Topic: real-world data

PharmSci 360 connects experimental, computational and clinical evidence across drug discovery, development and delivery. Researchers will examine in-vitro-to-human translation using PBPK, quantitative systems pharmacology and AI; organ-chip and other human-relevant models; biomarkers and reliable bioanalytical assays; and integrating clinical trials with real-world data. Manufacturing sessions connect process understanding, analytical characterization and digital models with quality and scale-up. Formulation sessions address predictive design, advanced materials, targeted delivery and patient

Nikita Rudin discusses reinforcement learning for robot locomotion and the difficulties of transferring policies from simulation to physical robots. Topics include visual inputs, real-world data for improving simulators, imitation learning and teleoperation, hierarchical control, and trade-offs between modular and end-to-end approaches for autonomous robots.