Clinical Exposure Normalization Restores Translational Predictiveness of In Vitro Drug Response

Traditional laboratory methods quantify drug-efficacy based on dose-response metrics (e.g. IC50 or AUC), whereas clinical oncology defines drug-efficacy based on time-response metrics (e.g. progressive or stable disease). These measures often diverge, limiting translation between bench and bedside. We developed NCI1970-Meta, a harmonized dataset of 49,002 evaluable patients covering 30 drugs and 18 cancers, to provide the first large-scale benchmark linking in vitro potency, clinical pharmacokinetics, and Phase 2–3 outcomes data.

Raw in vitro metrics values showed poor correlation with clinical response, systematically underestimating antimetabolites and overvaluing outliers such as gemcitabine. By contrast, normalizing potency to clinically achievable exposure (e.g. the maximum plasma concentration (Cmax)) restored concordance with trial outcomes. Biomarker analyses, which compare patients treated with the same drug, were largely robust to this dichotomy: 234 curated biomarkers showed concordance across clinical and in vitro datasets. In addition, curated transporter knockout data validated a parallel flux model of additive resistance, explaining the limited success of multi-drug resistance inhibitors for drug-transporter enzymes.

These findings establish exposure-normalized potency as a simple, actionable framework for translational oncology. We recommend screening to the unbound Cmax and normalizing potency metrics by exposure to improve the fidelity of functional assays, reduce bias in AI models, and refine biomarker discovery. Beyond cytotoxic agents, NCI1970-Meta provides a general framework for aligning laboratory pharmacology with clinical outcomes.