Comprehensive Evaluation of the Utility of 20 Endogenous Molecules as Biomarkers of OATP1B Inhibition Compared with Rosuvastatin and Coproporphyrin I

An Isolated Perfused Rat Liver Model: Simultaneous LC-MS Quantification of Pitavastatin, Coproporphyrin I, and Coproporphyrin III Levels in the Rat Liver and Bile

The isolated perfused rat liver (IPRL) model provides a mechanistic understanding of the organic-anion-transporting polypeptide (OATP/Oatp)-mediated pharmacokinetics in the preclinical evaluation, which often requires the use of control substrates (i.e., pitavastatin) and monitoring endogenous biomarkers (coproporphyrin I and III). This study aimed to develop and validate an LC-MS method allowing the simultaneous quantification of pitavastatin, coproporphyrin I (CPI), and coproporphyrin III (CPIII) in rat liver perfusion matrices (perfusate, liver homogenate, bile). The analysis was performed on a C18 column at 60 °C with 20 μL of sample injection. The mobile phases consisted of water with 0.1% formic acid and acetonitrile with 0.1% formic acid with a gradient flow of 0.5 mL/min. The assay was validated according to the ICH M10 Bioanalytical Method Validation Guideline (2022) for selectivity, calibration curve and range, matrix effect, carryover, accuracy, precision, and reinjection reproducibility. The method allowing the simultaneous quantification of pitavastatin, CPI, and CPIII was selective without having carryover and matrix effects. The linear calibration curves were obtained within various calibration ranges for three analytes in different matrices. Accuracy and precision values fulfilled the required limits. After 60 min perfusion with pitavastatin (1 μM), the cumulative amounts of pitavastatin in the liver and bile were 5.770 ± 1.504 and 0.852 ± 0.430 nmol/g liver, respectively. CPIII was a more dominant marker than CPI in both liver (0.028 ± 0.017 vs 0.013 ± 0.008 nmol/g liver) and bile (0.016 ± 0.011 vs 0.009 ± 0.007 nmol/g liver). The novel and validated bioanalytical method can be applied in further IPRL preparations investigating Oatp-mediated pharmacokinetics and DDIs.

Utility of Coproporphyrin-I Determination in First-in-Human Study for Early Evaluation of OATP1B Inhibitory Potential Based on Investigation of Ensitrelvir, an Oral SARS-CoV-2 3C-Like Protease Inhibitor

Coproporphyrin-I (CP-I) has been investigated as an endogenous biomarker of organic anion transporting polypeptide (OATP) 1B. Here, we determined the CP-I concentrations in a cocktail drug-drug interaction (DDI) study of ensitrelvir to evaluate the OATP1B inhibitory potential because ensitrelvir had increased plasma concentrations of rosuvastatin in this study, raising concerns about breast cancer resistance protein and OATP1B inhibition. Furthermore, CP-I concentrations were compared between active and placebo groups in a first-in-human (FIH) study of ensitrelvir to verify whether the OATP1B inhibitory potential could be estimated at an early drug development stage. In the cocktail DDI study, CP-I did not differ between with/without administration of ensitrelvir, indicating that ensitrelvir has no OATP1B inhibitory effect. Although there were some individual variabilities in CP-I concentrations among the treatment groups in the FIH study, the normalization of CP-I concentrations with pre-dose values minimized these variabilities, suggesting that this normalized method would be helpful for comparing the CP-I from different participants. Finally, we concluded that CP-I concentrations were not affected by ensitrelvir in the FIH study. These results suggested that the CP-I determination in an FIH study and its normalized method can be useful for an early evaluation of the OATP1B-mediated DDI potential in humans.

Identification and characterization of endogenous biomarkers for hepatic vectorial transport (OATP1B3-P-gp) function using metabolomics with serum pharmacology

The organic anion-transporting polypeptide 1B3 and P-glycoprotein (P-gp) provide efficient directional transport (OATP1B3-P-gp) from the blood to the bile that serves as a key determinant of hepatic disposition of the drug. Unfortunately, there is still a lack of effective means to evaluate the disposal ability mediated by transporters. The present study was designed to identify a suitable endogenous biomarker for the assessment of OATP1B3-P-gp function in the liver. We established stably transfected HEK293T-OATP1B3 and HEK293T-P-gp cell lines. Results showed that azelaic acid (AzA) was an endogenous substrate for OATP1B3 and P-gp using serum pharmacology combined with metabolomics. There is a good correlation between the serum concentration of AzA and probe drugs of rOATP1B3 and rP-gp when rats were treated with their inhibitors. Importantly, after 5-fluorouracil-induced rat liver injury, the relative mRNA level and expression of rOATP1B3 and rP-gp were markedly down-regulated in the liver, and the serum concentration of AzA was significantly increased. These observations suggest that AzA is an endogenous substrate of both OATP1B3 and P-gp, and may serve as a potential endogenous biomarker for the assessment of the function of OATP1B3-P-gp for the prediction of changes in the pharmacokinetics of drugs transported by OATP1B3-P-gp in liver disease states.

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

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 (Cmax R) and AUCR of substrate drugs. In general, the CP-I Cmax R was equal to or greater than the CP-I AUCR. CP-I Cmax R < 1.25 was associated with absence of OATP1B-mediated DDIs (AUCR < 1.25) with no false negative predictions. CP-I Cmax 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.

