with sertraline, but treated with the more traditional rTMS to the dorsolateral prefrontal cortex, and showed that those who were predicted to have the biggest response to sertraline, here in this graph, did not improve that well with TMS, whereas those that were predicted to have the smallest response to sertraline did improve with TMS. So this is one indication, this is all retrospective data, it's not designed for this purpose, but it's one suggestion that these kinds of biomarkers can be used to differentially predict treatment, so that one could imagine you getting an EEG scan for your patients, which is relatively inexpensive, and can even be done portably, although I don't know that the machine learning would work in that system yet, and help your patient decide whether they're more likely to respond, in this case to an SSRI, as compared to transcranial magnetic stimulation. So we'd like to take these early phase studies that are suggestive of differential productivity, and really move them into a place where they can be used in the everyday clinic. And so the NIMH has developed a series of initiatives that we're calling an innovation funnel, that will attempt to parse the heterogeneity of depression using these existing methods that are out there in the literature, that have had small scale studies, or retrospective studies, suggesting they can be predictive, and allow people to then compete by showing us that they can predict these retrospective data, compete for a prospective trial that would eventually lead to, over time, FDA approval for helping us treat our patients with the medicine or therapy that is going to work better for them. So that precision funnel is one part, that, sorry, innovation funnel is one part of our precision psychiatry efforts. The second part is a larger effort to get much, much larger databases with a range of different data, not just one particular biomarker that a group or a company has suggested might work, and across disorders and diagnoses, to find out whether we can do a better job of data-driven clustering. Many of you will recognize this graph that was used to explain RDoC, and the IMPACT program grew out of RDoC, but what's different here is the recognition that in order to make progress, we need truly large data sets that integrate information across a number of different categories for our patients, and importantly, include clinical data, so that we can ask whether these additional sources of data can do a better job predicting clinically useful information. And what do we mean by clinically useful information? I'm not talking about trying to make up new diagnoses or better diagnoses. I'm talking about taking our patient who walks in the door with depression and making some prediction, yes, about what treatment might work better for them, or whether they are one of the 70% of folks who are gonna have a relapsing, remitting, chronic course of depression, or one of the 30% or so of folks who get one depression, get well, and then stay well for a long period of time. Or any other of the handful of clinical dilemmas that you have. The mainstay of this program is going to be developing a data infrastructure that allows these multimodal data sets to be combined with clinical records. Also, these individuals who are contributing their data will be recontactable, so that we can send out inexpensive modalities of testing them, like behavioral tests to them, on a very large scale. We're talking not of hundreds of individuals, not of thousands of individuals, but tens of thousands to hundreds of thousands of individuals. And the idea is then we will have, potentially, the power to ask these questions of the data. And most importantly, these data sets will be open and publicly accessible to all qualified researchers, so that we can harness all of the great ideas that we all have to offer. And they will be representative of the population that's in the United States. We just released the first pair of funding opportunities in the IMPACT program. One is focused on identifying and developing behavioral tasks and sending them out to clinical cohorts. And the second is to create a data coordination center that will create the infrastructure that will be publicly available, so that we can all explore these data sets. One of the resources that we hope to use in this effort is the NIH All of Us Research Program. We've already partnered with them on a beta test of a number of behavioral tests that we are sending out to thousands of people. These tests have previously been normed, but we can now norm them in a population that is more representative of the United States. And since the All of Us has genetics, as well as clinical data associated with it, we can use this set of hundreds of thousands of people, which is reasonably well-represented for individuals with mental illness, to begin asking the kinds of questions we hope to get out of IMPACT. This is some of the data showing that it's reasonably representative of individuals with mental illness. These are prevalence of psychiatric diagnoses from electronic health records in the All of Us Research Program, showing that 17% of participants or so have a history of a diagnosis of major depressive disorder, 4.4% bipolar disorder, and surprisingly, 1.5% schizophrenia. I'd like to think one of the reasons why we have this good representation is that we've been working with our advocacy groups, particularly Mental Health America and the National Alliance on Mental Illness, to try to encourage people in those communities to join All of Us. But it's really gratifying to see that we could potentially use this resource to explore mental illness. And as I said, we've already developed tasks and measures that we are sending out to these individuals, these participants, and hope to be able to make those data available to people to study within the coming year. I wanna turn now from near-term to immediate-term research, and I'll close with a description of three different efforts that we have to try to make an impact on mental health services research, on mental health