Coproporphyrin I Can Serve as an Endogenous Biomarker for OATP1B1 Inhibition: Assessment Using a Glecaprevir/Pibrentasvir Clinical Study

Transporter-mediated drug-drug interactions: regulatory guidelines, in vitro and in vivo methodologies and translation, special populations, and the blood-brain barrier

This review, part of a special issue on drug-drug interactions (DDIs) spearheaded by the International Society for the Study of Xenobiotics (ISSX) New Investigators, explores the critical role of drug transporters in absorption, disposition, and clearance in the context of DDIs. Over the past two decades, significant advances have been made in understanding the clinical relevance of these transporters. Current knowledge on key uptake and efflux transporters that affect drug disposition and development is summarized. Regulatory guidelines from the FDA, EMA, and PMDA that inform the evaluation of potential transporter-mediated DDIs are discussed in detail. Methodologies for preclinical and clinical testing to assess potential DDIs are reviewed, with an emphasis on the utility of physiologically based pharmacokinetic (PBPK) modeling. This includes the application of relative abundance and expression factors to predict human pharmacokinetics (PK) using preclinical data, integrating the latest regulatory guidelines. Considerations for assessing transporter-mediated DDIs in special populations, including pediatric, hepatic, and renal impairment groups, are provided. Additionally, the impact of transporters at the blood-brain barrier (BBB) on the disposition of CNS-related drugs is explored. Enhancing the understanding of drug transporters and their role in drug disposition and toxicity can improve efficacy and reduce adverse effects. Continued research is essential to bridge remaining gaps in knowledge, particularly in comparison with cytochrome P450 (CYP) enzymes.

Rifampin- and Silymarin-Mediated Pharmacokinetic Interactions of Exogenous and Endogenous Substrates in a Transgenic OATP1B Mouse Model

Organic anion-transporting polypeptides (OATP) 1B1 and OATP1B3, encoded by the SLCO gene family of the solute carrier superfamily, are involved in the disposition of many exogenous and endogenous compounds. Preclinical rodent models help assess risks of pharmacokinetic interactions, but interspecies differences in transporter orthologs and expression limit direct clinical translation. An OATP1B transgenic mouse model comprising a rodent Slco1a/1b gene cluster knockout and human SLCO1B1 and SLCO1B3 gene insertions provides a potential physiologically relevant preclinical tool to predict pharmacokinetic interactions. Pharmacokinetics of exogenous probe substrates, pitavastatin and pravastatin, and endogenous OATP1B biomarkers, coproporphyrin-I and coproporphyrin-III, were determined in the presence and absence of known OATP/Oatp inhibitors, rifampin or silymarin (an extract of milk thistle [Silybum marianum]), in wild-type FVB mice and humanized OATP1B mice. Rifampin increased exposure of pitavastatin (4.6- and 2.8-fold), pravastatin (3.6- and 2.2-fold), and coproporphyrin-III (1.6- and 2.1-fold) in FVB and OATP1B mice, respectively, but increased coproporphyrin-I AUC0-24h only (1.8-fold) in the OATP1B mice. Silymarin did not significantly affect substrate AUC, likely because the silymarin flavonolignan concentrations were at or below their reported IC50 values for the relevant OATPs/Oatps. Silymarin increased the Cmax of pitavastatin 2.7-fold and pravastatin 1.9-fold in the OATP1B mice. The data of the OATP1B mice were similar to those of the pitavastatin and pravastatin clinical data; however, the FVB mice data more closely recapitulated pitavastatin clinical data than the data of the OATP1B mice, suggesting that the OATP1B mice are a reasonable, though costly, preclinical strain for predicting pharmacokinetic interactions when doses are optimized to achieve clinically relevant plasma concentrations.

Quantification of OATP1B1 endogenous metabolites coproporphyrin I and III in human urine

Coproporphyrin (CP)-I and CP-III are the markers of organic anion-transporting polypeptides' (OATPs) activities, and they are porphyrin metabolites that originate from heme synthesis. Furthermore, CP-I and CP-III, which are OATP1B endogenous metabolites, have gradually attracted the attention of scientists and researchers in recent years. Previous studies have also observed CP-I and CP-III levels as clinical biomarkers for predicting OATP1B inhibition in drug-drug interaction studies. To establish an accurate ultra-high performance liquid chromatography-mass spectrometry method for the quantitation of CP-I and CP-III, we reviewed previous methodological publications and applied them to a clinical pharmacology study using a human urine matrix. We used 13.25 M formic acid as a working solution for internal standards (CP-I 15N4 and CP-III d8) to avoid isobaric interference. The calibration curve showed good linearity in the range of 1-100 ng/mL, with a correlation coefficient (R2) higher than 0.996 in each validation batch. Both the between-run and within-run assays achieved good precision and accuracy, and we found that both CP-I and CP-III were stable in the pre-study validation. The method exhibited suitable dilution integrity, allowing for the re-analysis of samples with concentrations exceeding the upper limit of quantification through dilution. Overall, the application of the described method in a clinical study revealed that it can be utilized effectively to monitor drug-drug interactions mediated by OATP1B.

