Richard Simon, Ph.D., is Chief of the Biometric Research Branch in the Division of Cancer Treatment and Diagnosis. Dr. Simon holds a doctoral degree in applied mathematics and computer science from Washington University in St. Louis, MO. He has been at the National Institutes of Health (NIH) since 1969 and has developed many of the statistical methods used today in cancer clinical trials, including dynamically stratified randomization, optimal two-stage phase 2 designs, accelerated titration phase 1 designs, stochastic curtailment for futility monitoring, tests of qualitative treatment by patient covariate interactions, Bayesian subset analysis, and Bayesian designs for therapeutic equivalence (active control) trials. He has published more than 400 papers on the application of biostatistical methodology to biomedical research.
Dr. Simon is an elected member of the American Statistical Association, a member of the National Research Council Committee on Theoretical and Applied Statistics, and a former member of the Oncologic Drug Advisory Committee of the U.S. Food and Drug Administration (FDA). He is a pioneer in the use of data monitoring committees for cancer clinical trials.
In 1998, Dr. Simon established a multidisciplinary group of statistical, mathematical, computational, physical, and biological scientists to develop and apply methods for the application of genomic, gene expression, and other molecular data to cancer research. His group has developed expertise in the analysis of DNA microarray gene expression data; new methods for the planning and analysis of DNA microarray studies; and integrated software (BRB-ArrayTools) for the analysis of microarray data, with more than 13,000 registered users in 65 countries (http://linus.nci.nih.gov/ BRB-ArrayTools). BRB-ArrayTools has been cited in more than 1700 publications and won a prestigious Award for Excellence in Technology Transfer from the Federal Laboratory Consortium for Technology Transfer in 2012.
Dr. Simon is the lead author of Design and Analysis of DNA Microarray Investigations, published by Springer. His group is also involved in development of methods for elucidating T-cell receptor binding rules based on combinatorial peptide library data, design of peptide vaccines, and development of models of oncogenesis for use in deep analysis of clinical trial results.