For almost 20 years, Dr. William Kim has been leveraging the power of machine learning with functional genomics approaches to contribute to a deeper understanding of cellular circuitry underlying cancer initiation, maintenance, and progression. He has helped pioneer several novel computational framework to better functionally characterize cancers to identify appropriate therapeutic strategies towards realizing precision cancer medicine. He is currently the co-leader of a California Initiate to Advance Precision Medicine (CIAPM) Project sponsored by the State of California Office of Governor’s Planning and Research which aims to target Triple-Negative Breast Cancers to help reduce health disparities.
Keith Yamamoto, UCSF
Patient-centric data – Real-World Evidence (RWE) and Real-World Data (RWD) - is becoming instrumental in the drug development process and for health care decisions in general. This data is not only informative for the process from discovery to new indications, clinical trial design, and drug development, it also can be of value to monitor post-marketing drug safety and for decision support in clinical practice. As the data becomes a decision driver, science companies and medical organizations are increasingly focused on leveraging RWD and RWE to not only better understand the patient populations using their drugs and the respective outcomes, but also to accelerate clinical decision support. This session will focus on the various aspects of integrating RWE and RWD to support drug development and clinical decision support