Survey of Pharmaceutical Industry's Best Practices around In Vitro Transporter Assessment and Implications for Drug Development: Considerations from the International Consortium for Innovation and Quality for Pharmaceutical Development Transporter Working Group

The International Consortium for Innovation and Quality in Pharmaceutical Development Transporter Working Group had a rare opportunity to analyze a crosspharma collation of in vitro data and assay methods for the evaluation of drug transporter substrate and inhibitor potential. Experiments were generally performed in accordance with regulatory guidelines. Discrepancies, such as not considering the impact of preincubation for inhibition and free or measured in vitro drug concentrations, may be due to the retrospective nature of the dataset and analysis. Lipophilicity was a frequent indicator of crosstransport inhibition (P-gp, BCRP, OATP1B, and OCT1), with high molecular weight (MW ≥500 Da) also common for OATP1B and BCRP inhibitors. A high level of overlap in in vitro inhibition across transporters was identified for BCRP, OATP1B1, and MATE1, suggesting that prediction of DDIs for these transporters will be common. In contrast, inhibition of OAT1 did not coincide with inhibition of any other transporter. Neutrals, bases, and compounds with intermediate-high lipophilicity tended to be P-gp and/or BCRP substrates, whereas compounds with MW <500 Da tended to be OAT3 substrates. Interestingly, the majority of in vitro inhibitors were not reported to be followed up with a clinical study by the submitting company, whereas those compounds identified as substrates generally were. Approaches to metabolite testing were generally found to be similar to parent testing, with metabolites generally being equally or less potent than parent compounds. However, examples where metabolites inhibited transporters in vitro were identified, supporting the regulatory requirement for in vitro testing of metabolites to enable integrated clinical DDI risk assessment. SIGNIFICANCE STATEMENT: A diverse dataset showed that transporter inhibition often correlated with lipophilicity and molecular weight (>500 Da). Overlapping transporter inhibition was identified, particularly that inhibition of BCRP, OATP1B1, and MATE1 was frequent if the compound inhibited other transporters. In contrast, inhibition of OAT1 did not correlate with the other drug transporters tested.

A 3D spheroid model of quadruple cell co-culture with improved liver functions for hepatotoxicity prediction

Drug-induced liver injury (DILI) is one of the major concerns during drug development. Wide acceptance of the 3 R principles and the innovation of in-vitro techniques have introduced various novel model options, among which the three-dimensional (3D) cell spheroid cultures have shown a promising prospect in DILI prediction. The present study developed a 3D quadruple cell co-culture liver spheroid model for DILI prediction via self-assembly. Induction by phorbol 12-myristate 13-acetate at the concentration of 15.42 ng/mL for 48 hours with a following 24-hour rest period was used for THP-1 cell differentiation, resulting in credible macrophagic phenotypes. HepG2 cells, PUMC-HUVEC-T1 cells, THP-1-originated macrophages, and human hepatic stellate cells were selected as the components, which exhibited adaptability in the designated spheroid culture conditions. Following establishment, the characterization demonstrated the competence of the model in long-term stability reflected by the maintenance of morphology, viability, cellular integration, and cell-cell junctions for at least six days, as well as the reliable liver-specific functions including superior albumin and urea secretion, improved drug metabolic enzyme expression and CYP3A4 activity, and the expression of MRP2, BSEP, and P-GP accompanied by the bile acid efflux transport function. In the comparative testing using 22 DILI-positive and 5 DILI-negative compounds among the novel 3D co-culture model, 3D HepG2 spheroids, and 2D HepG2 monolayers, the 3D culture method significantly enhanced the model sensitivity to compound cytotoxicity compared to the 2D form. The novel co-culture liver spheroid model exhibited higher overall predictive power with margin of safety as the classifying tool. In addition, the non-parenchymal cell components could amplify the toxicity of isoniazid in the 3D model, suggesting their potential mediating role in immune-mediated toxicity. The proof-of-concept experiments demonstrated the capability of the model in replicating drug-induced lipid dysregulation, bile acid efflux inhibition, and α-SMA upregulation, which are the key features of liver steatosis and phospholipidosis, cholestasis, and fibrosis, respectively. Overall, the novel 3D quadruple cell co-culture spheroid model is a reliable and readily available option for DILI prediction.

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.

Inception and development of a LC-MS/MS assay for the multiplexed quantitation of nine human drug transporter biomarkers

Background: It has become common practice to assess solute carrier transporter (SLC)-mediated drug-drug interactions (DDIs) by quantitating various individual endogenous compounds as biomarkers in human plasma and urine. The goal of this work was to develop biomarker multiplex assays that could be utilized during first in human studies to support the simultaneous assessment of clinical DDI risk across various SLCs. Methodology: Hydrophilic interaction chromatography-MS/MS methods were developed, and validations were performed. Results: The multiplex assays were applied to a first in human study. Placebo/reference subject biomarker data were consistent with single assay in-house and published data. Conclusion: This work demonstrates the utility of these multiplex methods to support the concurrent evaluation of clinical DDI risk across various SLCs.