services, sorry, through research. First, I already introduced you to EpiNet, which is a learning healthcare system for early psychosis. And then I'll talk to you about two center mechanisms that we have that bring together interdisciplinary researchers to try to improve treatment delivery in the near-term, the Alacrity Centers, and try to reduce suicide rates, the practice-based suicide prevention research centers. So as you know, serious mental illness in particular is a tremendous burden in the United States, and we need to do a better job delivering therapies that we know work, as well as improving care through emerging health technologies. We also know that the life course of an individual with schizophrenia is not a single linear line, but rather a decline that occurs particularly early on in the illness. And for a long time, we felt like addressing the illness early might be able to achieve better outcomes, and in fact, data shows that if you can intervene with a first episode of psychosis relatively rapidly, you will get better outcomes at least in the first few years of a life after that first episode of psychosis. So NIMH, along with other groups, showed some decade ago or so that a particular package of treatments called coordinated specialty care has the potential to, combined with early delivery of treatment during first episode psychosis, dramatically improve outcomes in individuals with first episode psychosis. And Congress, based upon that data and with the urging of organizations like the APA and NAMI and MHA, set aside a specific portion of the block grant money to fund first episode psychosis clinics throughout the United States. One of the real great achievements, frankly, of NIMH-sponsored research and one for which I can take no credit because it all happened before I got here, there are now over 300 of these clinics throughout the United States treating thousands of individuals each year. It's a tremendous achievement. But we know we need to do better. And one of the ways that we know we need to do better is we need to make sure that these treatment centers are actually delivering effective care that has fidelity to the original model and also to improve upon that model to understand what elements of that models are associated with good outcomes. So a few years ago, we set up a learning healthcare network or series of networks to try to do exactly that. We put out a call for academic organizations to partner with these first episode psychosis clinics and funded eight different networks in different regions of the country, covering rural and urban areas and covering a large diversity of communities, each of which works with those centers to ensure that they're using common outcome measures, both at the patient level and at the treatment delivery level, and collect that data and share that data through a national data coordinating center, which is charged not only with accumulating that data and making it available for researchers, but also analyzing that data and sending that information back to the networks so that the clinics can use that information in real time to understand how are they doing relative to other peer clinics in other networks. What are the things that they are doing well from a fidelity perspective? What are the things that are doing not so well that need improvement? And although this work is only a couple of years old, we're starting to at least see some outcome data reporting. And so far, it looks like the clinics are doing what they're supposed to be doing, improving outcomes. This is just one of several papers, early papers from these EpiNet networks showing in the New York network decreases in hospitalizations, increases in education and employment, increases in global functioning in the year following admission to these first episode psychosis clinics. These data are not controlled because everyone in the clinic is getting coordinated specialty care. But it does suggest the clinics are doing what they're supposed to be doing. They're delivering treatment that is efficacious. And what we really don't have on this slide, but what we want to learn from is the variance here, right? Which clinics are doing better? Which individuals are getting better? What are the variables that subserve those improvements? Now, beyond first episode psychosis, we also wanna make an impact in other areas. Now, we don't have the organized networks of first episode psychosis clinics that are performing uniform service delivery to be able to learn from. So we've taken a more heterogeneous approach in funding the alacrity centers, which are aimed at speeding the translation of research into practice. These research centers require a practice-based research infrastructure. They have to build off of existing clinics that are treating patients in real world settings. They have multidisciplinary research teams, usually involving people in tech outside of the normal sort of mental health research focus. And they have a deployment-focused research approach that is these centers are building tools that are being implemented in the practice-based infrastructure to try to understand not just do these things work, but are we able to use them? We currently support 14 of these centers across the country. I just wanna show you some data coming out of one of those centers that's focused on young adults transitioning to college. It's a pilot randomized controlled trial of a digital intervention that shows reductions over time that are greater in the mobile support tool group than in enhanced usual care. And that are again being implemented in real world practice settings. Finally, I mentioned of course that suicide prevention is a major near-term goal for NIMH. And so we've created something similar to the Alacrity Center's practice-based suicide prevention research centers. The motivation is pretty clear. Suicide rates are going up in the United States. And again, most disturbingly, they're going up higher in blacks and African-Americans and orange and American Indian and Alaska natives in dark, in medium blue, I guess is the title. Like