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个人简介
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".
Research Interests
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.
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".
Research Interests
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.
研究兴趣
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SURGERYno. 3 (2024): 710-711
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Plage H., Hofbauer S., Furlano K., Roßner F., Schallenberg S., Elezkurtaj S., Kluth M., Lennartz M., Marx A.H., Samtleben H., Fisch M., Rink M.,
European Urology (2024): S1346
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Marian Grade, Patrick Hörmann, Sandra Becker,Amanda B. Hummon,Danny Wangsa,Sudhir Varma,Richard Simon,Torsten Liersch,Heinz Becker,Michael J. Difilippantonio,B. Michael Ghadimi,Thomas Ried
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Jeffrey Melson Clarke,Tom Stinchcombe,Lin Gu,Hirva Mamdani,Scott Joseph Antonia,George R. Simon,Guru P. Sonpavde,Neal E. Ready,Jeffrey Crawford, Michael Campa,Elizabeth Gottlin, Ryan Bushey,
JOURNAL OF CLINICAL ONCOLOGYno. 16 (2023)
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Chiharu Sako, Petr Jordan, Ross McCall,Arpan Patel,Dwight Hall Owen,Arya Amini,An Liu,Brendan D. Curti,Roshanthi K. Weerasinghe,Soohee Lee,Ray D. Page,Aurelie Swalduz,
JOURNAL OF CLINICAL ONCOLOGYno. 16 (2023)
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