Evaluation of the Selectivity of Several Organic Anion Transporting Polypeptide 1B Biomarkers Using Relative Activity Factor Method

In recent years, some endogenous substrates of organic anion transporting polypeptide 1B (OATP1B) have been identified and characterized as potential biomarkers to assess OATP1B-mediated clinical drug-drug interactions (DDIs). However, quantitative determination of their selectivity to OATP1B is still limited. In this study, we developed a relative activity factor (RAF) method to determine the relative contribution of hepatic uptake transporters OATP1B1, OATP1B3, OATP2B1, and sodium-taurocholate co-transporting polypeptide (NTCP) on hepatic uptake of several OATP1B biomarkers, including coproporphyrin I (CPI), coproporphyrin I CPIII, and sulfate conjugates of bile acids: glycochenodeoxycholic acid sulfate (GCDCA-S), glycodeoxycholic acid sulfate (GDCA-S), and taurochenodeoxycholic acid sulfate (TCDCA-S). RAF values for OATP1B1, OATP1B3, OATP2B1, and NTCP were determined in cryopreserved human hepatocytes and transporter transfected cells using pitavastatin, cholecystokinin, resveratrol-3-O-β-D-glucuronide, and taurocholic acid (TCA) as reference compounds, respectively. OATP1B1-specific pitavastatin uptake in hepatocytes was measured in the absence and presence of 1 µM estropipate, whereas NTCP-specific TCA uptake was measured in the presence of 10 µM rifampin. Our studies suggested that CPI was a more selective biomarker for OATP1B1 than CPIII, whereas GCDCA-S and TCDCA-S were more selective to OATP1B3. OATP1B1 and OATP1B3 equally contributed to hepatic uptake of GDCA-S. The mechanistic static model, incorporating the fraction transported of CPI/III estimated by RAF and in vivo elimination data, predicted several perpetrator interactions with CPI/III. Overall, RAF method combined with pharmacogenomic and DDI studies is a useful tool to determine the selectivity of transporter biomarkers and facilitate the selection of appropriate biomarkers for DDI evaluation. SIGNIFICANCE STATEMENT: The authors developed a new relative activity factor (RAF) method to quantify the contribution of hepatic uptake transporters organic anion transporting polypeptide (OATP)1B1, OATP1B3, OATP2B1, and sodium taurocholate co-transporting polypeptide (NTCP) on several OATP1B biomarkers and evaluated their predictive value on drug-drug interactions (DDI). These studies suggest that the RAF method is a useful tool to determine the selectivity of transporter biomarkers. This method combined with pharmacogenomic and DDI studies will mechanistically facilitate the selection of appropriate biomarkers for DDI prediction.

Glycochenodeoxycholate and glycodeoxycholate 3-O-glucuronides, but not hexadecanedioate and tetradecanedioate, detected weak inhibition of OATP1B caused by GDC-0810 in humans

Endogenous biomarkers of drug transporters are promising tools to evaluate in vivo transporter function and potential alterations in the pharmacokinetics of their substrates. We have previously reported that coproporphyrin I/III captured the weak inhibition of OATP1B transporters by GDC-0810. In this study, we measured plasma concentrations of additional biomarkers, namely fatty acids, bile acids and their sulphate or glucuronide conjugates in the presence and absence of GDC-0810. Concentrations of hexadecanedioate and tetradecanedioate did not increase in the presence of GDC-0810. Among bile acids and their conjugates, glycochenodeoxycholate and glycodeoxycholate 3-O-glucuronides (GCDCA-3G and GDCA-3G) showed C_max increases with geometric mean ratio (95% confidence interval) of 1.58 (1.13-2.22) and 1.49 (1.21-1.83), consistent with previous reports from low-dose rifampin co-administration and pharmacogenetic studies. These results suggest that GCDCA-3G and GDCA-3G are two more promising biomarkers that may capture weak OATP1B inhibition in addition to coproporphyrin I/III.

