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Physiologically based and population PK modeling in optimizing drug development: A predict–learn–confirm analysis
Author(s) -
Suri A,
Chapel S,
Lu C,
Venkatakrishnan K
Publication year - 2015
Publication title -
clinical pharmacology and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.941
H-Index - 188
eISSN - 1532-6535
pISSN - 0009-9236
DOI - 10.1002/cpt.155
Subject(s) - physiologically based pharmacokinetic modelling , clearance , drug development , pharmacokinetics , pharmacology , drug , population , medicine , computer science , urology , environmental health
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 .