Analysis of time dependent inhibition reveals that ESI complexities impact drug-drug interactions and predictions.
In order to predict drug-drug interactions (DDIs), screening and evaluating time dependent inhibition (TDI) of cytochrome P450 (CYPs) is an important part of the drug discovery process. Invitro experiments are performed for obtaining TDI parameters (inhibitor binding constant, K I , and inactivation rate constant, k inact ) which are further used for the prediction of clinical DDI. This work utilized numerical methods for analysis of in vitro in vitro TDI datasets to estimate K I and k inact . Specifically, the impact of enzyme-substrate-inhibitor (ESI) complex formation on the estimation of K I and k inact was evaluated. A total of 13 datasets were evaluated, all of which exhibited non-Michaelis-Menten kinetics including activation, biphasic inactivation, partial inactivation, and multiple binding kinetics. Datasets were modeled with and without ESI formation. The difference in inactivation efficiency between models with and without ESI ranged from 0.67-fold to 2.94-fold across all compounds. This resulted in different DDI predictions ranging from moderate to strong DDI predictions for the same compound. These results suggest that in vitro TDI models should incorporate the observed in vitro kinetic complexities to improve confidence in in vivo DDI prediction.
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Yadav et al. (2026) studied this question.
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