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Utilization of OATP1B Biomarker Coproporphyrin-I to Guide Drug-Drug Interaction Risk Assessment: Evaluation by the Pharmaceutical Industry.

Ryota KikuchiParesh P ChotheXiaoyan ChuFelix HuthKazuya IshidaNaoki IshiguroRongrong JiangHong ShenSimone H StahlManthena V S VarmaMarie-Emilie WilleminBridget L Morse
Published in: Clinical pharmacology and therapeutics (2023)
Drug-drug interactions (DDIs) involving hepatic organic anion transporting polypeptides 1B1/1B3 (OATP1B) can be substantial, however, challenges remain for predicting interaction risk. Emerging evidence suggests that endogenous biomarkers, particularly coproporphyrin-I (CP-I), can be used to assess in vivo OATP1B activity. The present work under the International Consortium for Innovation and Quality in Pharmaceutical Development was aimed primarily at assessing CP-I as a biomarker for informing OATP1B DDI risk. Literature and unpublished CP-I data along with pertinent in vitro and clinical DDI information were collected to identify DDIs primarily involving OATP1B inhibition and assess the relationship between OATP1B substrate drug and CP-I exposure changes. Static models to predict changes in exposure of CP-I, as a selective OATP1B substrate, were also evaluated. Significant correlations were observed between CP-I area-under-the-curve ratio (AUCR) or maximum concentration ratio (C max R) and AUCR of substrate drugs. In general, the CP-I C max R was equal to or greater than the CP-I AUCR. CP-I C max R <1.25 was associated with absence of OATP1B-mediated DDIs (AUCR <1.25) with no false negative predictions. CP-I C max R <2 was associated with weak OATP1B-mediated DDIs (AUCR <2). A correlation was identified between CP-I exposure changes and OATP1B1 static DDI predictions. Recommendations for collecting and interpreting CP-I data are discussed, including a decision tree for guiding DDI risk assessment. In conclusion, measurement of CP-I is recommended to inform OATP1B inhibition potential. The current analysis identified changes in CP-I exposure that may be used to prioritize, delay or replace clinical DDI studies.
Keyphrases
  • risk assessment
  • human health
  • electronic health record
  • big data
  • ionic liquid
  • quality improvement
  • adverse drug