The influence of OATP2B1 and atorvastatin on coproporphyrin isomers in rats

Coproporphyrin I (CPI) and III (CPIII) are discussed as biomarkers for organic anion transporting polypeptides (OATPs). We report on CPI and CPIII levels in wildtype, rSlco2b1-knockout, and SLCO2B1-humanized rats at baseline and after administration of atorvastatin, an inhibitor of the CPIII-specific rOATP2B1/hOATP2B1 and the CPI/CPIII-transporting rOATP1B2. OATP-inhibition by atorvastatin leads to significantly increased CPI and CPIII serum levels. However, basal CP serum levels in rSlco2b1-knockout animals were significantly lower (CPI), or unaffected (CPIII). In the presence of atorvastatin, this genotype effect was abolished. In conclusion, our results indicate an unexpected impact of OATP2B1 on CP serum levels in rats.

A 20-Year Research Overview: Quantitative Prediction of Hepatic Clearance Using the In Vitro-In Vivo Extrapolation Approach Based on Physiologically Based Pharmacokinetic Modeling and Extended Clearance Concept

Understanding the extended clearance concept and establishing a physiologically based pharmacokinetic (PBPK) model are crucial for investigating the impact of changes in transporter and metabolizing enzyme abundance/functions on drug pharmacokinetics in blood and tissues. This mini-review provides an overview of the extended clearance concept and a PBPK model that includes transporter-mediated uptake processes in the liver. In general, complete in vitro and in vivo extrapolation (IVIVE) poses challenges due to missing factors that bridge the gap between in vitro and in vivo systems. By considering key in vitro parameters, we can capture in vivo pharmacokinetics, a strategy known as the top-down or middle-out approach. We present the latest progress, theory, and practice of the Cluster Gauss-Newton method, which is used for middle-out analyses. As examples of poor IVIVE, we discuss "albumin-mediated hepatic uptake" and "time-dependent inhibition" of OATP1Bs. The hepatic uptake of highly plasma-bound drugs is more efficient than what can be accounted for by their unbound concentration alone. This phenomenon is referred to as "albumin-mediated" hepatic uptake. IVIVE was improved by measuring hepatic uptake clearance in vitro in the presence of physiologic albumin concentrations. Lastly, we demonstrate the application of Cluster Gauss-Newton method-based analysis to the target-mediated drug disposition of bosentan. Incorporating saturable target binding and OATP1B-mediated hepatic uptake into the PBPK model enables the consideration of nonlinear kinetics across a wide dose range and the prediction of receptor occupancy over time. SIGNIFICANCE STATEMENT: There have been multiple instances where researchers' endeavors to unravel the underlying mechanism of poor in vitro-in vivo extrapolation have led to the discovery of previously undisclosed truths. These include 1) albumin-mediated hepatic uptake, 2) the target-mediated drug disposition in small molecules, and 3) the existence of a trans-inhibition mechanism by inhibitors for OATP1B-mediated hepatic uptake of drugs. Consequently, poor in vitro-in vivo extrapolation and the subsequent inquisitiveness of scientists may serve as a pivotal gateway to uncover hidden mechanisms.

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.

Use of In Vivo Imaging and Physiologically-Based Kinetic Modelling to Predict Hepatic Transporter Mediated Drug-Drug Interactions in Rats

Gadoxetate, a magnetic resonance imaging (MRI) contrast agent, is a substrate of organic-anion-transporting polypeptide 1B1 and multidrug resistance-associated protein 2. Six drugs, with varying degrees of transporter inhibition, were used to assess gadoxetate dynamic contrast enhanced MRI biomarkers for transporter inhibition in rats. Prospective prediction of changes in gadoxetate systemic and liver AUC (AUCR), resulting from transporter modulation, were performed by physiologically-based pharmacokinetic (PBPK) modelling. A tracer-kinetic model was used to estimate rate constants for hepatic uptake (khe), and biliary excretion (kbh). The observed median fold-decreases in gadoxetate liver AUC were 3.8- and 1.5-fold for ciclosporin and rifampicin, respectively. Ketoconazole unexpectedly decreased systemic and liver gadoxetate AUCs; the remaining drugs investigated (asunaprevir, bosentan, and pioglitazone) caused marginal changes. Ciclosporin decreased gadoxetate khe and kbh by 3.78 and 0.09 mL/min/mL, while decreases for rifampicin were 7.20 and 0.07 mL/min/mL, respectively. The relative decrease in khe (e.g., 96% for ciclosporin) was similar to PBPK-predicted inhibition of uptake (97-98%). PBPK modelling correctly predicted changes in gadoxetate systemic AUCR, whereas underprediction of decreases in liver AUCs was evident. The current study illustrates the modelling framework and integration of liver imaging data, PBPK, and tracer-kinetic models for prospective quantification of hepatic transporter-mediated DDI in humans.

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.

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.

Isotretinoin and its Metabolites Alter mRNA of Multiple Enzyme and Transporter Genes In Vitro, but Downregulation of Organic Anion Transporting Polypeptide Does Not Translate to the Clinic