Progress in the Quantitative Assessment of Transporter-Mediated Drug-Drug Interactions Using Endogenous Substrates in Clinical Studies

Variations in drug transporter activities, caused by genetic polymorphism and drug-drug interactions (DDIs), alter the systemic exposure of substrate drugs, leading to differences in drug responses. Recently, some endogenous substrates of drug transporters, particularly the solute carrier family transporters such as OATP1B1, OATP1B3, OAT1, OAT3, OCT1, OCT2, MATE1, and MATE2-K, have been identified to investigate variations in drug transporters in humans. Clinical data obtained support their performance as surrogate probes in terms of specificity and reproducibility. Pharmacokinetic parameters of the endogenous biomarkers depend on the genotypes of drug transporters and the systemic exposure to perpetrator drugs. Furthermore, the development of physiologically based pharmacokinetic models for the endogenous biomarkers has enabled a top-down approach to obtain insights into the effect of perpetrators on drug transporters and to more precisely simulate the DDI with victim drugs, including probe drugs. The endogenous biomarkers can address the uncertainty in the DDI prediction in the preclinical and early phases of clinical development and have the potential to fulfill regulatory requirements. Therefore, the endogenous biomarkers should be able to predict disease effects on the variations in drug transporter activities observed in patients. This mini-review focuses on recent progress in the identification and use of the endogenous drug transporter substrate biomarkers and their application in drug development. SIGNIFICANCE STATEMENT: Advances in analytical methods have enabled the identification of endogenous substrates of drug transporters. Changes in the pharmacokinetic parameters (Cmax, AUC, or CLR) of these endogenous biomarkers relative to baseline values can serve as a quantitative index to assess variations in drug transporter activities during clinical studies and thereby provide more precise DDI predictions.

Differential Preincubation Effects of Nicardipine on OATP1B1- and OATP1B3-Mediated Transport in the Presence and Absence of Protein: Implications in Assessing OATP1B1- and OATP1B3-Mediated Drug-Drug Interactions

Impaired transport activity of hepatic OATP1B1 and OATP1B3 due to drug-drug interactions (DDIs) often leads to increased systemic exposure to substrate drugs (e.g., lipid-lowering statins). Since dyslipidemia and hypertension frequently coexist, statins are often concurrently used with antihypertensives, including calcium channel blockers (CCBs). OATP1B1/1B3-related DDIs in humans have been reported for several CCBs. To date, the OATP1B1/1B3-mediated DDI potential of CCB nicardipine has not been assessed. The current study was designed to assess the OATP1B1- and OATP1B3-mediated DDI potential of nicardipine using the R-value model, following the US-FDA guidance. IC50 values of nicardipine against OATP1B1 and OATP1B3 were determined in transporter-overexpressing human embryonic kidney 293 cells using [3H]-estradiol 17β-D-glucuronide and [3H]-cholecystokinin-8 as substrates, respectively, with or without nicardipine-preincubation in protein-free Hanks' Balanced Salt Solution (HBSS) or in fetal bovine serum (FBS)-containing culture medium. Preincubation with nicardipine for 30 min in protein-free HBSS buffer produced lower IC50 and higher R-values for both OATP1B1 and OATP1B3 compared to in FBS-containing medium, yielding IC50 values of 0.98 and 1.63 µM and R-values of 1.4 and 1.3 for OATP1B1 and OATP1B3, respectively. The R-values were higher than the US-FDA cut-off value of 1.1, supporting that nicardipine has the potential to cause OATP1B1/3-mediated DDIs. Current studies provide insight into the consideration of optimal preincubation conditions when assessing the OATP1B1/3-mediated DDIs in vitro.

