Innovations In Clinical Neuroscience

ISCTM Supplement 2015

A peer-reviewed, evidence-based journal for clinicians in the field of neuroscience

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[ V O L U M E 1 2 , N U M B E R 3 – 4 , S U P P L E M E N T A , M A R C H – A P R I L 2 0 1 5 ] Innovations in CLINICAL NEUROSCIENCE 19S trials of molecules engaging promising new targets using the FAST-FAIL methodology described earlier and working within the RDoC framework. T hese networks represent unique NIMH, private, and academic partnerships are meant to 1) provide a path for promising compounds that are currently not being developed, 2) establish a new standard for early phase drug development that will improve the cost/benefit of CNS drug development and re-kindle pharma interest, and 3) improve our understanding of mechanisms of psychopathology, treatments to psychiatric disorders, and optimal trial methodologies. The NIMH has recently awarded grants in three areas: 1) Mood and Anxiety Spectrum Disorders (FAST-MAS; a grant awarded to Duke; PI - Krystal), 2) Psychotic Spectrum Disorders (FAST-PS; grant awarded to Columbia; PI – Lieberman), and 3) Autism Spectrum Disorders (FAST- AS; grant awarded to UCLA – PI - McCraken). These efforts involve a number of steps including choosing a neurobiologic target that is promising but yet to be fully evaluated; finding a molecule that engages that target; determining a dose of the molecule that robustly engages that target; identify an appropriate RDoC construct relevant to the target of interest; select outcome measures that reflect that construct and that will allow an assessment of whether engaging the target achieves the desired effect on the brain; identifying the relevant patient population and determining how they will be selected; and estimating the number of subjects needed for the trial. Perhaps the most important step is selecting the target to study. This has involved working with a committee including NIMH program offices and consultants to identify the most promising targets to study and how to study them. Once this has been achieved, the next key step is to design trials based on the principles outlined earlier to optimize the capacity to make a definitive go/no-go decision at the end of Phase IIa. It should be emphasized that go/no-go decisions will be made based on whether engaging the target achieves a hypothesized effect, such as achieving a change in a particular brain c ircuit, and not on whether there is a significant effect on a clinical scale. If the drug does not engage the circuitry it would not make sense to move forward even if there is a therapeutic effect on a clinical or self-report endpoint. This would be another likely set up for a failed Phase III trial. Qualification process for the FAST-MAS target selection process. First, there should be promising preclinical/clinical data that indicate the potential of a given target. There also has to be available means of assessing target engagement, and an available molecule for testing the target hypothesis. The drug must also be far along enough that an Investigational New Drug application (IND) exists or it is IND-ready, as time is limited. The molecule must not be too far along in development such that the promise of the target (or lack thereof) has already been established or such that trials are being carried out that are redundant with likely FAST- MAS trials. Furthermore, a target must have an associated molecule that does not have prohibitive adverse effects or a problematic toxicological profile. In terms of being able to assess target engagement, it is necessary to have means to determine the degree to which a given dose engages the pharmacologic target of interest (e.g. antagonism of the 5HT 2A receptor). It is also necessary to have means to test whether engaging the target has the hypothesized effect (e.g., achieves a change in a brain circuit or an objectively measureable aspect of behavior). Process of target selection. As part of the FAST-MAS effort, an exhaustive search was carried out that led to identifying a target of interest where there was a molecule available that engaged that target and that was at an appropriate point in development. Means of establishing a dose that robustly engages the target with PET was an an important factor in choosing the molecule to study. The same was true for having means of establishing POC in terms of an effect on brain circuits. In the case of FAST-MAS, where we a re studying a molecule that is believed to affect reward function, the relevant test of whether there is an effect on the brain is a determination of whether treatment affects reward- related circuitry. Choice of RDoC constructs(s) challenge. The first question that one needs to ask is "Where in RDoC is the functional domain that I want to study?" For instance, our interest was in studying the inability to experience pleasure, referred to as anhedonia (a core symptom of major depression), which cuts across traditional diagnoses as anhedonia is also seen in those with anxiety disorders and schizophrenia. As a result, we sought to identify RDoC constructs related to anhedonia and identify the associated circuitry, behavior test, and clinical scales to employ. The relevant RDoC domain for anhedonia is Positive Valence Systems. There are a number of relevant RDoC constructs related to reward, such as Reward Valuation, Expending Effort for Reward, Reward Prediction/Expectancy, Reward Responsibility, and Effect of Reward on Learning. These constructs reflect current best understanding of relevant neurobiology and tools for assessment of outcomes. A number of the relevant circuits and measures overlap to a degree across constructs of interest. We chose to employ task-related fMRI using the monetary incentive delay task to determine whether engaging our target had the hypothesized effect on neural circuitry (increase in ventral striatal activity) as a means of establishing proof of concept. This task is known to change in response to antidepressant treatment in depressed subjects. Outcomes are reverse of traditional approach. A circuit measure serves as the primary outcome measure for our study. Key secondary measures are behavioral intermediate phenotype assessments (more closely linked to neural circuitry than clinical outcome, but also linked

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