Biomarker‐Informed Model‐Based Risk Assessment of Organic Anion Transporting Polypeptide 1B Mediated Drug‐Drug Interactions

基于生理学的药代动力学模型 药理学 丙磺舒 化学 药代动力学 体内 药品 生物标志物 有机阴离子转运多肽 效力 IC50型 运输机 体外 医学 生物化学 生物 生物技术 基因
作者
Emi Kimoto,Chester Costales,Mark A. West,Yi‐An Bi,Manoli Vourvahis,A. David Rodrigues,Manthena V. S. Varma
出处
期刊:Clinical Pharmacology & Therapeutics [Wiley]
卷期号:111 (2): 404-415 被引量:33
标识
DOI:10.1002/cpt.2434
摘要

Quantitative prediction of drug-drug interactions (DDIs) involving organic anion transporting polypeptide (OATP)1B1/1B3 inhibition is limited by uncertainty in the translatability of experimentally determined in vitro inhibition potency (half-maximal inhibitory concentration (IC50 )). This study used an OATP1B endogenous biomarker-informed physiologically-based pharmacokinetic (PBPK) modeling approach to predict the effect of inhibitor drugs on the pharmacokinetics (PKs) of OATP1B substrates. Initial static analysis with about 42 inhibitor drugs, using in vitro IC50 values and unbound liver inlet concentrations (Iin,max,u ), suggested in vivo OATP1B inhibition risk for drugs with R-value (1+ Iin,max,u /IC50 ) above 1.5. A full-PBPK model accounting for transporter-mediated hepatic disposition was developed for coproporphyrin I (CP-I), an endogenous OATP1B biomarker. For several inhibitors (cyclosporine, diltiazem, fenebrutinib, GDC-0810, itraconazole, probenecid, and rifampicin at 3 different doses), PBPK models were developed and verified against available CP-I plasma exposure data to obtain in vivo OATP1B inhibition potency-which tend to be lower than the experimentally measured in vitro IC50 by about 2-fold (probenecid and rifampicin) to 37-fold (GDC-0810). Models verified with CP-I data are subsequently used to predict DDIs with OATP1B probe drugs, rosuvastatin and pitavastatin. The predicted and observed area under the plasma concentration-time curve ratios are within 20% error in 55% cases, and within 30% error in 89% cases. Collectively, this comprehensive study illustrates the adequacy and utility of endogenous biomarker-informed PBPK modeling in mechanistic understanding and quantitative predictions of OATP1B-mediated DDIs in drug development.
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