The history and current state of antidepressant clinical trial design: a call to action for proof-of-concept studies.
Conference Paper
Overview
abstract
BACKGROUND: The development of new antidepressant drugs has reached a plateau. There is an unmet need for faster, better, and safer medications, but as placebo-response rates rise, effect sizes shrink, and more studies fail or are negative, pharmaceutical companies are increasingly reluctant to invest in new drug development because of the risk of failure. In the absence of an identifiable human pathophysiology that can be modeled in preclinical studies, the principal point of leverage to move beyond the present dilemma may be improving the information gleaned from well-designed proof-of-concept (POC) studies of new antidepressant drugs with novel central nervous system effects. With this in mind, a group of experts was convened under the auspices of the University of Arizona Department of Psychiatry and Best Practice Project Management, Inc. PARTICIPANTS: Forty-five experts in the study of antidepressant drugs from academia, government (U.S. Food and Drug Administration and National Institute of Mental Health), and industry participated. EVIDENCE/CONSENSUS PROCESS: In order to define the state of clinical trials methodology in the antidepressant area, and to chart a way forward, a 2-day consensus conference was held June 21-22, 2007, in Bethesda, Md., at which careful reviews of the literature were presented for discussion. Following the presentations, participants were divided into 3 workgroups and asked to address a series of separate questions related to methodology in POC studies. The goals were to review the history of antidepressant drug trials, discuss ways to improve study design and data analysis, and plan more informative POC studies. CONCLUSIONS: The participants concluded that the federal government, academic centers, and the pharmaceutical industry need to collaborate on establishing a network of sites at which small, POC studies can be conducted and resulting data can be shared. New technologies to analyze and measure the major affective, cognitive, and behavioral components of depression in relationship to potential biomarkers of response should be incorporated. Standard assessment instruments should be employed across studies to allow for future meta-analyses, but new instruments should be developed to differentiate subtypes and symptom clusters within the disorder that might respond differently to treatment. Better early-stage POC studies are needed and should be able to amplify the signal strength of drug efficacy and enhance the quality of information in clinical trials of new medications with novel pharmacologic profiles.