the Alacrity Centers, these suicide prevention research centers aim to speed the translation of research into practice. They are also aimed at addressing disparities in suicide outcomes among individuals who may be at risk. We don't have as many of them yet. We continue, these were launched more recently, but they have significant geographic diversity as well as diversity in the communities that they address. And so we hope that this will build again, a momentum towards implementing suicide prevention practices in a variety of settings. Finally, I just wanna close by noting that NIMH has been at this now for 75 years. And starting this September, we're going to acknowledge and commemorate that anniversary by a series of symposiums, lectures, sessions at scientific meetings, including APA next year, and communication resources that will be focusing on understanding what have we succeeded at in those 75 years and what have we not succeeded at? What are the gaps that remain? One of my main goals in this 75th anniversary celebration is to clarify both to the scientific community and the practicing community, as well as the public at large, the role of mental health research in current mental health care. There is a trope that is oft repeated. Frankly, I see it most repeated by neuroscientists, but it's repeated by a lot of people that we don't know anything about mental illness and that all of our mental illness treatments have arisen by accident. And although it's true that most of our drugs were discovered by accident or by mimicking a drug that was discovered by accident, there are numerous examples, like the one I just gave you about coordinated specialty care, where you can make clear lines from investments in mental health research to improvements in mental health care. And just one more example, of course, yes, we know that antipsychotics and antidepressants were discovered by accident, but only the first one or two. After that, every single other advance required the knowledge of basic science investments to identify things like, oh, it's the D2 receptor. Oh, it's the serotonin reuptake pump that is the target of these drugs that then allowed companies to go out and say, oh, let me get another D2 receptor. So even the Me Too developments that have enabled lots of different drugs that we have with admittedly similar efficacy, but somewhat different side effect profiles to proliferate. So that's just one more example, but we hope to be able to be making a lot of these points in the future. Why, why is it important to do that? Because if we keep saying that investments in mental health research haven't paid off, it doesn't give a lot of incentive for people to make investments in mental health research. Now, I recognize we might differ about which kind of mental health research we might want to prioritize, right? Some will argue that we need to make more investments in fundamental basic research. Others will argue we need to make more investments in the here and now. But if we don't make the point that any of those investments pay off, well, then we can't ask funders to continue to give us dollars to do it. So with that, I'll say, save the date for September 13th will be an in-person and virtual event. The first of our, it's the inaugural event for the 75th anniversary and the first of three symposia that will take place through the years. It will explore key advances in mental health research, learn about current research we're doing, and hear visionaries discuss future innovations. And with that, I will leave it open for questions. Thank you. Thank you so much for the overview. I'm Savita Bhakta. I'm from the UC San Diego Medical School, and I'm a college mental health program director, and this is really exciting. We are doing a lot of work towards providing care and access is a big deal for students with serious mental health illness. So my question is, looking at the Alacrity Center as well as the suicide prevention centers, how do one of the clinics or how do we get onto this or apply for this to be a center? And what could be the RFAs or what should we be looking at? So both of those centers continue to have application deadlines, I think one of them is being re-released again either next year. I'm just looking to see if anyone from that division is here to correct my dates. So typically these centers require, again, an interdisciplinary team of researchers as well as what you have just articulated, you have, which is a practice-based setting in which that research can take place. So what I would suggest is if you're interested and you have some partners on the research side who are interested is to get in touch with anyone in our Division of Services and Intervention Research. Dr. Joel Sherrill is a good place to start. You can look up his email address or you can email me, joshua.gordon at NIH.gov, and I will send you there to get a sense of, you know, we can send you the links to websites that describe the programs and a sense of the requirements for applications. Each of these centers is limited to only one renewal, and our alacrity centers, the first alacrity centers are coming up for renewal now. So we are funding both renewals and new applications. So there's a lot of interest in that area. Some of them already focus in the youth mental health in that transition age. I showed you some data from that, right? Others are in other areas, though, and we're always looking for opportunities to fund new ideas. Okay. So we'll alternate between in-person questions and the virtual questions. You have some spicy questions coming from the virtual community. Always spicier when you don't have to say it in person, right? So we'll start off light. One of the questions spoke about, first, thank you for the presentation. It was very helpful to see the NIMH initiatives. One of the questions touched on what are, can you comment on ways in which rural centers and more community-based centers can participate at these higher-level research, and how can we democratize a little bit more this component of a research oligarchy? So that's a