OncoTraj: a public benchmark for longitudinal resistance prediction in EGFR-mutant non-small-cell lung cancer on osimertinib
OncoTraj establishes the first public benchmark for training machine learning models on longitudinal cancer patient data, aggregating 813 EGFR-mutant NSCLC cases across three clinical-genomic sources to standardize resistance prediction under osimertinib therapy. The dataset unlocks three locked evaluation tasks spanning binary progression classification, time-to-event regression, and multi-class outcome prediction, addressing a critical gap in computational oncology where predictable clonal evolution under drug pressure has lacked standardized benchmarking infrastructure. This work signals growing maturity in clinical ML by moving beyond isolated retrospective studies toward reproducible, multi-institutional evaluation frameworks that enable direct model comparison and accelerate development of clinically actionable resistance forecasting systems.62
