CPT: Pharmacometrics & Systems Pharmacology (Sep 2021)

Quantitative prediction of breast cancer resistant protein mediated drug‐drug interactions using physiologically‐based pharmacokinetic modeling

  • Chester Costales,
  • Jian Lin,
  • Emi Kimoto,
  • Shinji Yamazaki,
  • James R. Gosset,
  • A. David Rodrigues,
  • Sarah Lazzaro,
  • Mark A. West,
  • Michael West,
  • Manthena V. S. Varma

DOI
https://doi.org/10.1002/psp4.12672
Journal volume & issue
Vol. 10, no. 9
pp. 1018 – 1031

Abstract

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Abstract Quantitative assessment of drug‐drug interactions (DDIs) involving breast cancer resistance protein (BCRP) inhibition is challenged by overlapping substrate/inhibitor specificity. This study used physiologically‐based pharmacokinetic (PBPK) modeling to delineate the effects of inhibitor drugs on BCRP‐ and organic anion transporting polypeptide (OATP)1B‐mediated disposition of rosuvastatin, which is a recommended BCRP clinical probe. Initial static model analysis using in vitro inhibition data suggested BCRP/OATP1B DDI risk while considering regulatory cutoff criteria for a majority of inhibitors assessed (25 of 27), which increased rosuvastatin plasma exposure to varying degree (~ 0–600%). However, rosuvastatin area under plasma concentration‐time curve (AUC) was minimally impacted by BCRP inhibitors with calculated G‐value (= gut concentration/inhibition potency) below 100. A comprehensive PBPK model accounting for intestinal (OATP2B1 and BCRP), hepatic (OATP1B, BCRP, and MRP4), and renal (OAT3) transport mechanisms was developed for rosuvastatin. Adopting in vitro inhibition data, rosuvastatin plasma AUC changes were predicted within 25% error for 9 of 12 inhibitors evaluated via PBPK modeling. This study illustrates the adequacy and utility of a mechanistic model‐informed approach in quantitatively assessing BCRP‐mediated DDIs.