Speakers
Description
In drug development, mathematical models and quantitative tools are essential to driving efficiency and innovation. Such tools include quantitative systems pharmacology (QSP) models, disease progression models, pharmacokinetics and pharmacodynamics (PKPD) models, virtual populations, digital twins, and in silico clinical trials. These are used to assist in decision making across all stages of drug development, informing target selection, design of preclinical experiments, dose selection, clinical trial design, and more. In this session, we feature modelers across the pharmaceutical industry who will showcase their innovative work and real-world impact through compelling case studies. Join us to discover how cutting-edge quantitative science is driving informed decisions, reducing risk, and accelerating the delivery of new, life-changing therapies to patients.
Speakers:
Inmaculada Sorribes (Merck): “Fit-for-Purpose Modeling in Immuno-Oncology: A Practical Guide to Data and Quantitative Tools Across the Pipeline, featuring a Case Study on novel T Cell Engagers”
Gianluca Selvaggio (Pharmetheus): “Mathematical modelling as a tool to investigate bell-shaped dose-response relationships in drug development”
Hoai-Thu Thai (Sanofi): “Joint modeling of longitudinal data and survival outcome to improve decision making in oncology drug development”
Felix Jost (Sanofi): “Feature based prediction of preclinical pharmacokinetic profiles using machine learning and compartmental modeling”
