Dr. Richard Simon
Associate Director, Division of Cancer Treatment and Diagnosis
Director, Biometric Research Program
Chief, Computational & Systems Biology Branch
Richard Simon, D.Sc., leads the Biometric Research Program and is chief of the Computational & Systems Biology Branch. He holds a doctoral degree in Applied Mathematics & Computer Science from Washington University in St. Louis Mo. He has developed many of the statistical methods used in cancer clinical trials including dynamically stratified randomization, optimal 2 stage phase 2 clinical trial designs, accelerated titration phase 1 designs, stochastic curtailment for futility monitoring, tests of qualitative treatment by covariate interactions, predictive biomarker based enrichment designs, adaptive biomarker driven clinical trial designs and Bayesian methods for subset analysis, factorial clinical trials, and active control clinical trials. Dr. Simon is a leader in the development and use of predictive biomarkers in therapeutic research.
In 1998 Dr. Simon established a multidisciplinary group of statistical, computational and biological scientists to develop and apply methods for the application of high-dimensional genomic data to cancer research. This group expanded over the years and became the Computational & Systems Biology Branch. Dr. Simon has received laboratory training in genomics and cell biology at Cold Spring Harbor Laboratory and at the NIH FAES. Dr, Simon has published many papers on the analysis of genomic data and has trained many postdoctoral fellows in computational and statistical cancer genomics. Dr. Simon is the architect of software that empowers biologists and pharmacologists to analyze and interpret genome-wide data including BRB-ArrayTools and the Translational Pharmacology Workbench. BRB ArrayTools has over 15,000 registered users in 65 countries and has been cited in over 2000 publications.
Dr. Simon is an elected fellow of the American Statistical Association and a former member of the FDA Oncologic Drug Advisory Committee. He received the 2013 Karl Peace Award from the American Statistical Association for "outstanding statistical contributions for the benefit of society".
I am interested in using genome-wide technologies to understand the earliest steps of oncogenesis; to identify the cell type of origin of human tumors and the founder somatic genomic alterations which drive tumor evolution and generate genomic heterogeneity. I am also interested in using genome-wide data to better understand drug and immune cell interactions with tumors and the strategies that tumors use to survive such interventions. I am interested in creating a tightly integrated team of cancer biologists, computational biologists and informaticists to develop novel strategies for using state-of-the-art biotechnology to better understand tumor invasion and to devise more effective treatment strategies. Finally, I am interested in developing novel clinical trial designs which enhance progress in developing more effective treatments.
Simon R, Paik S, Hayes DH. Use of archived specimens in evaluation of prognostic and predictive biomarkers. Journal of the National Cancer Institute 101(21):1-7, 2009.
Freidlin B, Jiang W, Simon R. The cross-validated adaptive signature design. Clinical Cancer Research 16:691-8, 2010.
Subramanian J, Simon R. Gene expression-based prognostic signatures in lung cancer: Ready for clinical use? Journal of the National Cancer Institute 102:464-74, 2010.
Subramanian J, Simon R. An evaluation of resampling methods for assessment of survival risk prediction in high dimensional settings. Statistics in Medicine 30(6):642-53, 2011.
Youn A, Simon R. Identifying cancer driver genes in tumor genome sequencing studies. Bioinformatics 27(2):175-81, 2011.
Simon, RM, Subramanian J, Li MC, Menezes S. Using cross validation to evaluate prediction accuracy of survival risk classifiers based on high dimensional data. Briefings in Bioinformatics 12(3):203-214, 2011.
Karuri SW, Simon R. A two-stage Bayesian design for co-development of new drugs and companion diagnostics. Statistics in Medicine 31:901-14, 2012.
Matsui S, Simon R, Qu P, Shaughnessy JD, Barlogie B & Crowley J. Developing and validating continuous genomic signatures in randomized clinical trials for predictive medicine, Clinical Cancer Research 18:6065-6073.
Youn A, Simon R. Estimating the order of mutations during tumorigenesis from genome sequencing data. Bioinformatics 28 (12): 1555-61, 2012.
Hong F, Simon R. The run-in phase III trial design with post-treatment predictive biomarkers. Journal of the National Cancer Institute 106:1628-33, 2013.
Simon N, Simon R. Adaptive enrichment designs for clinical trials. Biostatistics, doi:10.1093/biostatistics/kxt010, published online March 21, 2013.
Simon R, Polley E. Clinical trials for precision oncology using next generation sequencing. Personalized Medicine 10:485-95, 2013.
Youn A, Simon R. Using passenger mutations to estimate the timing of driver mutations and identify mutator alterations. BMC Bioinformatics 2013, 14:363
Simon R, Roychowdhury S. Implementing personalized cancer genomics in clinical trials. Nature Reviews Drug Discovery 12:358-69, 2013.
Kim KI, Simon R. Using single cell sequencing data to model the evolutionary history of a tumor. BMC Bioinformatics 15:27, January 2014.
Simon R, Blumenthal G, Rothenberg ML, Sommer J, Roberts SA, Armstrong DK, LaVange LM, Pazdur R. The role of non-randomized trials in the evaluation of oncology drugs. Clinical Pharmacology & Therapeutics 97(5): 502-7, 2015.
Zhao Y, Polley E, Li MC, Lih CJ, Palmisano A, Sims D, Rubinstein L, Conley B, Chen A, Williams PM, Kummar S, Doroshow J, Simon R. GeneMed: An informatics hub for coordinating next-generation sequencingstudies that support precision oncology studies. Cancer Informatics 14(Suppl 2):45-55, 2015.
Simon R. Sensitivity, specificity, ppv and npv for predictive biomarkers. Journal of the National Cancer Institute 107(8)L 153-6, 2015.
Simon R, Geyer S, Subramanian J, Roychowdhury S. The Bayesian basket design for genomic variant driven phase II trials. Seminars in Oncology 43:13-18, 2016.
Simon R. Genomic driven clinical trials in oncology. Annals of Internal Medicine 116:270-8, 2016.
Palmisano A, Zhao Y, Li MC, Polley E, Simon RM. OpenGeneMed: A portable, flexible and customizable informatics hub for the coordination of next-generation sequencing studies in support of precision medicine trials. Briefings in Bioinformatics (In press)
Simon R, Korn E, McShane L, Radmacher M, Wright G, Zhao Y. Design and Analysis of DNA Microarray Investigations, Springer-Verlag New York, 2003.
Simon R. Genomic Clinical Trials and Predictive Medicine, Cambridge University Press, 2013.
Matsui S, Simon R, Buyse M. Design and Analysis of Clinical Trials for Predictive Medicine, Taylor and Francis Publisher, 2015