Determination of the endogenous OATP1B biomarkers glycochenodeoxycholate-3-sulfate and chenodeoxycholate-24-glucuronide in human and mouse plasma by a validated UHPLC-MS/MS method

Glycochenodeoxycholate-3-sulfate (GCDCA-S) and chenodeoxycholate-24-glucuronide (CDCA-24G) are bile acid metabolites that potentially serve as endogenous biomarkers for drug-drug interactions mediated by the hepatic uptake transporters OATP1B1 and OATP1B3. We developed and validated a novel UHPLC-MS/MS method for the quantitative determination of GCDCA-S and CDCA-24G in mouse and human plasma with a lower limit of quantitation of 0.5 ng/mL. Chromatographic separation was achieved on an Accucore aQ column (50 mm × 2.1 mm, dp = 2.6 μm) maintained at 20 °C and a gradient mobile phase comprising 2 mM ammonium acetate in water and methanol. The extraction recoveries of GCDCA-S and CDCA-24G were >80 %, and linear (r2 > 0.99) calibration curves ranged 0.5-100 ng/mL (CDCA-24G and GCDCA-S in mouse plasma) or 0.5-1000 ng/mL (GCDCA-S in mouse plasma). Values for precision (CV < 11.6 %) and accuracy bias (10.9 %) of analyte-spiked quality control samples verified that water was an acceptable matrix to prepare calibrators. This method was successfully applied to establish baseline activity of OATP1B1/OATP1B3 in humans and mice and establish the in vivo effects of OATP1B1/OATP1B3 inhibitors rifampin and micafungin.

Cluster Gauss-Newton method analyses of PBPK model parameter combinations of coproporphyrin-I based on OATP1B-mediated rifampicin interaction studies

Coproporphyrin I (CP-I) is an endogenous biomarker supporting the prediction of drug-drug interactions (DDIs) involving hepatic organic anion transporting polypeptide 1B (OATP1B). We previously constructed a physiologically-based pharmacokinetic (PBPK) model for CP-I using clinical DDI data with an OATP1B inhibitor, rifampicin (RIF). In this study, PBPK model parameters for CP-I were estimated using the cluster Gauss-Newton method (CGNM), an algorithm used to find multiple approximate solutions for nonlinear least-squares problems. Eight unknown parameters including the hepatic overall intrinsic clearance (CL_int,all ), the rate of biosynthesis (v_syn ), and the OATP1B inhibition constant of RIF(K_i,u,OATP ) were estimated by fitting to the observed CP-I blood concentrations in two different clinical studies involving changing the RIF dose. Multiple parameter combinations were obtained by CGNM that could well capture the clinical data. Among those, CL_int,all , K_i,u,OATP , and v_syn were sensitive parameters. The obtained K_i,u,OATP for CP-I was 5.0- and 2.8-fold lower than that obtained for statins, confirming our previous findings describing substrate-dependent K_i,u,OATP values. In conclusion, CGNM analyses of PBPK model parameter combinations enables estimation of the three essential parameters for CP-I to capture the DDI profiles, even if the other parameters remain unidentified. The CGNM also clarified the importance of appropriate combinations of other unidentified parameters to enable capture of the CP-I concentration time course under the influence of RIF. The described CGNM approach may also support the construction of robust PBPK models for additional transporter biomarkers beyond CP-I.

Development and validation of an LC-MS/MS method to quantify kynurenic acid in human plasma

Background: Monitoring levels of endogenous biomarkers has become an alternative approach to assess transporter-mediated drug-drug interactions in clinical trials. Among the biomarkers of interest, kynurenic acid is effective for the human organic anion transporters OAT1 and OAT3. Here, a simple and robust bioanalytical method was developed using LC-MS/MS to quantify kynurenic acid in human plasma. Results: This method achieved a LLOQ of 10 nm with acceptable signal-to-noise ratio (S/N >5). In addition, an interfering agent, tryptophan, was identified and separated chromatographically. A full method validation was performed in the spirit of GLP. Conclusion: This method can serve as a tool readily available to assess potential drug-drug interactions mediated by inhibition of OAT1 and OAT3 activities.