Isotretinoin [13-cis-retinoic acid (13cisRA)] is widely used for the treatment of neuroblastoma and acne. It acts via regulating gene transcription through binding to retinoic acid receptors. Yet, the potential for isotretinoin to cause transcriptionally mediated drug-drug interactions (DDIs) has not been fully explored. We hypothesized that isotretinoin and its active metabolites all-trans-retinoic acid (atRA) and 4-oxo-13cisRA would alter the transcription of enzymes and transporters in the human liver via binding to nuclear receptors. The goal of this study was to define the DDI potential of isotretinoin and its metabolites resulting from transcriptional regulation of cytochrome P450 and transporter mRNAs. In human hepatocytes (n = 3), 13cisRA, atRA, and 4-oxo-13cisRA decreased OATP1B1, CYP1A2, CYP2C9, and CYP2D6 mRNA and increased CYP2B6 and CYP3A4 mRNA in a concentration-dependent manner. The EC50 values for OATP1B1 mRNA downregulation ranged from 2 to 110 nM, with maximum effect (Emax ) ranging from 0.17- to 0.54-fold. Based on the EC50 and Emax values and the known circulating concentrations of 13cisRA and its metabolites after isotretinoin dosing, a 55% decrease in OATP1B1 activity was predicted in vivo. In vivo DDI potential was evaluated clinically in participants dosed with isotretinoin for up to 32 weeks using coproporphyrin-I (CP-I) as an OATP1B1 biomarker. CP-I steady-state serum concentrations were unaltered following 2, 8, or 16 weeks of isotretinoin treatment. These data show that isotretinoin and its metabolites alter transcription of multiple enzymes and transporters in vitro, but translation of these changes to in vivo drug-drug interactions requires clinical evaluation for each enzyme. SIGNIFICANCE STATEMENT: Isotretinoin and its metabolites alter the mRNA expression of multiple cytochrome P450s (CYPs) and transporters in human hepatocytes, suggesting that isotretinoin may cause clinically significant drug-drug interactions (DDIs). Despite the observed changes in organic anion transporting polypeptide 1B1 (OATP1B1) mRNA in human hepatocytes, no clinical DDI was observed when measuring a biomarker, coproporphyrin-I. Further work is needed to determine whether these findings can be extrapolated to a lack of a DDI with CYP1A2, CYP2B6, and CYP2C9 substrates.

Novel Insights in Drug Transporter Sciences: the Year 2021 in Review

On behalf of the team I am pleased to present the second annual 'novel insights into drug transporter sciences review' focused on peer-reviewed articles that were published in the year 2021. In compiling the articles for inclusion, preprints available in 2021 but officially published in 2022 were considered to be in scope. To support this review the contributing authors independently selected one or two articles that were thought to be impactful and of interest to the broader research community. A similar approach as published last year was adopted whereby key observations, methods and analysis of each paper is concisely summarized in the synopsis followed by a commentary highlighting the impact of the paper in understanding of drug transporters' role in drug disposition.As the goal of this review is not to provide a comprehensive overview of each paper but rather highlight important findings that are well supported by the data, the reader is encouraged to consult the original articles for additional information. Further, and keeping in line with the goals of this review, it should be noted that all authors actively contributed by writing synopsis and commentary for individual papers and no attempt was made to standardize language or writing styles. In this way, the review article is reflective of not only the diversity of the articles but also that of the contributors. I extend my thanks to the authors for their continued support and also welcome Diane Ramsden and Pallabi Mitra as contributing authors for this issue.

Coproporphyrin I as an Endogenous Biomarker to Detect Reduced OATP1B Activity and Shift in Elimination Route in Chronic Kidney Disease

Coproporphyrin I (CPI) is an endogenous biomarker of organic anion transporting polypeptide 1B transporter (OATP1B). CPI plasma baseline was reported to increase with severity of chronic kidney disease (CKD). Further, ratio of CPI area under the plasma concentration-time curve (AUCR) in the presence/absence of OATP1B inhibitor rifampin was higher in patients with CKD compared with healthy participants, in contrast to pitavastatin (a clinical OATP1B probe). This study investigated mechanism(s) contributing to altered CPI baseline in patients with CKD by extending a previously developed physiologically-based pharmacokinetic (PBPK) model to this patient population. CKD-related covariates were evaluated in a stepwise manner on CPI fraction unbound in plasma (f_u,p ), OATP1B-mediated hepatic uptake clearance (CL_active ), renal clearance (CL_R ), and endogenous synthesis (k_syn ). The CPI model successfully recovered increased baseline and rifampin-mediated AUCR in patients with CKD by accounting for the following disease-related changes: 13% increase in f_u,p , 29% and 39% decrease in CL_active in mild and moderate to severe CKD, respectively, decrease in CL_R proportional to decline in glomerular filtration rate, and 27% decrease in k_syn in severe CKD. Almost complete decline in CPI renal elimination in severe CKD increased its fraction transported by OATP1B, rationalizing differences in the CPI-rifampin interaction observed between healthy participants and patients with CKD. In conclusion, mechanistic modeling performed here supports CKD-related decrease in OATP1B function to inform prospective PBPK modeling of OATP1B-mediated drug-drug interaction in these patients. Monitoring of CPI allows detection of CKD-drug interaction risk for OATP1B drugs with combined hepatic and renal elimination which may be underestimated by extrapolating the interaction risk based on pitavastatin data in healthy participants.

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.

