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Reliably predicting  in vivo  efficacy from  in vitro  data would facilitate drug development by reducing animal usage and guiding drug dosing in human clinical trials. However, such prediction remains challenging. Here, we built a quantitative pharmacokinetic/pharmacodynamic (PK/PD) mathematical model capable of predicting  in vivo  efficacy in animal xenograft models of tumor growth while trained almost exclusively on  in vitro  cell culture data sets. We studied a chemical inhibitor of LSD1 (ORY‐1001), a lysine‐specific histone demethylase enzyme with epigenetic function, and drug‐induced regulation of target engagement, biomarker levels, and tumor cell growth across multiple doses administered in a pulsed and continuous fashion. A PK model of unbound plasma drug concentration was linked to the  in vitro  PD model, which enabled the prediction of  in vivo  tumor growth dynamics across a range of drug doses and regimens. Remarkably, only a change in a single parameter—the one controlling intrinsic cell/tumor growth in the absence of drug—was needed to scale the PD model from the  in vitro  to  in vivo  setting. These findings create a framework for using  in vitro  data to predict  in vivo  drug efficacy with clear benefits to reducing animal usage while enabling the collection of dense time course and dose response data in a highly controlled  in vitro  environment.

Predicting In Vivo Efficacy from In Vitro Data: Quantitative Systems Pharmacology Modeling for an Epigenetic Modifier Drug in Cancer