Dr. Helen Moore
Dr. Moore is a mathematician who spent 11 years in academia working in modeling and optimization, primarily in oncology, immunology, and virology. While in academia, she won two teaching awards and received a National Science Foundation grant for her research. During 14 years in the biopharma industry, she has worked in a variety of therapeutic areas and drug development stages at Genentech, Certara, Bristol-Myers Squibb, AstraZeneca, and now Applied BioMath. In 2018, she was named a Fellow of the Society for Industrial and Applied Mathematics. Her current work includes mechanistic ODE systems modeling, modeling of tumor dynamics, optimization of combination regimens, and quantitative evaluation of predictive mathematical models. She graduated from the University of North Carolina at Chapel Hill in 1989, and earned her PhD in mathematics from Stony Brook University in New York in 1995.
Systems Modelling in Biopharma
Due to the resources required for drug development, quantitative systems pharmacology (QSP) models are increasingly being used for decision making in the biotechnology/pharmaceutical (biopharma) industry. QSP models are typically systems of ordinary differential equations with some mechanistic level of detail of the disease and a therapy. Parameters in a QSP model may be estimated from data, or obtained from the literature or from input from disease/biology experts. Once parameter values or distributions are determined, a QSP model can be used for predictive purposes. I will provide motivation for the use of QSP models in biopharma, and share an example of an actual QSP model application. I will also mention some of the issues and open problems for the use of QSP models.
Dr. Jake P. Taylor-King is a successful mathematician (G-Research prize, Lee Segel prize) and aspiring entrepreneur with degrees from the University of Bristol (BSc), the University of Oxford (MSc, D.Phil), and the University of Cambridge (MPhil). His work has broad scope, from theoretical advances (stochastic processes, numerical methods) to applied mathematical modelling (swarm robotics, animal migration). After a research secondment to the Moffitt Cancer Center, Jake then looked to work in increasingly biomedical settings (bone formation, histology analysis). A short post-doc at the ETH Zurich allowed for a transition into single-cell bioinformatics (HDL-X grant & iPSC time series modelling), which Jake then utilised as Head of Bioinformatics at Empyrean Therapeutics designing and optimising high throughput CRISPR screens. Dr. Taylor-King has worked with Juvenescence since mid 2019 to advance efforts in exploiting machine learning for drug development, and leads technical and scientific direction at Relation Therapeutics.
“Exploiting AI in Early Clinical Development”
Abstract coming soon.
Dr. Dean Bottino received his PhD in Applied Mathematics from Tulane University in 1996. His academic work at Tulane, and subsequently at University of Utah and UC Berkeley, consisted of spatiotemporal simulations of eukaryotic cell motility and chemotaxis. Dr. Bottino then moved into industry, joining Physiome Sciences in 2001, co-founding the BioAnalytics Group LLC in 2003, then moving on to Novartis in 2005, Roche in 2011 and Millennium (Takeda) in 2013. He has specialized in preclinical and clinical modeling and simulation in oncology since 2005.
Stuff I wish I’d paid better attention to in grad school:
Math modeling in oncology drug R&D
The talk will feature 2 or 3 vignettes of applications of mathematical modeling to oncology drug research and development: characterizing bivalent activation artifacts of an antagonist antibody, antibody-dependent cell mediated cytotoxicity (ADCC) in immune-oncology, and simultaneous toxicity and efficacy modeling for novel-novel anti-cancer drug combinations.
Since joining Pfizer April 2012, Richard has provided systems modeling and simulation support for multiple disease areas including Type 2 diabetes, chronic kidney disease, obesity, and non-alcoholic steatohepatitis. More recently, Richard has been working on a model of the immune response to COVID-19. Richard earned a PhD in Applied Mathematics from University College London and completed a postdoctoral fellowship at the University of North Carolina at Chapel Hill.
Insights into Modeling and Simulation Careers in Biopharma
Bringing novel medicines to patients is fraught with challenges. Many of these challenges are driven by uncertainty in the pathophysiology, or how a putative therapy is acting. By using mechanistic modeling to address these questions we hope to meet medical needs more efficiently. In this talk I will briefly describe what being a modeler at Pfizer is like, what we look for in new hires, and (by way of an example) the types of modeling we pursue.