The pharmacokinetics of oral trazpiroben (TAK-906) after organic anion transporting polypeptide 1B1/1B3 inhibition: A phase I, randomized study

Trazpiroben is a dopamine D₂/D₃ receptor antagonist under development for the treatment of gastroparesis. This phase I, open‐label, randomized, two‐way crossover study (NCT04121078) evaluated the effect of single‐dose intravenous rifampin, a potent inhibitor of the organic anion transporting polypeptides (OATPs) 1B1 and 1B3, on the pharmacokinetics and safety of trazpiroben in healthy adults. The utility of coproporphyrin (CP) I and CPIII as biomarkers of OATP inhibition was also assessed. Overall, 12 participants were enrolled and randomized (1:1) into one of two treatment sequences (AB and BA). Participants received either a single oral dose of trazpiroben 25 mg (treatment A) or a single oral dose of trazpiroben 25 mg immediately after a single 30‐min intravenous infusion of rifampin 600 mg (treatment B). After a washout period of at least 7 days, participants received the other treatment. Geometric mean area under the curve from time 0 extrapolated to infinity (AUC_∞) and maximum serum concentration (C_max) of plasma trazpiroben were higher in participants receiving treatment B than those receiving treatment A (AUC_∞, 168.5 vs. 32.68 ng*h/ml; C_max, 89.62 vs. 14.37 ng/ml); corresponding geometric mean ratios (90% confidence interval) showed 5.16 (4.25–6.25) and 6.24 (4.62–8.42)‐fold increases in these parameters, respectively. In this study, trazpiroben was confirmed as a substrate of OATP1B1/1B3, and therefore co‐administration of trazpiroben with moderate to strong inhibitors of OATP1B1/1B3 is not recommended. This is also the first assessment of the utility of CPI and CPIII as endogenous biomarkers of OATP1B1/1B3 inhibition after a single intravenous dose of rifampin.

Acute and Chronic Effects of Rifampin on Letermovir Suggest Transporter Inhibition and Induction Contribute to Letermovir Pharmacokinetics

Rifampin has acute inhibitory and chronic inductive effects that can cause complex drug-drug interactions. Rifampin inhibits transporters including organic-anion-transporting polypeptide (OATP)1B and P-glycoprotein (P-gp), and induces enzymes and transporters including cytochrome P450 3A, UDP-glucuronosyltransferase (UGT)1A, and P-gp. This study aimed at separating inhibitory and inductive effects of rifampin on letermovir disposition and elimination (indicated for cytomegalovirus prophylaxis in hematopoietic stem cell transplant recipients). Letermovir is a substrate of UGT1A1/3, P-gp, and OATP1B, with its clearance primarily mediated by OATP1B. Letermovir (single-dose) administered with rifampin (single-dose) resulted in increased letermovir exposure through transporter inhibition. Chronic coadministration with rifampin (inhibition plus potential OATP1B induction) resulted in modestly decreased letermovir exposure versus letermovir alone. Letermovir administered 24 hours after last rifampin dose (potential OATP1B induction) resulted in markedly decreased letermovir exposure. These data suggest rifampin may induce transporters that clear letermovir; the modestly reduced letermovir exposure with chronic rifampin coadministration likely reflects the net effect of inhibition and induction. OATP1B endogenous biomarkers coproporphyrin (CP) I and glycochenodeoxycholic acid-sulfate (GCDCA-S) were also analyzed; their exposures increased after single-dose rifampin plus letermovir, consistent with OATP1B inhibition and prior reports of inhibition by rifampin alone. CP I and GCDCA-S exposures were substantially reduced with letermovir administered 24 hours after the last dose of rifampin versus letermovir plus chronic rifampin coadministration, This study suggests that OATP1B induction may contribute to reduced letermovir exposure after chronic rifampin administration, although given the complexity of letermovir disposition, alternative mechanisms are not fully excluded.

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.

Recent Advances in Drug Transporter Sciences: Highlights From the Year 2020

Drug Metabolism Reviews has an impressive track record of providing scientific reviews in the area of xenobiotic biotransformation over 47 years. It has consistently proved to be resourceful to many scientists from pharmaceutical industry, academia, regulatory agencies working in diverse areas including enzymology, pharmacology, pharmacokinetics and toxicology. Over the last 5 years Drug metabolism Reviews has annually published an industry commentary aimed to highlight novel insights and approaches that have made significant impacts on the field of biotransformation (led by Cyrus Khojasteh). We hope to continue this tradition by providing an overview of advances made in the field of drug transporters during 2020. The field of drug transporters is rapidly evolving as they play an essential role in drug absorption, distribution, clearance and elimination. In this review we have selected outstanding drug transporter articles that have significantly contributed to moving forward the field of transporter science with respect to translation and improved understanding of diverse aspects including uptake clearance, clinical biomarkers, induction, proteomics, emerging transporters and tissue targeting.The theme of this review consists of synopsis that summarizes each article followed by our commentary. The objective of this work is not to provide a comprehensive review but rather exemplify novel insights and state-of-the-art highlights of recent research that have advanced our understanding of drug transporters in drug disposition. We are hopeful that this effort will prove useful to the scientific community and as such request feedback, and further extend an invitation to anyone interested in contributing to future reviews.

Physiologically Based Pharmacokinetic Modeling of Transporter-Mediated Hepatic Disposition of Imaging Biomarker Gadoxetate in Rats

