Ph.D., CEO, Genialis, Inc.
Rafael leads Genialis’ effort to integrate and mine vast and diverse sources of biomedical knowledge to realize the promise of precision medicine and therapeutic discovery. He spent nearly 20 years in biomedical research prior to Genialis, publishing on the evolution of innate immune systems, bioengineering of microbes, and genetics of development. He has also nurtured a specialty in developing software for high-throughput molecular design and analyses, co-inventing the j5 DNA assembly design automation tool (which has since been commercialized by TeselaGen Biotechnology). Rafael attended Dartmouth College and then Yale University, where he was an NSF Graduate Research Fellow. He went on to postdoctoral training in Jay Keasling’s synthetic biology group at Lawrence Berkeley National Laboratory, Joint BioEnergy Institute (JBEI), followed by a National Library of Medicine fellowship in Biomedical Informatics at Baylor College of Medicine.
AI and Data Science Showcase: Genialis, Inc.
Genialis innovates at the nexus of biomedical data, machine learning, and expert engagement to accelerate precision therapies from the lab to patient.
Machine Learning To Predict Outcomes In Immunotherapy
Immunotherapies constitute half of all cancer drugs in R&D. These work miracles… when they work at all. Response rates remain unacceptably low. We apply machine learning to identify biomarkers of desired response, and predict better combinations and application areas.