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<p>Cytochrome P450 3A4 (CYP3A4) is a key target for time-dependent inhibition (TDI) assessment during drug development. However, translating in vitro TDI data to <i>in vivo</i> drug-drug interaction (DDI) risk remains challenging due to the acknowledged overestimation when incorporating in vitro kinetics in predictive models. We investigated different in vitro TDI assay conditions in human liver microsomes (HLM) and evaluated their impact on the predictive accuracy for CYP3A4-related DDI for 32 marketed drugs. Considering assay sensitivity and <i>in vivo</i> DDI prediction accuracy with mechanistic static modeling (MSM), optimal incubation parameters were identified as: a pre-incubation time of 40&#xa0;min for precipitants and 10&#xa0;min incubation time for CYP3A4 substrate midazolam (10&#xa0;μM) at 0.1&#xa0;mg/mL HLM. A tendency to overestimate the DDI magnitude (AFE = 4.83, AAFE = 4.87) was still observed in MSM when using the unbound drug inhibition constant (KI,<sub>u</sub>) and maximum inactivation rate (k<sub>inact</sub>), measured under optimized incubation conditions. Improved predictions were achieved when applying the same parameters in physiologically-based pharmacokinetic (PBPK) models (AFE = 1.94, AAFE = 2.13), with 60% of predicted AUCR falling in the twofold range. These findings highlighted the importance of optimizing <i>in vitro</i> TDI incubation conditions, together with evaluating the benefits and limitations of numerical prediction approaches for predicting clinically significant CYP3A4 TDI effects with mechanistic static and PBPK models.</p> Graphical Abstract <p></p>

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Optimization of In Vitro CYP3A4 TDI Assay Conditions and Use of Derived Parameters for Clinical DDI Risk Assessment Using Static and Dynamic Models

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月13日

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  • Alessandra Pugliano,
  • Aynur Ekiciler,
  • Lena Preiss,
  • Neil John Parrott,
  • Pieter Annaert,
  • Kenichi Umehara

摘要

Cytochrome P450 3A4 (CYP3A4) is a key target for time-dependent inhibition (TDI) assessment during drug development. However, translating in vitro TDI data to in vivo drug-drug interaction (DDI) risk remains challenging due to the acknowledged overestimation when incorporating in vitro kinetics in predictive models. We investigated different in vitro TDI assay conditions in human liver microsomes (HLM) and evaluated their impact on the predictive accuracy for CYP3A4-related DDI for 32 marketed drugs. Considering assay sensitivity and in vivo DDI prediction accuracy with mechanistic static modeling (MSM), optimal incubation parameters were identified as: a pre-incubation time of 40 min for precipitants and 10 min incubation time for CYP3A4 substrate midazolam (10 μM) at 0.1 mg/mL HLM. A tendency to overestimate the DDI magnitude (AFE = 4.83, AAFE = 4.87) was still observed in MSM when using the unbound drug inhibition constant (KI,u) and maximum inactivation rate (kinact), measured under optimized incubation conditions. Improved predictions were achieved when applying the same parameters in physiologically-based pharmacokinetic (PBPK) models (AFE = 1.94, AAFE = 2.13), with 60% of predicted AUCR falling in the twofold range. These findings highlighted the importance of optimizing in vitro TDI incubation conditions, together with evaluating the benefits and limitations of numerical prediction approaches for predicting clinically significant CYP3A4 TDI effects with mechanistic static and PBPK models.

Graphical Abstract