Physiologically based pharmacokinetic (PBPK) models are increasingly used in drug development to simulate changes in both systemic and tissue exposures that arise as a result of changes in enzyme and/or transporter activity. Verification of these model-based simulations of tissue exposure is challenging in the case of transporter-mediated drug–drug interactions (tDDI), in particular as these may lead to differential effects on substrate exposure in plasma and tissues/organs of interest. Gadoxetate, a promising magnetic resonance imaging (MRI) contrast agent, is a substrate of organic-anion-transporting polypeptide 1B1 (OATP1B1) and multidrug resistance-associated protein 2 (MRP2). In this study, we developed a gadoxetate PBPK model and explored the use of liver-imaging data to achieve and refine in vitro–in vivo extrapolation (IVIVE) of gadoxetate hepatic transporter kinetic data. In addition, PBPK modeling was used to investigate gadoxetate hepatic tDDI with rifampicin i.v. 10 mg/kg. In vivo dynamic contrast-enhanced (DCE) MRI data of gadoxetate in rat blood, spleen, and liver were used in this analysis. Gadoxetate in vitro uptake kinetic data were generated in plated rat hepatocytes. Mean (%CV) in vitro hepatocyte uptake unbound Michaelis–Menten constant (K_m,u) of gadoxetate was 106 μM (17%) (n = 4 rats), and active saturable uptake accounted for 94% of total uptake into hepatocytes. PBPK–IVIVE of these data (bottom-up approach) captured reasonably systemic exposure, but underestimated the in vivo gadoxetate DCE–MRI profiles and elimination from the liver. Therefore, in vivo rat DCE–MRI liver data were subsequently used to refine gadoxetate transporter kinetic parameters in the PBPK model (top-down approach). Active uptake into the hepatocytes refined by the liver-imaging data was one order of magnitude higher than the one predicted by the IVIVE approach. Finally, the PBPK model was fitted to the gadoxetate DCE–MRI data (blood, spleen, and liver) obtained with and without coadministered rifampicin. Rifampicin was estimated to inhibit active uptake transport of gadoxetate into the liver by 96%. The current analysis highlighted the importance of gadoxetate liver data for PBPK model refinement, which was not feasible when using the blood data alone, as is common in PBPK modeling applications. The results of our study demonstrate the utility of organ-imaging data in evaluating and refining PBPK transporter IVIVE to support the subsequent model use for quantitative evaluation of hepatic tDDI.

Population pharmacokinetic modeling and simulation to support qualification of pyridoxic acid as endogenous biomarker of OAT1/3 renal transporters

Renal clearance of many drugs is mediated by renal organic anion transporters OAT1/3 and inhibition of these transporters may lead to drug‐drug interactions (DDIs). Pyridoxic acid (PDA) and homovanillic acid (HVA) were indicated as potential biomarkers of OAT1/3. The objective of this study was to develop a population pharmacokinetic model for PDA and HVA to support biomarker qualification. Simultaneous fitting of biomarker plasma and urine data in the presence and absence of potent OAT1/3 inhibitor (probenecid, 500 mg every 6 h) was performed. The impact of study design (multiple vs. single dose of OAT1/3 inhibitor) and ability to detect interactions in the presence of weak/moderate OAT1/3 inhibitors was investigated, together with corresponding power calculations. The population models developed successfully described biomarker baseline and PDA/HVA OAT1/3‐mediated interaction data. No prominent effect of circadian rhythm on PDA and HVA individual baseline levels was evident. Renal elimination contributed greater than 80% to total clearance of both endogenous biomarkers investigated. Estimated probenecid unbound in vivo OAT inhibitory constant was up to 6.4‐fold lower than in vitro values obtained with PDA as a probe. The PDA model was successfully verified against independent literature reported datasets. No significant difference in power of DDI detection was found between multiple and single dose study design when using the same total daily dose of 2000 mg probenecid. Model‐based simulations and power calculations confirmed sensitivity and robustness of plasma PDA data to identify weak, moderate, and strong OAT1/3 inhibitors in an adequately powered clinical study to support optimal design of prospective clinical OAT1/3 interaction studies.

Further Evaluation of Coproporphyrins as Clinical Endogenous Markers for OATP1B

Coproporphyrins (CP-I and CP-III) in plasma are considered potential markers for assessing liver organic anion-transporting polypeptide transporter OATP1B activity and monitoring OATP1B-mediated drug-drug interactions (DDIs) in clinical settings. However, the effect of altered renal clearance (CL_renal ) on CP-I and CP-III plasma exposure has rarely been examined. Therefore, the purpose of this study is to further evaluate CP-I and CP-III as clinical endogenous markers for OATP1B activity and to investigate the impact of CL_renal on DDI assessments for the first time. In this study, 18 healthy participants were recruited to receive RO7049389 (a potential inhibitor of OATP1B) 800 mg twice daily for 6 days and a single dose of pitavastatin (a probe drug of OATP1B) before and after RO7049389 treatment. Plasma concentrations of pitavastatin, CP I, CP III, and the amounts of CP-I and CP-III excreted in urine were measured. Seventeen healthy participants completed the study. After multiple doses of RO7049389, the area under the plasma concentration-time curve from time 0 to 12 hours of pitavastatin increased 1.95-fold (90% confidence interval [CI], 1.58-2.41), while for CP-I and CP-III it increased 3.00-fold (90%CI, 2.35-3.82) and 2.84-fold (90%CI, 2.22-3.65), respectively. Concurrently, the CL_renal of CP-I decreased by 31% (90%CI, 23%-39%), and that of CP-III decreased by 70% (90%CI, 61%-77%). In conclusion, CP-I and CP-III in plasma display the potential to be applied as endogenous markers for the evaluation of OATP1B inhibition in clinical trials. While renal transporters contribute significantly to the CL_renal of CP-III, it would be better to investigate the impact of the CL_renal on plasma exposure of CP-III during clinical DDI assessments.

Clinical Investigation on Endogenous Biomarkers to Predict Strong OAT-Mediated Drug-Drug Interactions

BACKGROUND

Endogenous biomarkers are promising tools to assess transporter-mediated drug-drug interactions early in humans.

METHODS

We evaluated on a common and validated in vitro system the selectivity of 4-pyridoxic acid (PDA), homovanillic acid (HVA), glycochenodeoxycholate-3-sulphate (GCDCA-S) and taurine towards different renal transporters, including multidrug resistance-associated protein, and assessed the in vivo biomarker sensitivity towards the strong organic anion transporter (OAT) inhibitor probenecid at 500 mg every 6 h to reach close to complete OAT inhibition.