really good question, and I have two different answers to that. One is from an NIMH-centric perspective, and one is from a larger NIH perspective, including other institutes. From the NIMH perspective, I think the best way that we can democratize the research endeavor to include, in particular, clinical practice-based research settings that are in a greater variety of areas is to require that in our announcements. And so we really do ask people to come in with a variety of, as I said, a diversity of clinical populations. And when we make decisions on funding this center versus that center, yes, the quality of the science has to be high, but we always have more good science than we can fund, and so the next thing we look at is the diversity of the approaches. So I showed you the data from OnTrack New York. Importantly, OnTrack New York is not just a New York City-based network of sites. It also includes rural areas and smaller city areas in upstate New York. And so we try to make sure that when we're funding a center or a series of centers or a group of projects, that we include that diversity in the slate of grants that we fund. Now, there's another element of democratization which moves us out of the academic field altogether and into community-based organizations, and that's something we're really taking a hard look at at NIH in general. So one of the programs that I'm involved in is an NIH-wide program called COMPASS, which is, I forget what the acronym starts with, but it's a health disparities-focused approach that it asks community-based organizations to come in with applications, and they have to pair with academics, but they are the primary grant fundee, if you will. They are the primary applicant, and we give the money to the community-based organization and subcontracts to the academic organizations. And they are coordinated by hubs and the data coordination centers that can provide the additional expertise that are necessary to make sure that they have well-designed and well-carried-out, rigorous clinical studies. This is a program that just launched. We are evaluating the first tranche of applications now. Importantly, these organizations, what they have to do is they have to propose an intervention on a structural determinant of health, particularly that's outside of the healthcare system, per se. It could be about healthcare access, but most of it's aimed at things like, you know, can we improve a neighborhood's health through adding green space, or access to fruits and vegetables, or increased exercise programs to look at structural determinants of health and health disparities. And we have the community organization be the lead here because we recognize they know their communities better than the academic organizations. And so this is new for us, and we'll see how that goes, but it is a distinct effort to democratize our research platforms. That's wonderful. First microphone. So I'm in Virginia, and I am part of the coordinated specialty care in Virginia at a CSB. We are about two and a half years in, and I guess what I want to see if you've seen, I think our biggest frustration is when you're training, it's absolutely one of the best programs I've ever been part of because it is. It's like one, two, three. Everything is very laid out for you. This is what we do. This is the process, and it's almost like a no-fail. However, what we are automatic, like what we've fought so far is the clients coming in because either we get clients that are 16, 17, that have a schizophrenia diagnosis because strictly they have psychosis, but as we start to work with them, we find their autism has caused the psychosis, or the trauma has caused the psychosis, and it's not necessarily schizophrenia, and it's like we're back to the drawing board. So then the program's never going to work, and then you have to have awkward conversations with parents, or we have clients that their psychosis has started with smoking weed, and then in mental health, it's usually, you know, you handle the drug use first, then you do the mental health. Well, marijuana is legalized in Virginia, so it is extremely hard to have a conversation that says, you know, we encourage you to stop smoking weed so that we can do, because they say, well, it's legal, and we like it, and this is what we want to do. So, so far, we've not had anything even look successful. We're just like a rotating door in the hospital because of their initial diagnosis. Yeah. So, I just wonder if you've seen any of that. So, I haven't myself, and it sounds tremendously frustrating, like you're trying to apply one set of treatments that's not working for the population that you happen to have. Right. This sounds like a case for more research, like where we need to understand, okay, how do we take care of these folks? Theoretically, CSC was developed agnostic to diagnosis, but I don't know, and this is one thing that we can learn through EpiNet, I don't know to the extent to which it has been shown to be less efficacious in what kinds of people come in with the psychosis they're presenting with, like the two cases you're suggesting, autism or other neurodevelopmental disorders and marijuana-induced psychosis. So, it's a great question. I don't have a good answer for you. Right. Because it is a great program, and I suggest anybody that doesn't have it, I mean, it's well-defined, but it's just the initial, you know, I don't know, like you said, with the autism, it makes it very hard, which came first. Yeah. So, I guess it's, you know, it's part of the challenge in translating any sort of, you know, well-defined, manualized package of programs is then translating that into a precision treatment for an individual, and I don't have answers in those two particular cases, so it sounds like we need some more research in those areas. I agree. Thanks. Back microphone. Debbie Cohen, I think I was a plant for that question, because that's what I wanted to ask about. So, I am a part of UT Austin, EpiNet Texas, and I generally focus on transitioning to adulthood. What I found frustrating with the youth mental health