Background Numerous drugs have the potential to be affected by cytochrome P450 (CYP) 2B6-mediated drug-drug interactions (DDIs). Objectives In this work, we extend a static approach to the prediction of the extent of pharmacokinetics DDIs between substrates and inhibitors or inducers of CYP2B6. Methods This approach is based on the calculation of two parameters (the contribution ratio [CR], representing the fraction of dose of the substrate metabolized via this pathway and the inhibitory or inducing potency of the perpetrator [IR or IC, respectively]) calculated from the area under the concentration-time curve (AUC) ratios obtained in in-vivo DDI studies. Results Forty-eight studies involving 5 substrates, 11 inhibitors and 18 inducers of CYP2B6 (overall 15 inhibition and 33 induction studies) were divided into test and validation sets and considered for estimation of the parameters. The proposed approach demonstrated a fair accuracy for predicting the extent of DDI related to CYP2B6 inhibition and induction, all predictions related to the validation test (N = 18) being 50-200% of the observed ratios. Conclusions This methodology can be used for proposing initial dose adaptations to be adopted, for example in clinical use or for designing DDI studies involving this enzyme.

Quantitative Prediction of Drug Interactions Caused by Cytochrome P450 2B6 Inhibition or Induction

Di Paolo, Veronica;Quintieri, Luigi
2022

Abstract

Background Numerous drugs have the potential to be affected by cytochrome P450 (CYP) 2B6-mediated drug-drug interactions (DDIs). Objectives In this work, we extend a static approach to the prediction of the extent of pharmacokinetics DDIs between substrates and inhibitors or inducers of CYP2B6. Methods This approach is based on the calculation of two parameters (the contribution ratio [CR], representing the fraction of dose of the substrate metabolized via this pathway and the inhibitory or inducing potency of the perpetrator [IR or IC, respectively]) calculated from the area under the concentration-time curve (AUC) ratios obtained in in-vivo DDI studies. Results Forty-eight studies involving 5 substrates, 11 inhibitors and 18 inducers of CYP2B6 (overall 15 inhibition and 33 induction studies) were divided into test and validation sets and considered for estimation of the parameters. The proposed approach demonstrated a fair accuracy for predicting the extent of DDI related to CYP2B6 inhibition and induction, all predictions related to the validation test (N = 18) being 50-200% of the observed ratios. Conclusions This methodology can be used for proposing initial dose adaptations to be adopted, for example in clinical use or for designing DDI studies involving this enzyme.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3454260
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