Reimagining the Framework Supporting the Static Analysis of Transporter Drug Interaction Risk; Integrated Use of Biomarkers to Generate Pan‐Transporter Inhibition Signatures

Solute carrier (SLC) transporters present as the loci of important drug-drug interactions (DDIs). Therefore, sponsors generate in vitro half-maximal inhibitory concentration (IC₅₀ ) data and apply regulatory agency-guided "static" methods to assess DDI risk and the need for a formal clinical DDI study. Because such methods are conservative and high false-positive rates are likely (e.g., DDI study triggered when liver SLC R value ≥ 1.04 and renal SLC maximal unbound plasma (C_max,u )/IC₅₀ ratio ≥ 0.02), investigators have attempted to deploy plasma- and urine-based SLC biomarkers in phase I studies to de-risk DDI and obviate the need for drug probe-based studies. In this regard, it was possible to generate in-house in vitro SLC IC₅₀ data for various clinically (biomarker)-qualified perpetrator drugs, under standard assay conditions, and then estimate "% inhibition" for each SLC and relate it empirically to published clinical biomarker data (area under the plasma concentration vs. time curve (AUC) ratio (AUCR, AUC_inhibitor /AUC_reference ) and % decrease in renal clearance (ΔCL_renal )). After such a "calibration" exercise, it was determined that only compounds with high R values (> 1.5) and C_max,u /IC₅₀ ratios (> 0.5) are likely to significantly modulate liver (AUCR > 1.25) and renal (ΔCL_renal  > 25%) biomarkers and evoke DDI risk. The % inhibition approach supports integration of liver and renal SLC data and allows one to generate pan-SLC inhibition signatures for different test perpetrators (e.g., SLC % inhibition ranking). In turn, such signatures can guide the selection of the most appropriate individual (or combinations of) biomarkers for testing in phase I studies.

Utilizing Endogenous Biomarkers to Derisk Assessment of Transporter Mediated Drug-Drug Interactions: A Scientific Perspective

Comprehensive characterization of transporter mediated drug-drug interactions (DDIs) is important to formulate clinical management strategies and ensure the safe and effective use of concomitantly administered drugs. The potential of a drug to inhibit transporters is predicted by comparing the ratio of the relevant concentration (depending on the transporter) and the half maximum inhibitory concentration (IC₅₀ ) to a pre-defined "cut off" value. If the ratio is greater than the cut off value, modeling approaches such as Physiologically Based Pharmacokinetic (PBPK) Modeling or a clinical DDI trial may be recommended. Because false positive (in vitro data suggests the potential for a DDI, whereas no significant DDI is observed in vivo) and false negative (in vitro data does not suggest the potential for a DDI, whereas significant DDI is observed in vivo) outcomes have been observed, there is interest in exploring additional approaches to facilitate prediction of transporter mediated DDIs. The idea of assessing changes in the concentration of endogenous biomarkers (which are substrates of clinically relevant transporters) to gain insight on the potential for a drug to inhibit transporter activity has received widespread attention. This brief report describes how endogenous biomarkers may help to expand the DDI assessment toolkit, highlights some current knowledge gaps, and outlines a conceptual framework that may complement the current paradigm of predicting the potential for transporter mediated DDIs. This article is protected by copyright. All rights reserved.

Effect of Cyclosporin A and Impact of Dose Staggering on OATP1B1/1B3 Endogenous Substrates and Drug Probes for Assessing Clinical Drug Interactions

This study was designed to assess the quantitative performance of endogenous biomarkers for organic anion transporting polypeptide (OATP) 1B1/1B3‐mediated drug‐drug interactions (DDIs). Ten healthy volunteers orally received OATP1B1/1B3 probe cocktail (0.2 mg pitavastatin, 1 mg rosuvastatin, and 2 mg valsartan) and an oral dose of cyclosporin A (CysA, 20 mg and 75 mg) separated by a 1‐hour interval (20 mg (−1 hour), and 75 mg (−1 hour)). CysA 75 mg was also given with a 3‐hour interval (75 mg (−3 hours)) to examine the persistence of OATP1B1/1B3 inhibition. The area under the plasma concentration‐time curve ratios (AUCRs) were 1.63, 3.46, and 2.38 (pitavastatin), 1.39, 2.16, and 1.81 (rosuvastatin), and 1.42, 1.77, and 1.85 (valsartan), at 20 mg, 75 mg (−1 hour) and 75 mg (−3 hours) of CysA, respectively. CysA effect on OATP1B1/1B3 was unlikely to persist at the dose examined. Among 26 putative OATP1B1/1B3 biomarkers evaluated, AUCR and maximum concentration ratio (C_maxR) of CP‐I showed the highest Pearson’s correlation coefficient with CysA AUC (0.94 and 0.93, respectively). Correlation between AUCR of pitavastatin, and C_maxR or AUCR of CP‐I were consistent between this study and our previous study using rifampicin as an OATP1B1/1B3 inhibitor. Nonlinear regression analysis of AUCR⁻¹ of pitavastatin and CP‐I against CysA C_max yielded K_{i,OATP1B1/1B3,app} (109 ± 35 and 176 ± 42 nM, respectively), similar to the K_{i,OATP1B1/1B3} estimated by our physiologically‐based pharmacokinetic model analysis described previously (107 nM). The endogenous OATP1B1/1B3 biomarkers, particularly C_maxR and AUCR of CP‐I, corroborates OATP1B1/1B3 inhibition and yields valuable information that improve accurate DDI predictions in drug development, and enhance our understanding of interindividual variability in the magnitude of DDIs.