crisis and all the stuff coming out is that, while we've invested greatly in first episode of psychosis, Texas has, we're up to 29 of our 39 mental health centers, we're really all in, but we have that constantly happen. Yeah. So, we'll have centers come and talk to us and say, but what about the rest of our 16 to 29-year-olds? There's no answer. And then, for someone who works in this space, is that we constantly are, like, pulling pennies together to do any of the other services for that age group? So, I'm just curious, like, is there any interest? Because so far, SAMHSA and NAMH hasn't really been interested in that more transdiagnostic youth mental health approach. So, I think we're recognizing that we need similar systems that are more general. We, the, from the care perspective, that's not really my arena per se, but SAMHSA did get nearly a tripling of their budget, and hopefully some of that's going to go towards youth mental health, I would think. To 18 to 24, because at first, this point, nothing goes beyond 18. Yeah. The other answer that I would say is, we've been having discussions with them, as I mentioned, about expanding the learning healthcare model, and that is written into the president's budget, that we have a certain amount of dollars to expand, and the idea is to expand it beyond EpiNet, beyond psychosis, into other areas. So, I would say, if you're operating clinics that, you know, have more general approach to youth mental health and you're interested in partnering with researchers, or your researcher in that area wants to, you know, have those kinds of things, pay attention. I can't promise we're going to get the money, but we hope to develop those programs. You know, there are good examples of that in other countries, where there are, you know, Australia, for example, which is where the CSE model came from, has a more general approach to mental health in youth, and I think we can take those models and explore them. But so far, you know, I'm not aware of any, you know, the dollars that, the dollars went, CSE works so well because the dollars went to SAMHSA with the express requirement that they use an evidence-based approach to first step psychosis. I don't see that same mandate yet in the other dollars that have been since appropriated to Congress. And while you're on the subject of frustrations with the mental health crisis, from my perspective, and I'm sure many of you in this room share it, my frustration with the mental health crisis is everybody thinks it's new since COVID. It's new, it's not. And it's not, it's been going on for at least half a decade, right, if you think about the rising rates of suicide deaths in youth, for example. So, yeah. But thank you. So, since NIMH is taxpayer funded, and as we're seeing more and more for-profit entities and private entities receiving these grants, can you comment a little bit more on what are some of the ways in which we can ensure access in an equitable sense, especially for taxpayers who may not necessarily have the means to access the clinical application of those research? So, let me first address the opening clause. Although I don't have dollars to give you, I guess theoretically it's correct, more and more dollars are going to private organizations, for-profit organizations, but that's only because our budget has gone up, and a certain percentage of our budget is dedicated to small business. And the vast, vast majority of dollars that we spend on research to private organizations, to for-profit organizations, are these small business investments, which represents a small fraction of our overall budget. So, it's a fraction of our budget, it's essentially constant, right? So, it's not really growing. Now, there are lots and lots of private dollars going into mental health research, whether it be by pharmaceutical companies or, you know, the entities that are doing the psychedelic research now, et cetera. That's not taxpayer dollars. What can we do to ensure access, though? Regardless of who's doing the research, there are two important things that we can do to ensure access. One is make sure the research is done in representative populations in the United States, because if we don't include everybody in our research cohorts, then we won't know if a given treatment is effective, or beyond effective, is acceptable or implementable. So, that's one of the reasons why we have these practice-based research settings that we fund, and why we make sure that we fund them in a variety of communities. The second thing that we need to do is cost-effectiveness research on the work that we do. So, you know, many of you are probably familiar with Brexanilone, right? This is the drug which I think is really the first basic science-to-novel drug story that grew clearly out of NIMH-funded work. I've talked about it before. It's also very expensive, right? It's something like $50,000. But there's been a separate independent analysis of the cost-effectiveness performed that suggests it's actually quite cost-effective, and duh, no-brainer, if you can get a woman who has a baby well so they can function, the benefits are just immeasurable. And they didn't even count in that cost-effectiveness the future productivity and reduction in mental illness in the child, right? So that's an example where, yes, it's a very expensive treatment, but if it's covered by Medicaid, if it's covered by private insurance the way it should be for the cost-effectiveness of it, then it would be accessible to people. So we need to do a better job of ensuring that we study the cost-effectiveness of our treatments. And the reason why I say that as opposed to just lowering the cost of our treatments is, you know, yes, lowering the cost of treatment is an important problem for the health care system in general, but let's not, in mental health, be so focused on making sure that our treatments are all cheap, right, when we forget that it's about cost-effectiveness and we are often, in mental health, faced with a lack of understanding of the true benefits of our therapies. Thank you. Hi, my name is Megan Good. I'm