Framing oncology clinical development as an offline decision-making problem, where an agent predicts the next six-month trial portfolio of a drug programme from information available at the decision date. Built on a temporal dataset of 31.7k public records turned into 881 decision episodes across 45 historical programmes, used to train offline policies and compare them against frontier LLM agents on held-out drug, sponsor, drug-class and temporal splits.
