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Drug transporters are critical in drug absorption, distribution, and excretion processes. They should be included in physiological-based pharmacokinetic (PBPK) models, which help predict human drug disposition. However, predicting this is challenging during drug development, especially when liver transport is involved. However, with a realistic representation of body transport processes, an accurate model may be possible.
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Area of Science:

  • Pharmacokinetics and Drug Metabolism
  • Systems Biology and Modeling
  • Drug Discovery and Development

Background:

  • Drug-drug interactions (DDIs) mediated by hepatic transporters significantly impact drug efficacy and safety.
  • Organic anion transporting polypeptides (OATPs) are crucial for the uptake of many drugs, including statins.
  • Physiologically based pharmacokinetic (PBPK) modeling offers a powerful tool for predicting DDIs.

Purpose of the Study:

  • To develop a widely applicable PBPK modeling method for quantitative analysis of DDIs involving OATP inhibition.
  • To incorporate enterohepatic circulation (EHC) of statins into PBPK models for improved accuracy.
  • To optimize PBPK parameters using clinical data for various statin substrates and known OATP inhibitors.

Main Methods:

  • Construction of PBPK models for pitavastatin, fluvastatin, and pravastatin as OATP substrates.
  • Inclusion of cyclosporin A (CsA) and rifampicin (RIF) as OATP inhibitors in the PBPK models.
  • Optimization of absorption, hepatic elimination, and EHC parameters by fitting to clinical data.

Main Results:

  • The developed PBPK models satisfactorily explained the extent of DDIs caused by OATP inhibition.
  • Consistent in vivo inhibition constant (Ki) values were obtained for each inhibitor across different statin substrates.
  • Estimated Ki values for CsA aligned with in vitro data, while RIF values were lower than reported in vitro values.

Conclusions:

  • This study proposes a robust method for optimizing in vivo PBPK parameters in transporter-mediated DDIs.
  • The PBPK modeling approach provides a valuable framework for predicting OATP-mediated DDIs.
  • The findings contribute to a better understanding of statin pharmacokinetics and drug interactions.