a PGY-3 at the University of Louisville. My question is that I'm an early career psychiatrist. I've recently developed an interest in broadening and deepening the research experience I've gained in my training. Does the NIMH have any opportunities for that for someone like me? A lot of different opportunities. Let me just suggest that you visit our training website on nimh.gov and look for training. It details a number of them. In Louisville, there's some really amazing research going on, particularly in substance use disorders and really in applied research there and in systems of care research, but there's also the opportunity to go elsewhere and learn other things if your interests lie elsewhere. So we support a number of different training programs for people to pursue postgraduate training and research. They're both individual fellowships and also institutional fellowships. Institutional fellowships are given to institutions and they pay for trainee salaries and things like that and then the individual ones you can apply for yourself. We also have training opportunities on the NIH campus. So we have fellowships for clinical fellows to come and be involved in the clinical research that takes place at NIMH, as well as research fellowships that allow you to directly engage in the research. And so that would be also available on our website. So lots of different ways that we try to support individuals interested in research. And again, you can also shoot me an email and I'll send you to our training team. And I encourage you not just look at the website, but you know, email our training team program officers. They're really happy to try to help you figure out what it is that you're looking for and how we can help. Thank you so much. This is a little bit germane to one of the questions that was asked earlier is oftentimes real life patients are a lot messier. We expect them to come in these really neatly categorized DSM-5 checklists and they often come in this amalgamated form of what is this? I was curious if you can comment a little bit more on how can we better bridge that gap between the research translations where it's very clean, so to speak, quote unquote, and clinical practice where it's a lot more messy. So yeah, I remember during residency, I know there's a few Columbia folks in the audience, PI-5, which is supposedly, you know, a floor where a lot of depression research goes on. I don't think anyone had lessons before diagnosis in that research floor. So there's a real importance to doing certain kinds of research in purified populations, right? You have to show, for example, that a treatment you're trying works. And if you have too much noise, it's hard to show that it works. But once you've shown that it works, then it's really important to do that follow-up study to show will it work in the real world? And I emphasize one part of the real world during my talk, which was real world practice settings. And the issues there are a little bit different than, well, they include the heterogeneity of the patients, but they're about, you know, how do you train someone to deliver that therapy? How do you make sure it's done with fidelity? Is it going to work in a variety of different, you know, communities and populations? But you bring up, or this question brings up that other piece of it, which does it work in real patients who don't just have one clean diagnosis and nothing else? And so I think that also takes place in these practice research settings, although I didn't mention that. The other thing that I would say is that it's important that when we do the work that we're doing, for example, in precision psychiatry, that we allow that richness into the data set. So we're not asking for cohorts of people who only have major depressive disorder and don't have dysthymia and don't have psychosis and don't have, you know, tobacco use and don't have marijuana use or don't have autism. We want all that variety because maybe it's the folks with depression and autism who are most likely to respond to X therapy. And those who have depression and marijuana use are more likely to respond to Y. Now, the reason why you haven't seen a lot of that in the past is because the more differences, the more heterogeneity you include in your sample, the larger the sample you need. So I'll just point out one, you know, one thing that we've been doing the last bunch of years now actually is funding the Mental Health Research Network, which is a practice-based research network that's run out of the Kaiser's in Northern California and other where around the Northwest. And they are able to do clinical trials at scale with thousands of individuals for relatively cheap, a few bucks a participant. So this is not clinical trials of new drugs. You're not going to do a brand new drug in that setting, but they can look at different things that they do in the electronic health record and, you know, and use that heterogeneity across a large sample to be able to give you answers. And so I think that's the kind of thing that we need to do more and more. In addition to these practice-based research centers that conduct research with that in mind of in real world patients with real world things where you're not excluding anybody who comes in the door. I'll just point out another study, which you all know, right? The STAR-D study, right? Which also included that heterogeneity and it was real world. And it revealed to us what we kind of already knew from practice, right? That our drugs are okay, but they're not that good, right? And that they don't last, right? And that's probably a good reason for that is the heterogeneity that you're incorporating lots of people who wouldn't have been included in those carefully organized trials. That's wonderful. Any other questions? All right. Please join me and thank you, Dr. Gordon, for the presentation. Thank you all for coming.

mental health research

NIMH priorities

psychiatric diseases

youth mental health crisis

precision psychiatry

genetic discoveries

diversity in research

biomarkers

EpiNet initiative

Alacrity Centers