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

Author:

Kikuchi Ryota1,Chothe Paresh P.2ORCID,Chu Xiaoyan3ORCID,Huth Felix4ORCID,Ishida Kazuya5ORCID,Ishiguro Naoki6,Jiang Rongrong7,Shen Hong8,Stahl Simone H.9ORCID,Varma Manthena V.S.10ORCID,Willemin Marie‐Emilie11,Morse Bridget L.12

Affiliation:

1. Quantitative, Translational and ADME Sciences, AbbVie Inc. North Chicago Illinois USA

2. Global Drug Metabolism and Pharmacokinetics, Takeda Development Center Americas, Inc. (TDCA) Lexington Massachusetts USA

3. ADME and Discovery Toxicology, Merck & Co., Inc. Rahway New Jersey USA

4. PK Sciences, Novartis Pharma AG Basel Switzerland

5. Drug Metabolism, Gilead Sciences Inc. Foster City California USA

6. Pharmacokinetics and Non‐Clinical Safety Department, Nippon Boehringer Ingelheim Co., Ltd. Kobe Japan

7. Drug Metabolism and Pharmacokinetics, Eisai Inc. Cambridge Massachusetts USA

8. Departments of Drug Metabolism and Pharmacokinetics Bristol Myers Squibb Research and Development Princeton New Jersey USA

9. CVRM Safety, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca Cambridge UK

10. Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Pfizer Inc. Groton Connecticut USA

11. Drug Metabolism and Pharmacokinetics, Janssen Research and Development, a Division of Janssen Pharmaceutica NV Beerse Belgium

12. Department of Drug Disposition Eli Lilly Indianapolis Indiana USA

Abstract

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 Literature and unpublished CP‐I data along with pertinent in vitro and clinical DDI information were collected to identify DDIs primarily involving OATP1B inhibition and assess the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 (CmaxR) and AUCR of substrate drugs. In general, the CP‐I CmaxR was equal to or greater than the CP‐I AUCR. CP‐I CmaxR < 1.25 was associated with absence of OATP1B‐mediated DDIs (AUCR < 1.25) with no false negative predictions. CP‐I CmaxR < 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.

Publisher

Wiley

Subject

Pharmacology (medical),Pharmacology

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