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Updated: May 24, 2026

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method
Published on: May 21, 2018
Predicting drug interaction potential with a physiologically based pharmacokinetic model: a case study of
Md L T Vieira1, P Zhao, E G Berglund
1Office of Clinical Pharmacology, Office of Translational Sciences, US Food and Drug Administration, Silver Spring, Maryland, USA.
Abstract:
Telithromycin is a substrate and an inhibitor of cytochrome P450 3A (CYP3A4), with dose- and time-dependent nonlinear pharmacokinetics (PK). We hypothesized that the time-dependent inhibition (TDI) of CYP3A4 was responsible for the nonlinear PK of telithromycin and then used physiologically based PK (PBPK) modeling and simulation to verify this mechanism. Telithromycin PBPK models integrating in vitro, in silico, and in vivo PK data ruled out the contribution of enzyme/transporter saturation and suggested that TDI is a plausible mechanism for PK nonlinearity. The model successfully predicted the clinical interaction with the CYP3A4 substrate midazolam, as verified by external data not used for the model-building (intravenous (i.v.) and oral (p.o.) midazolam area under the concentration-time curve (AUC) ratio with/without concurrent telithromycin administration: 3.26 and 6.72 predicted vs. 2.20 and 6.11 observed, respectively). Models assuming reversible inhibition failed to predict such strong CYP3A4 inhibition. In the absence of in vitro TDI data, a PBPK model can be used to incorporate TDI mechanisms based on nonlinear PK data to predict clinical drug-drug interactions.
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