Kosorok leads NIH-sponsored research to improve clinical trials, speed new cancer therapies

 

“Statistical Methods for Cancer Clinical Trials,” is one of the largest grants of its kind to be awarded by the National Cancer Institute. The project is led by three principal investigators: Michael R. Kosorok, PhD, professor and chair of the biostatistics department of the UNC Gillings School of Global Public Health and lead principal investigator on the project; Marie Davidian, PhD, William Neal Reynolds Professor of Statistics and director of the Center for Quantitative Sciences in Biomedicine at NC State; and Stephen L. George, PhD, professor of biostatistics at Duke. The project will support a major collaborative, multidisciplinary effort that takes advantage of the unrivaled concentration of leading statistical and clinical experts across the three institutions and the two highly-rated cancer centers at UNC and Duke. 

The leadership team also includes three co-principal investigators: Joseph G. Ibrahim, PhD, Alumni Distinguished Professor of Biostatistics and director of the Center for Innovative Clinical Trials at UNC; Sin-Ho Jung, PhD, professor of biostatistics at Duke; and Anastasios A. Tsiatis, PhD, Drexel Professor of Statistics at NC State. The principal investigators, co-principal investigators, and project leaders

Jianwen Cai, PhD, professor and associate chair of biostatistics and Danyu Lin, PhD, Dennis Gillings Distinguished Professor of Biostatistics, form the steering committee that will provide overall guidance for the project. In addition to the Department of Biostatistics in the Gillings School of Global Public Health, other departments, schools and centers at UNC with co-investigators on the study, include the Departments of Epidemiology and

 

Statisticians play an integral role in designing trials, analyzing and interpreting the results to determine if they are meaningful, and developing new methods for design and analysis in settings where traditional methods are inappropriate. The project’s statistical researchers will work with its clinical investigators to apply state-of-the-art statistical techniques to address the challenges for trial design and analysis posed by complex clinical endpoints, diagnostic markers, personalized medicine, and sequential courses of treatment in melanoma, breast, colorectal, lung and prostate cancer settings. The goal is to dramatically improve the efficiency of the cancer clinical trial process and ultimately to improve the health and longevity of cancer patients.