Physiologically based and population PK modeling in optimizing drug development: A predict-learn-confirm analysis

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Abstract

Physiologically based pharmacokinetic (PBPK) modeling and classical population pharmacokinetic (PK) model-based simulations are increasingly used to answer various drug development questions. In this study, we propose a methodology to optimize the development of drugs, primarily cleared by the kidney, using model-based approaches to determine the need for a dedicated renal impairment (RI) study. First, the impact of RI on drug exposure is simulated via PBPK modeling and then confirmed using classical population PK modeling of phase 2/3 data. This methodology was successfully evaluated and applied to an investigational agent, orteronel (nonsteroidal, reversible, selective 17,20-lyase inhibitor). A phase 1 RI study confirmed the accuracy of model-based predictions. Hence, for drugs eliminated primarily via renal clearance, this modeling approach can enable inclusion of patients with RI in phase 3 trials at appropriate doses, which may be an alternative to a dedicated RI study, or suggest that only a reduced-size study in severe RI may be sufficient.

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Suri, A., Chapel, S., Lu, C., & Venkatakrishnan, K. (2015). Physiologically based and population PK modeling in optimizing drug development: A predict-learn-confirm analysis. Clinical Pharmacology and Therapeutics, 98(3), 336–344. https://doi.org/10.1002/cpt.155

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