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J Am Coll Cardiol, 2007; 50:738-740, doi:10.1016/j.jacc.2007.04.067
(Published online 6 August 2007). © 2007 by the American College of Cardiology Foundation |
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Division of Cardiovascular and Renal Products, Office of New Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland.
Manuscript received April 5, 2007; revised manuscript received April 18, 2007, accepted April 24, 2007.
* Reprint requests and correspondence: Dr. Ellis F. Unger, HFD 110, Building 22, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993. (Email: ellis.unger{at}fda.hhs.gov).
It is not unusual for novel treatment strategies to fail in clinical trials, despite highly encouraging results in preclinical proof-of-concept studies. Typically, such "failures of translation" are blamed on the poor predictiveness of animal models. Often, however, the poor predictiveness of todays preclinical proof-of-concept studies is related not to limitations of the models but to investigator bias and a lack of scientific rigor. The resulting false-positive results only serve to mislead the field and impede medical progress. With the resurgence of translational research, it is useful to examine some of the problems that plague these studies and consider their solutions. With thoughtful planning, execution, and analysis, it is possible to generate reliable and predictive data from preclinical proof-of-concept studies, results that should more rapidly advance medical progress.
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