RESULTS

PDA and HVA were substrates of the OAT1/2/3, OAT4 (PDA only) and multidrug resistance-associated protein 4; GCDCA-S was more selective, having affinity only towards OAT3 and multidrug resistance-associated protein 2. Taurine was not a substrate of any of the investigated transporters under the in vitro conditions tested. Plasma exposure of PDA and HVA significantly increased and the renal clearance of GCDCA-S, PDA and HVA decreased; the magnitude of these changes was comparable to those of known clinical OAT probe substrates. PDA and GCDCA-S were the most promising endogenous biomarkers of the OAT pathway activity: PDA plasma exposure was the most sensitive to probenecid inhibition, and, in contrast, GCDCA-S was the most sensitive OAT biomarker based on renal clearance, with higher selectivity towards the OAT3 transporter.

CONCLUSIONS

The current findings illustrate a clear benefit of measuring PDA plasma exposure during phase I studies when a clinical drug candidate is suspected to be an OAT inhibitor based on in vitro data. Subsequently, combined monitoring of PDA and GCDCA-S in both urine and plasma is recommended to tease out the involvement of OAT1/3 in the inhibition interaction.

CLINICAL TRIAL REGISTRATION

EudraCT number: 2016-003923-49.

Hepatic transporter-mediated pharmacokinetic drug-drug interactions: Recent studies and regulatory recommendations

Transporter-mediated drug-drug interactions are one of the major mechanisms in pharmacokinetic-based drug interactions and correspondingly affecting drugs' safety and efficacy. Regulatory bodies underlined the importance of the evaluation of transporter-mediated interactions as a part of the drug development process. The liver is responsible for the elimination of a wide range of endogenous and exogenous compounds via metabolism and biliary excretion. Therefore, hepatic uptake transporters, expressed on the sinusoidal membranes of hepatocytes, and efflux transporters mediating the transport from hepatocytes to the bile are determinant factors for pharmacokinetics of drugs, and hence, drug-drug interactions. In parallel with the growing research interest in this area, regulatory guidances have been updated with detailed assay models and criteria. According to well-established preclinical results, observed or expected hepatic transporter-mediated drug-drug interactions can be taken into account for clinical studies. In this paper, various methods including in vitro, in situ, in vivo, in silico approaches, and combinational concepts and several clinical studies on the assessment of transporter-mediated drug-drug interactions were reviewed. Informative and effective evaluation by preclinical tools together with the integration of pharmacokinetic modeling and simulation can reduce unexpected clinical outcomes and enhance the success rate in drug development.

PBPK Model of Coproporphyrin I: Evaluation of the Impact of SLCO1B1 Genotype, Ethnicity, and Sex on its Inter-Individual Variability

Coproporphyrin I (CPI) is an endogenous biomarker of OATP1B activity and associated drug-drug interactions. In this study, a minimal physiologically-based pharmacokinetic model was developed to investigate the impact of OATP1B1 genotype (c.521T>C), ethnicity, and sex on CPI pharmacokinetics and interindividual variability in its baseline. The model implemented mechanistic descriptions of CPI hepatic transport between liver blood and liver tissue and renal excretion. Key model parameters (e.g., endogenous CPI synthesis rate, and CPI hepatic uptake clearance) were estimated by fitting the model simultaneously to three independent CPI clinical datasets (plasma and urine data) obtained from white (n = 16, men and women) and Asian-Indian (n = 26, all men) subjects, with c.521 variants (TT, TC, and CC). The optimized CPI model successfully described the observed data using c.521T>C genotype, ethnicity, and sex as covariates. CPI hepatic active was 79% lower in 521CC relative to the wild type and 42% lower in Asian-Indians relative to white subjects, whereas CPI synthesis was 23% higher in male relative to female subjects. Parameter sensitivity analysis showed marginal impact of the assumption of CPI synthesis site (blood or liver), resulting in comparable recovery of plasma and urine CPI data. Lower magnitude of CPI-drug interaction was simulated in 521CC subjects, suggesting the risk of underestimation of CPI-drug interaction without prior OATP1B1 genotyping. The CPI model incorporates key covariates contributing to interindividual variability in its baseline and highlights the utility of the CPI modeling to facilitate the design of prospective clinical studies to maximize the sensitivity of this biomarker.

Assessing Transporter-Mediated Natural Product-Drug Interactions Via In vitro-In Vivo Extrapolation: Clinical Evaluation With a Probe Cocktail

The botanical natural product goldenseal can precipitate clinical drug interactions by inhibiting cytochrome P450 (CYP) 3A and CYP2D6. Besides P-glycoprotein, effects of goldenseal on other clinically relevant transporters remain unknown. Established transporter-expressing cell systems were used to determine the inhibitory effects of a goldenseal extract, standardized to the major alkaloid berberine, on transporter activity. Using recommended basic models, the extract was predicted to inhibit the efflux transporter BCRP and uptake transporters OATP1B1/3. Using a cocktail approach, effects of the goldenseal product on BCRP, OATP1B1/3, OATs, OCTs, MATEs, and CYP3A were next evaluated in 16 healthy volunteers. As expected, goldenseal increased the area under the plasma concentration-time curve (AUC_0-inf ) of midazolam (CYP3A; positive control), with a geometric mean ratio (GMR) (90% confidence interval (CI)) of 1.43 (1.35-1.53). However, goldenseal had no effects on the pharmacokinetics of rosuvastatin (BCRP and OATP1B1/3) and furosemide (OAT1/3); decreased metformin (OCT1/2, MATE1/2-K) AUC_0-inf (GMR, 0.77 (0.71-0.83)); and had no effect on metformin half-life and renal clearance. Results indicated that goldenseal altered intestinal permeability, transport, and/or other processes involved in metformin absorption, which may have unfavorable effects on glucose control. Inconsistencies between model predictions and pharmacokinetic outcomes prompt further refinement of current basic models to include differential transporter expression in relevant organs and intestinal degradation/metabolism of the precipitant(s). Such refinement should improve in vitro-in vivo prediction accuracy, contributing to a standard approach for studying transporter-mediated natural product-drug interactions.

