Robert Beckman, M.D. is currently Professor of Oncology and of Biostatistics, Bioinformatics, and Biomathematics at Georgetown University Medical Center. Dr. Beckman is an oncology clinical researcher and mathematical biologist, whose goals are to develop cancer therapies and to improve the way cancer therapies are developed and deployed in patients, with emphasis on personalized medicine, tumor heterogeneity, and tumor evolution.
He has played significant leadership roles in the development of new oncology clinical research groups at SmithKline Beecham (now Glaxo SmithKline), Centocor, Inc. (a Johnson and Johnson Company), Merck Research Laboratories, and Daiichi Sankyo Pharmaceutical Development and in 5 cross-company collaborations (SmithKline Beecham with Immunogen and with Aradigm, Centocor with Alza, Merck with Ariad, and Daiichi Sankyo with Amgen). His clinical research career spans small molecule and macromolecular therapeutics and supportive care agents targeting repair, angiogenesis, signal transduction, and developmental pathways, as well as novel technology platforms such as DNA vaccines, antibody-drug conjugates, and immunoliposomes. He has brought 23 molecules into early clinical development, 5 into late clinical development (monoclonal antibodies targeting her3, death receptor 5, insulin-like growth factor receptor, alpha-v integrins, and interleukin-6), and 2 to market (Hycamtin® for small cell lung cancer, and Astra Zeneca’s Casodex® for adjuvant therapy of prostate cancer), and pioneered a post-approval clinical research program for Hycamtin® in pediatric cancers, one of the first of its kind.
Together with colleagues at Merck Research Laboratories, Dr. Beckman has invented novel clinical strategies for proof of concept studies and for early and late biomarker driven clinical development. He currently leads an international group of government, industry, and academic statisticians at the Drug Information Association (DIA), working on clinical trial designs for small populations, including biomarker defined subsets. At Merck, he also led an interdisciplinary group to facilitate molecular and clinical data flow from Moffitt Cancer Center to Merck, in turn enabling correlation of clinical outcomes with biomarkers.
In addition, Dr. Beckman studies cancer evolution and its impact on optimization of therapeutic strategies, and this will be his major focus going forward. These mathematical biology studies have led to the concept of efficiency of carcinogenesis as a way of evaluating cancer evolutionary pathways, which in 2006 predicted some of the results observed in subsequent experimental efforts from the TCGA program, the Sanger Institute, and others. Recently, this work inspired the invention of nonstandard strategies for personalized cancer therapy which explicitly consider intra-tumor heterogeneity and evolutionary dynamics, and hold promise for substantial improvement in clinical outcomes.
Educated at Harvard College and Harvard Medical School, Dr. Beckman did his clinical training in Pediatrics at Stanford University and Pediatric Hematology/Oncology at the University of Michigan, and postdoctoral work in nucleic acid and protein biophysics at Fox Chase Cancer Center (on a National Cancer Institute Physician Scientist Award) and the Bristol Myers Squibb Pharmaceutical Research Institute. He has served on the University of Michigan Biophysics faculty, and was a Member and Visiting Scientist in the Simons Center for Systems Biology, Institute for Advanced Study, Princeton, in the Biomolecular Structure and Drug Design group at Warner Lambert/Parke Davis Pharmaceuticals, and in the Cancer Biomarkers Steering Committee of the Foundation for the National Institutes of Health. His versatile publication record, comprising approximately 170 articles and abstracts, ranges from computational chemistry to clinical oncology, emphasizing quantitative approaches.
To view a complete list of his publications, click here.
Departments of Oncology and of Biostatistics, Bioinformatics, and Biomathematics
Lombardi Comprehensive Cancer Center
Impact of genetic dynamics and single-cell heterogeneity on development of nonstandard personalized medicine strategies for cancer; RA Beckman, GS Schemmann, CH Yeang; Proceedings of the National Academy of Sciences 109 (36), 14586-14591, 2012
Integrating predictive biomarkers and classifiers into oncology clinical development programmes; RA Beckman, J Clark, C Chen; Nature Reviews Drug Discovery 10 (10), 735-748, 2011
Efficiency of carcinogenesis with and without a mutator mutation; RA Beckman, LA Loeb; Proceedings of the National Academy of Sciences 103 (38), 14140-14145, 2006