A peer-reviewed, evidence-based journal for clinicians in the field of neuroscience
Issue link: https://innovationscns.epubxp.com/i/499434
[ 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 29S needed for cell growth. In about 30 percent of breast cancers, the Her-2 gene is over-expressed. Trastuzumab is an antibody that blocks this cell s urface receptor. There is a kit available for identifying this subgroup of breast cancer patients. During the development of trastuzumab, the clinical trials included mostly over- expressing patients. This led to a labeled indication only for over- expressing patients. A well-known example from the central nervous system (CNS) pharmacopoeia involves the prediction of a serious safety outcome for the drug carbamazepine—Stevens-Johnson Syndrome (SJS), a serious skin reaction. Example for the utilization of biomarkers in early clinical development. Biomarkers may also be useful for increasing the efficiency in earlier phases of drug development. One approach comes from the National Institute of Mental Health (NIMH) programs Fast-Fail [FAST] and RDoC [http://www.nimh.nih.gov/research- priorities/research-initiatives/fast-fast- fail-trials.shtml]. This is a study being conducted in the FAST-Mood and Anxiety Spectrum Disorders (MAS) program, with Andrew Krystal at Duke University Medical Center as lead investigator. This represents a fundamental change in the proof of concept (POC) paradigm and a move away from DSM toward RDoC constructs. The focus is on demonstrating target engagement as the primary goal of this POC. The aim is not only to quickly identify compounds that merit more extensive testing, but also to identify targets in the brain for the development of additional candidate compounds. FAST will aim at answering the following questions: • Does the compound engage a target in the brain, for example, does it interact with a specific receptor in brain cells or alter signaling in the brain by a specific neurotransmitter? • Does it measurably alter a feature of brain function (e.g., change the results of a test of memory, cognition, or attention)? Unlike standard clinical drug-testing trials, clinical trials in FAST are small (about 10–30 subjects), and will be in human patients. Years of experience in drug testing suggests that positive results in animals do not necessarily translate to humans. With this type of testing, compounds that are found to engage a target in the brain, and alter an indicator (or biomarker) of brain function can quickly go forward to further testing. Negative results will avoid costly and time-consuming testing, and also provide information that will be helpful in designing future trials. The identification of new targets in the brain identified through this approach will broaden the avenues available for development and screening of new candidate compounds. The following summarizes the general approach for planning such a study. First, identify a compound of interest. Then identify a brain target (circuit) thought to be engaged by that compound (target engagement [TE]). Subsequently, identify a biomarker that signals TE. And finally, identify a behavioral construct (preferably RDoC) thought to be represented by the brain target. This approach has now been applied in a program targeting the RDoC construct anhedonia. A compound has been identified. The ventral striatum (VS) has been determined to be the circuit of interest (in particular, activation by a monetary incentive delay task in VS). Functional magnetic resonance imaging (fMRI) has been selected as a biomarker for VS activation. As noted, anhedonia is the RDoC construct that has been targeted. The Snaith- Hamilton Pleasure Scale (SHAPS) is being used as a specific behavioral measure for anhedonia. Patients are selected based on their threshold SHAPS scores. Patients could present with either major depressive disorder (MDD) or general anxiety disorder (GAD) (i.e., this program cuts across DSM categories). The Hamilton Rating Scale for Depression (HAM-D) and Hamilton Rating Scale for Anxiety (HAM-A) are also measured, but fMRI is the primary outcome. Regulatory challenges: pseudospecificity. There are fundamental regulatory challenges to endorsing an alternative to the DSM classification of psychiatric illness. It is necessary to provide a rationale for an alternative approach. This is true whether dealing with a phenomenological domain, a biomarker-defined subgroup or an RDoC construct. The key regulatory issue is pseudospecificity. For a regulatory agency, in particular FDA, a claim is considered pseudospecific if it is viewed as artificially narrow. One example might be a demographic subgroup (e.g., depression in women or in the elderly). Another example might be a symptom, or symptom FIGURE 1. Two ways for biomarker to subdivide the population (assume marker: M+/M-)