Physiologically-based pharmacokinetic model-based translation of OATP1B-mediated drug-drug interactions from coproporphyrin I to probe drugs

The accurate prediction of OATP1B-mediated drug-drug interactions (DDIs) is challenging for drug development. Here, we report physiologically-based pharmacokinetic (PBPK) model analysis for clinical DDI data generated in heathy subjects who received oral doses of cyclosporin A (CysA; 20 and 75 mg) as an OATP1B inhibitor, and the probe drugs (pitavastatin, rosuvastatin and valsartan). PBPK models of CysA and probe compounds were combined assuming inhibition of hepatic uptake of endogenous coproporphyrin I (CP-I) by CysA. In vivo K_i of unbound CysA for OATP1B (K_i,OATP1B ), and the overall intrinsic hepatic clearance per body weight of CP-I (CL_int,all,unit ) were optimized to account for the CP-I data (K_i,OATP1B , 0.657 ± 0.048 nM; CL_int,all,unit , 57.0 ± 6.3 L/h/kg). DDI simulation using K_i,OATP1B reproduced the dose-dependent effect of CysA (20 and 75 mg) and the dosing interval (1 h and 3 h) on the time profiles of blood concentrations of pitavastatin and rosuvastatin, but DDI simulation using in vitro K_i,OATP1B failed. The Cluster Gauss-Newton method was used to conduct parameter optimization using 1,000 initial parameter sets for the seven pharmacokinetic parameters of CP-I (β, CL_int,all , F_a F_g , R_dif , f_bile , f_syn , and v_syn ), and K_i,OATP1B , and K_i,MRP2 of CysA. Based on the accepted 498 parameter sets, the range of CL_int,all and K_i,OATP1B was narrowed, with coefficients of variation (CVs) of 9.3% and 11.1%, respectively, indicating that these parameters were practically identifiable. These results suggest that PBPK model analysis of CP-I is a promising translational approach to predict OATP1B-mediated DDIs in drug development.

Quantitative prediction of pharmacokinetic properties of drugs in humans: Recent advance in in vitro models to predict the impact of efflux transporters in the small intestine and blood-brain barrier

Efflux transport systems are essential to suppress the absorption of xenobiotics from the intestinal lumen and protect the critical tissues at the blood-tissue barriers, such as the blood-brain barrier. The function of drug efflux transport is dominated by various transporters. Accumulated clinical evidences have revealed that genetic variations of the transporters, together with coadministered drugs, affect the expression and/or function of transporters and subsequently the pharmacokinetics of substrate drugs. Thus, in the preclinical stage of drug development, quantitative prediction of the impact of efflux transporters as well as that of uptake transporters and metabolic enzymes on the pharmacokinetics of drugs in humans has been performed using various in vitro experimental tools. Various kinds of human-derived cell systems can be applied to the precise prediction of drug transport in humans. Mathematical modeling consisting of each intrinsic metabolic or transport process enables us to understand the disposition of drugs both at the organ level and at the level of the whole body by integrating a variety of experimental results into model parameters. This review focuses on the role of efflux transporters in the intestinal absorption and brain distribution of drugs, in addition to recent advances in predictive tools and methodologies.

Endogenous Biomarkers for SLC Transporter-Mediated Drug-Drug Interaction Evaluation

Membrane transporters play an important role in the absorption, distribution, metabolism, and excretion of xenobiotic substrates, as well as endogenous compounds. The evaluation of transporter-mediated drug-drug interactions (DDIs) is an important consideration during the drug development process and can guide the safe use of polypharmacy regimens in clinical practice. In recent years, several endogenous substrates of drug transporters have been identified as potential biomarkers for predicting changes in drug transport function and the potential for DDIs associated with drug candidates in early phases of drug development. These biomarker-driven investigations have been applied in both preclinical and clinical studies and proposed as a predictive strategy that can be supplanted in order to conduct prospective DDIs trials. Here we provide an overview of this rapidly emerging field, with particular emphasis on endogenous biomarkers recently proposed for clinically relevant uptake transporters.