Abstract:
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Tuberculosis remains a serious global health problem, afflicting an estimated 9 million people in 2013 and causing approximately 1.5 million deaths. Better regimens requiring shorter treatment durations are critically needed to curb this pandemic. The drug pipeline is now producing candidate therapies, after a 30-year period of quiescence. The standard clinical trials paradigm, however, is widely viewed as being too slow to address the crisis. Statistical science has the potential to improve the speed of drug development, through design of more informative and efficient phase 2 and 3 trials. In this talk, I will describe the needs from the perspective of a clinical trialist and propose solutions provided from the field of statistics. Statistical contributions are wide ranging and include high-dimensional image processing to provide better phase 2 endpoints, novel study designs to guide more rational combinations of drugs, and sensibly adaptive study designs.
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