British Journal of Clinical Pharmacology
British Journal of Clinical Pharmacology
5 years ago

A physiologically based pharmacokinetic modelling approach to predict buprenorphine pharmacokinetics following intravenous and sublingual administration

Steve N. Caritis, Hari V. Kalluri, Hongfei Zhang, Raman Venkataramanan
Aims Opioid dependence is associated with high morbidity and mortality. Buprenorphine (BUP) is approved by the Food and Drug Administration to treat opioid dependence. There is a lack of clear consensus on the appropriate dosing of BUP due to interpatient physiological differences in absorption/disposition, subjective response assessment and other patient comorbidities. The objective of the present study was to build and validate robust physiologically based pharmacokinetic (PBPK) models for intravenous (IV) and sublingual (SL) BUP as a first step to optimizing BUP pharmacotherapy. Methods BUP-PBPK modelling and simulations were performed using SimCyp® by incorporating the physiochemical properties of BUP, establishing intersystem extrapolation factors-based in vitro–in-vivo extrapolation (IVIVE) methods to extrapolate in vitro enzyme activity data, and using tissue-specific plasma partition coefficient estimations. Published data on IV and SL-BUP in opioid-dependent and non-opioid-dependent patients were used to build the models. Fourteen model-naïve BUP-PK datasets were used for inter- and intrastudy validations. Results The IV and SL-BUP-PBPK models developed were robust in predicting the multicompartment disposition of BUP over a dosing range of 0.3–32 mg. Predicted plasma concentration–time profiles in virtual patients were consistent with reported data across five single-dose IV, five single-dose SL and four multiple dose SL studies. All PK parameter predictions were within 75–137% of the corresponding observed data. The model developed predicted the brain exposure of BUP to be about four times higher than that of BUP in plasma. Conclusion The validated PBPK models will be used in future studies to predict BUP plasma and brain concentrations based on the varying demographic, physiological and pathological characteristics of patients.

Publisher URL: http://onlinelibrary.wiley.com/resolve/doi

DOI: 10.1111/bcp.13368

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