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

Organic anion transporting polypeptide (OATP) 1B1 and OATP1B3 are involved in the disposition of a variety of commonly prescribed drugs. The evaluation of OATP1B1/1B3 inhibition potential by investigational drugs is of interest during clinical drug development due to various adverse events associated with increased exposures of their substrates. Regulatory guidance documents on the in vitro assessment of OATP1B1/1B3 inhibition potential are conservative with up to a third of predictions resulting in false positives. This work investigated the utility of OATP1B1/1B3 endogenous biomarkers, coproporphyrin (CP)‐I and CP‐III, to assess clinical inhibition of OATP1B1/1B3 and potentially eliminate the need for prospective clinical drug‐drug interaction (DDI) studies. Correlations between CP‐I exposures and various OATP1B1 static DDI predictions were also evaluated. Glecaprevir/pibrentasvir (GLE/PIB) 300/120 mg fixed‐dose combination is known to cause clinical inhibition of OATP1B1/1B3. In a clinical study evaluating the relative bioavailability of various formulations of GLE/PIB regimen, CP‐I peak plasma concentration (C_max) ratio and 0–16‐hour area under the concentration‐time curve (AUC_0–16) ratio relative to baseline increased with increasing GLE exposures, whereas there was a modest correlation between GLE exposure and CP‐III C_max ratio but no correlation with CP‐III AUC_0–16 ratio. This suggests that CP‐I is superior to CP‐III as an endogenous biomarker for evaluation of OATP1B1 inhibition. There was a significant correlation between CP‐I and GLE C_max (R² = 0.65; P < 0.001) across individual subjects. Correlation analysis between GLE OATP1B1 R values and CP‐I exposures (C_max ratio and AUC_0–16 ratio) suggests that an R value of > 3 can predict a biologically meaningful inhibition of OATP1B1 when the inhibitor clinical pharmacokinetic parameters are available.

Current status and future directions of high-throughput ADME screening in drug discovery

During the last decade high-throughput in vitro absorption, distribution, metabolism and excretion (HT-ADME) screening has become an essential part of any drug discovery effort of synthetic molecules. The conduct of HT-ADME screening has been "industrialized" due to the extensive development of software and automation tools in cell culture, assay incubation, sample analysis and data analysis. The HT-ADME assay portfolio continues to expand in emerging areas such as drug-transporter interactions, early soft spot identification, and ADME screening of peptide drug candidates. Additionally, thanks to the very large and high-quality HT-ADME data sets available in many biopharma companies, in silico prediction of ADME properties using machine learning has also gained much momentum in recent years. In this review, we discuss the current state-of-the-art practices in HT-ADME screening including assay portfolio, assay automation, sample analysis, data processing, and prediction model building. In addition, we also offer perspectives in future development of this exciting field.

Alteration in the Plasma Concentrations of Endogenous Organic Anion-Transporting Polypeptide 1B Biomarkers in Patients with Non-Small Cell Lung Cancer Treated with Paclitaxel

Paclitaxel has been considered to cause OATP1B-mediated drug-drug interactions at therapeutic doses; however, its clinical relevance has not been demonstrated. This study aimed to elucidate in vivo inhibition potency of paclitaxel against OATP1B1 and OATP1B3 using endogenous OATP1B biomarkers. Paclitaxel is an inhibitor of OATP1B1 and OATP1B3, with K_i of 0.579 ± 0.107 and 5.29 ± 3.87 μM, respectively. Preincubation potentiated its inhibitory effect on both OATP1B1 and OATP1B3, with K_i of 0.154 ± 0.031 and 0.624 ± 0.183 μM, respectively. Ten patients with non-small cell lung cancer who received 200 mg/m² of paclitaxel by a 3-hour infusion were recruited. Plasma concentrations of 10 endogenous OATP1B biomarkers-namely, coproporphyrin I, coproporphyrin III, glycochenodeoxycholate-3-sulfate, glycochenodeoxycholate-3-glucuronide, glycodeoxycholate-3-sulfate, glycodeoxycholate-3-glucuronide, lithocholate-3-sulfate, glycolithocholate-3-sulfate, taurolithocholate-3-sulfate, and chenodeoxycholate-24-glucuronide-were determined in the patients with non-small cell lung cancer on the day before paclitaxel administration and after the end of paclitaxel infusion for 7 hours. Paclitaxel increased the area under the plasma concentration-time curve (AUC) of the endogenous biomarkers 2- to 4-fold, although a few patients did not show any increment in the AUC ratios of lithocholate-3-sulfate, glycolithocholate-3-sulfate, and taurolithocholate-3-sulfate. Therapeutic doses of paclitaxel for the treatment of non-small cell lung cancer (200 mg/m²) will cause significant OATP1B1 inhibition during and at the end of the infusion. This is the first demonstration that endogenous OATP1B biomarkers could serve as surrogate biomarkers in patients. SIGNIFICANCE STATEMENT: Endogenous biomarkers can address practical and ethical issues in elucidating transporter-mediated drug-drug interaction (DDI) risks of anticancer drugs clinically. We could elucidate a significant increment of the plasma concentrations of endogenous OATP1B biomarkers after a 3-hour infusion (200 mg/m²) of paclitaxel, a time-dependent inhibitor of OATP1B, in patients with non-small cell lung cancer. The endogenous OATP1B biomarkers are useful to assess the possibility of OATP1B-mediated DDIs in patients and help in appropriately designing a dosing schedule to avoid the DDIs.

