Associate Principal Scientist
Merck & Co. Inc
Disclosure: Merck & Co. (Employee)
Youfang Cao, PhD, is an Associate Principal Scientist at Quantitative Pharmacology & Pharmacometrics (QP2), Pharmacokinetics, Pharmacodynamics, and Drug Metabolism (PPDM) at Merck & Co. Youfang is a pharmacometrician with a background trainings in mathematics and computational sciences and strong expertise in algorithm design and system development using multiple programming languages. Youfang is currently leading an effort to build the capability of using modern AI/ML technology to help pharmacometrics data analysis and mechanistic modeling. After joined Merck in 2018, he has successfully led the development of multiple mechanistic Immune-Viral Dynamics Modeling (IVDM) platforms to integrate data from pre-clinical and clinical studies and inform drug development for multiple antiviral and oncology programs across early to late stages. His strong expertise in QSP modeling work have impacted drug discovery and development across therapeutic areas and stages of development from discovery to late development through simulations of clinical outcomes. Youfang holds a B.S. in Computational Mathematics, and M.S. in Biochemistry and Molecular Biology. He received a PhD in Biomedical Engineering from Shanghai Jiao Tong University in 2011. Before joining Merck, Youfang was a Research Assistant Professor at the University of Illinois at Chicago, and a postdoc in Theoretical Biology and Biophysics at the Los Alamos National Laboratory, during which he has developed innovative mathematical and computational biology modeling and simulation approaches to study the stochasticity and multiscale behavior in gene regulation networks and biochemical reaction systems. Youfang has deep experiences in model informed drug development, and he has published over 45 co-authored publication in peer-reviewed journals as well as book chapters and being invited to give oral presentations in multiple academic and industry conferences. Youfang is passionate about developing and applying novel AI/ML methods/approaches to innovate mechanistic QSP model discovery and development with multifaceted biological data.