Hybrid_DBP: Prediction of DNA-binding proteins using hybrid features and convolutional neural networks

DNA-binding proteins (DBP) play an essential role in the genetics and evolution of organisms. A particular DNA sequence could provide underlying therapeutic benefits for hereditary diseases and cancers. Studying these proteins can timely and effectively understand their mechanistic analysis and play a particular function in disease prevention and treatment. The limitation of identifying DNA-binding protein members from the sequence database is time-consuming, costly, and ineffective. Therefore, efficient methods for improving DBP classification are crucial to disease research. In this paper, we developed a novel predictor Hybrid _DBP, which identified potential DBP by using hybrid features and convolutional neural networks. The method combines two feature selection methods, MonoDiKGap and Kmer, and then used MRMD2.0 to remove redundant features. According to the results, 94% of DBP were correctly recognized, and the accuracy of the independent test set reached 91.2%. This means Hybrid_ DBP can become a useful prediction tool for predicting DBP.

Blockade of Organic Anion Transport in Humans After Treatment With the Drug Probenecid Leads to Major Metabolic Alterations in Plasma and Urine

Probenecid is used to treat gout and hyperuricemia as well as increase plasma levels of antiviral drugs and antibiotics. In vivo, probenecid mainly inhibits the renal SLC22 organic anion transporters OAT1 (SLC22A6), OAT3 (SLC22A8), and URAT1 (SLC22A12). To understand the endogenous role of these transporters in humans, we administered probenecid to 20 healthy participants and metabolically profiled the plasma and urine before and after dosage. Hundreds of metabolites were significantly altered, indicating numerous drug-metabolite interactions. We focused on potential OAT1 substrates by identifying 97 metabolites that were significantly elevated in the plasma and decreased in the urine, indicating OAT-mediated clearance. These included signaling molecules, antioxidants, and gut microbiome products. In contrast, urate was the only metabolite significantly decreased in the plasma and elevated in the urine, consistent with an effect on renal reuptake by URAT1. Additional support comes from metabolomics analyses of our Oat1 and Oat3 knockout mice, where over 50% of the metabolites that were likely OAT substrates in humans were elevated in the serum of the mice. Fifteen of these compounds were elevated in both knockout mice, whereas six were exclusive to the Oat1 knockout and 4 to the Oat3 knockout. These may be endogenous biomarkers of OAT function. We also propose a probenecid stress test to evaluate kidney proximal tubule organic anion transport function in kidney disease. Consistent with the Remote Sensing and Signaling Theory, the profound changes in metabolite levels following probenecid treatment support the view that SLC22 transporters are hubs in the regulation of systemic human metabolism.

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.

Quantitative prediction of OATP1B-mediated drug-drug interactions using endogenous biomarker coproporphyrin I

1. Evaluation of the organic anion transporting polypeptide (OATP) 1B-mediated drug-drug interaction (DDI) potential is important for drug development. The focus of this study was coproporphyrin I (CP-I), an endogenous OATP1B biomarker.2. We investigated a new approach to OATP1B-mediated DDI prediction based on the mechanistic static pharmacokinetics (MSPK) model.3. The ratio of the area under the plasma concentration-time curve (AUCR) with and without co-administration of rifampicin (a typical OATP1B inhibitor) was found for CP-I and OATP1B substrate, respectively, and was then used to derive the correlation curve equation. The AUCR with and without co-administration of another OATP1B inhibitor than rifampicin was then predicted for the OATP1B substrates by substituting the AUCR of CP-I in the correlation curve equation to verify the predictability of the AUCR of the OATP1B substrates.4. The derived correlation curve equation between CP-I and the OATP1B substrates of the AUCRs with and without co-administration of rifampicin matched the observed AUCRs well. Regarding pitavastatin, rosuvastatin and pravastatin, 92.9% of the predicted AUCR values were within a two-fold range of the observed values, indicating that this approach may be a good way to quantitatively predict DDI potential.

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.

Effect of a Ketohexokinase Inhibitor (PF-06835919) on In Vivo OATP1B Activity: Integrative Risk Assessment Using Endogenous Biomarker and a Probe Drug