Recent progress in in vivo phenotyping technologies for better prediction of transporter-mediated drug-drug interactions

Clinical reports on transporter-mediated drug-drug interactions (TP-DDIs) have rapidly accumulated and regulatory guidance/guidelines recommend that sponsors consider performing quantitative prediction of TP-DDI risks in the process of drug development. In vitro experiments for characterizing the function of drug transporters have been established and various parameters such as the inhibition constant (K_i) of drugs and the intrinsic uptake/efflux clearance for a certain transporter can be obtained. However, many reports have indicated large discrepancies between the parameters estimated from in vitro experiments and those rationally explaining drug pharmacokinetics. Thus, it is essential to evaluate directly the function of each transporter isoform in vivo in humans. At present, several transporter substrate drugs and endogenous compounds have been recognized as probe substrates for a specific transporter and transporter function was evaluated by monitoring the plasma and urine concentration of those probes; however, few compounds specifically transported via a single transporter isoform have been found. For monitoring the intraorgan concentration of drugs, positron emission tomography can be a powerful tool and clinical examples for quantification of in vivo transporter function have been published. In this review, novel methodologies for in vivo phenotyping of transporter function are summarized.

Dose-Dependent Inhibition of OATP1B by Rifampicin in Healthy Volunteers: Comprehensive Evaluation of Candidate Biomarkers and OATP1B Probe Drugs

To address the most appropriate endogenous biomarker for drug–drug interaction risk assessment, eight healthy subjects received an organic anion transporting polypeptide 1B (OATP1B) inhibitor (rifampicin, 150, 300, and 600 mg), and a probe drug cocktail (atorvastatin, pitavastatin, rosuvastatin, and valsartan). In addition to coproporphyrin I, a widely studied OATP1B biomarker, we identified at least 4 out of 28 compounds (direct bilirubin, glycochenodeoxycholate‐3‐glucuronide, glycochenodeoxycholate‐3‐sulfate, and hexadecanedioate) that presented good sensitivity and dynamic range in terms of the rifampicin dose‐dependent change in area under the plasma concentration‐time curve ratio (AUCR). Their suitability as OATP1B biomarkers was also supported by the good correlation of AUC_0‐24h between the endogenous compounds and the probe drugs, and by nonlinear regression analysis (AUCR⁻¹ vs. rifampicin plasma C_max (maximum total concentration in plasma)) to yield an estimate of the inhibition constant of rifampicin. These endogenous substrates can complement existing OATP1B‐mediated drug–drug interaction risk assessment approaches based on agency guidelines in early clinical trials.

Perspectives from the Innovation and Quality Consortium Induction Working Group on Factors Impacting Clinical Drug-Drug Interactions Resulting from Induction: Focus on Cytochrome 3A Substrates

A recent publication from the Innovation and Quality Consortium Induction Working Group collated a large clinical data set with the goal of evaluating the accuracy of drug-drug interaction (DDI) prediction from in vitro data. Somewhat surprisingly, comparison across studies of the mean- or median-reported area under the curve ratio showed appreciable variability in the magnitude of outcome. This commentary explores the possible drivers of this range of outcomes observed in clinical induction studies. While recommendations on clinical study design are not being proposed, some key observations were informative during the aggregate analysis of clinical data. Although DDI data are often presented using median data, individual data would enable evaluation of how differences in study design, baseline expression, and the number of subjects contribute. Since variability in perpetrator pharmacokinetics (PK) could impact the overall DDI interpretation, should this be routinely captured? Maximal induction was typically observed after 5-7 days of dosing. Thus, when the half-life of the inducer is less than 30 hours, are there benefits to a more standardized study design? A large proportion of CYP3A4 inducers were also CYP3A4 inhibitors and/or inactivators based on in vitro data. In these cases, using CYP3A selective substrates has limitations. More intensive monitoring of changes in area under the curve over time is warranted. With selective CYP3A substrates, the net effect was often inhibition, whereas less selective substrates could discern induction through mechanisms not susceptible to inhibition. The latter included oral contraceptives, which raise concerns of reduced efficacy following induction. Alternative approaches for modeling induction, such as applying biomarkers and physiologically based pharmacokinetic modeling (PBPK), are also considered. SIGNIFICANCE STATEMENT: The goal of this commentary is to stimulate discussion on whether there are opportunities to optimize clinical drug-drug interaction study design. The overall aim is to reduce, understand and contextualize the variability observed in the magnitude of induction across reported clinical studies. A large clinical CYP3A induction dataset was collected and further analyzed to identify trends and gaps. Reporting individual victim PK data, characterizing perpetrator PK and including additional PK assessments for mixed-mechanism perpetrators may provide insights into how these factors impact differences observed in clinical outcomes. The potential utility of biomarkers and PBPK modeling are discussed in considering future directions.