Fri, Feb 25, 2022, 09:00 – 10:00AM (PDT), 12:00 – 1:00PM (EST)
The application of established drug compounds to new therapeutic indications, known as drug repositioning, offers several advantages over traditional drug development, including reduced development costs and shorter paths to approval. The development and availability of large-scale genomic, transcriptomic, and other molecular profiling technologies and publicly available databases, in combination with the deployment of the network concept of drug targets and the power of phenotypic screening, provide an unprecedented opportunity to advance rational drug repositioning based on the ability of single or multiple therapeutic agents to perturb entire molecular networks away from disease states in cell-based and animal models. We have previously developed a systematic computational approach to predict novel therapeutic indications on the basis of comprehensive testing of molecular signatures in drug-disease pairs and have leveraged real world data to in-silico validate the predictions. The computational method provides a systematic approach for repositioning established drugs to treat a wide range of human diseases including IBD, preterm birth, Alzheimer’s disease and most recently COVID-19. In this talk, I will discuss the computational methods that we have developed and applied across extensive molecular datasets in order to speed up the process of drug discovery as well as touch on new clinical datasets that we are incorporating into the pipeline.
Marina Sirota, PhD
Associate Professor, Bakar Computational Health Sciences Institute, UCSF
Marina is currently an Associate Professor at the Bakar Computational Health Sciences Institute at UCSF. Prior to that she has worked as a Senior Research Scientist at Pfizer where she focused on developing Precision Medicine strategies in drug discovery. She completed her PhD in Biomedical Informatics at Stanford University. Dr. Sirota’s research experience in translational bioinformatics spans over 10 years during which she has co-authored over 100 scientific publications. Her research interests lie in developing computational integrative methods and applying these approaches in the context of disease diagnostics and therapeutics with a special focus on studying the role of the immune system in disease. The Sirota laboratory is funded by NIA, NLM, NIAMS, Pfizer, March of Dimes and the Burroughs Wellcome Fund. As a young leader in the field, she has been awarded the AMIA Young Investigator Award in 2017. Dr. Sirota also is the director of the AI4ALL program at UCSF, with the goal of introducing high school girls to applications of AI and machine learning in biomedicine and serves as the director of outreach and advocacy at the Bakar Computational Health Sciences Institute.