APOD: reasoning-guided agentic population ordinary differential equation discovery for pharmacological digital twins

Excerpt

arXiv:2610.06227v1 Announce Type: cross Abstract: Establishing ordinary differential equations (ODEs) describing population data is a fundamental part of mathematical modeling in pharmacology, crucial to developing digital twins. However, doing so from sparse, noisy data is a slow, expert-driven task. Existing automated methods either search a restricted model space or ignore population inter-individual variability. Here we introduce APOD (Agentic Population ODE Discovery), a language-model agen