Dr. Gregory Adams (CEO and Co-Founder, RAbD Biotech. Director of Biological Research and Therapeutics at Fox Chase)
Dr. Yibing Shan (Senior Scientist of Chemistry and Biology at D. E. Shaw Research)
Dr. Marta Filizola (Associate Professor Structural and Chemical Biology, Mt. Sinai)
Dr. Matthew Robinson (Assistant Professor Fox Chase Cancer Center)
Time: 6:15 PM – 8:30 PM, January 30, 2013 (Thursday)Venue: The NYU-Poly Varick Street Incubator, 137 Varick St, 2nd floor.
The greater New York City area is home to some of the most advanced biologists and computational biologists and is therefore poised to be the epicenter of in silico-based drug design. In this panel discussion, you’ll hear about why this approach is important and how it can be used to overcome some of the challenges facing groups focused on creating meaningful biotherapeutics, approaches used to transition from in silico design to in vivo preclinical studies, successful biotech start-ups using in silico based platforms. Panelists will share their thoughts on how to transform scientific ideas to value-generating intellectual property that can be used to create computational biology-driven biotech companies in New York City. Biotech entrepreneurs, investor community, faculty and postdoctoral fellows are encouraged to attend.
Please RSVP here: http://insilicodesign.eventbrite.com
Space is limited.
About the speakers:
Dr. Gregory Adams is a CEO and Co-Founder of RAbD Biotech. He is an immunologist with over 25 years of experience in developing antibody-based agents for the treatment and detection of cancer. He heads an antibody engineering and development laboratory at the Fox Chase Cancer Center in Philadelphia with a primary focus on developing antibodies and antibody-drug conjugates for the treatment of breast, ovarian and renal cancer. Greg serves as a scientific adviser to a number of biotechnology companies including Endo Pharmaceuticals, Symphogen, Avipep, AvidBiologics and am a member of the Antibody Society's Board of Directors. Greg also serves on the Editorial Boards of Cancer Immunology Research, MAbs and Cancer Biotherapy & Radiopharmaceuticals and recently rotated off of the editorial board of Cancer Research. He is a member of the Integration Panel of the Department of Defense's Breast Cancer Research Program and have served as a member or Ad Hoc reviewer for many other panels including the NCI, American Cancer Society and the California Breast Cancer Research Program.
Dr. Marta Filizola is a dedicated leader in computational biophysics of membrane proteins with over 20 years of experience. She has a special focus on the family of cell surface proteins called G protein-coupled receptors (GPCRs), which are the targets for about half of all currently used drugs. The overall goal of current research programs in Marta’s Laboratory is to obtain rigorous mechanistic insight into the structure, dynamics, and function of important classes of membrane proteins that are prominent drug targets of the human ‘druggable’ genome (e.g., G protein-coupled receptors (GPCRs), integrins, etc.) for the purpose of developing improved therapeutics. Marta is the author of several patents and 80-publications in the field of computational biophysics.
Dr. Mathew Robinson focuses on using antibody-engineering techniques to design antibodies for the purpose of diagnosing or treating cancer. He uses rational computational design methods to build antibodies that match the structure of proteins found on the surface of tumor cells. In this way, he increases the antibodies’ efficacy by improving their ability to selectively target tumor cells.
Dr. Yibing Shan earned a Ph.D. in physics and an M.S. in computer science from Drexel University. His recent research, enabled by long-timescale molecular dynamics simulations, focuses on the investigation of molecular mechanisms that underlies a biomolecule’s function from a perspective of protein structural dynamics and drug discovery, The research is mostly interested in signaling proteins, particularly protein kinases, with a special emphasis placed on close coupling with experimental work in an iterative fashion.
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