PF-06835919 is a first-in-class ketohexokinase inhibitor (KHKi), recently under development for the treatment of metabolic and fatty liver diseases, which inhibited organic anion transporting polypeptide (OATP)1B1 in vitro and presented drug-drug interaction (DDI) risk. This study aims to investigate the dose-dependent effect of KHKi on OATP1B in vivo activity. We performed an open-label study comparing pharmacokinetics of atorvastatin (OATP1B probe) dosed alone (20 mg single dose) and coadministered with two dose strengths of KHKi (50 and 280 mg once daily) in 12 healthy participants. Additionally, changes in exposure of coproporphyrin-I (CP-I), an endogenous biomarker for OATP1B, were assessed in the atorvastatin study (1.12-fold and 1.49-fold increase in area under the plasma concentration-time profile (AUC) with once-daily 50 and 280 mg, respectively), and a separate single oral dose study of KHKi alone (100-600 mg, n = 6 healthy participants; up to a 1.80-fold increase in AUC). Geometric mean ratios (90% confidence interval) of atorvastatin (area under the plasma concentration - time profile from time 0 extrapolated to infinite time) AUC_inf following 50 and 280 mg KHKi were 1.14 (1.00-1.30) and 1.54 (1.37-1.74), respectively. Physiologically-based pharmacokinetic modeling of CP-I plasma exposure following a single dose of KHKi predicted in vivo OATP1B inhibition from about 13% to 70% over the 100 to 600 mg dose range, while using the in vitro inhibition potency (1.9 µM). Model-based analysis correctly predicted "no-effect" (AUC ratio < 1.25) at the low dose range and "weak" effect (AUC ratio < 2) on atorvastatin pharmacokinetics at the high dose range of KHKi. This study exemplified the utility of biomarker-informed model-based approach in discerning even small effects on OATP1B activity in vivo, and to project DDI risk at the clinically relevant doses.

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

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 (I_in,max,u ), suggested in vivo OATP1B inhibition risk for drugs with R-value (1+ I_in,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.

Endogenous Plasma Kynurenic Acid in Human: A Newly Discovered Biomarker for Drug-Drug Interactions Involving Organic Anion Transporter 1 and 3 Inhibition

As an expansion investigation of drug-drug interaction (DDI) from previous clinical trials, additional plasma endogenous metabolites were quantitated in the same subjects to further identify the potential biomarkers of organic anion transporter (OAT) 1/3 inhibition. In the single dose, open label, three-phase with fixed order of treatments study, 14 healthy human volunteers orally received 1000 mg probenecid alone, or 40 mg furosemide alone, or 40 mg furosemide at 1 hour after receiving 1000 mg probenecid on days 1, 8, and 15, respectively. Endogenous metabolites including kynurenic acid, xanthurenic acid, indo-3-acetic acid, pantothenic acid, p-cresol sulfate, and bile acids in the plasma were measured by liquid chromatography-tandem mass spectrometry. The C_max of kynurenic acids was significantly increased about 3.3- and 3.7-fold over the baseline values at predose followed by the treatment of probenecid alone or in combination with furosemide respectively. In comparison with the furosemide-alone group, the C_max and area under the plasma concentration-time curve (AUC) up to 12 hours of kynurenic acid were significantly increased about 2.4- and 2.5-fold by probenecid alone, and 2.7- and 2.9-fold by probenecid plus furosemide, respectively. The increases in C_max and AUC of plasma kynurenic acid by probenecid are comparable to the increases of furosemide C_max and AUC reported previously. Additionally, the plasma concentrations of xanthurenic acid, indo-3-acetic acid, pantothenic acid, and p-cresol sulfate, but not bile acids, were also significantly elevated by probenecid treatments. The magnitude of effect size analysis for known potential endogenous biomarkers demonstrated that kynurenic acid in the plasma offers promise as a superior addition for early DDI assessment involving OAT1/3 inhibition. SIGNIFICANCE STATEMENT: This article reports that probenecid, an organic anion transporter (OAT) 1 and OAT3 inhibitor, significantly increased the plasma concentrations of kynurenic acid and several uremic acids in human subjects. Of those, the increases of plasma kynurenic acid exposure are comparable to the increases of furosemide by OAT1/3 inhibition. Effect size analysis for known potential endogenous biomarkers revealed that plasma kynurenic acid is a superior addition for early drug-drug interaction assessment involving OAT1/3 inhibition.

Performance of Plasma Coproporphyrin I and III as OATP1B1 Biomarkers in Humans

A previous study in 356 healthy Finnish volunteers showed that glycochenodeoxycholate 3‐O‐glucuronide (GCDCA‐3G) and glycodeoxycholate 3‐O‐glucuronide (GDCA‐3G) are promising biomarkers of organic anion transporting polypeptide 1B1 (OATP1B1). In the same cohort, we now evaluated the performances of two other OATP1B1 biomarkers, coproporphyrin I (CPI) and III (CPIII), and compared them with GCDCA‐3G and GDCA‐3G. Based on decreased (*5 and *15) and increased (*14 and *20) function SLCO1B1 haplotypes, we stratified the participants to poor, decreased, normal, increased, and highly increased OATP1B1 function groups. Fasting plasma CPI concentration was 68% higher in the poor (95% confidence interval, 44%, 97%; P = 1.74 × 10⁻¹⁰), 7% higher in the decreased (0%, 15%; P = 0.0385), 10% lower in the increased (3%, 18%; P = 0.0087), and 23% lower in the highly increased (1%, 40%; P = 0.0387) function group than in the normal function group. CPIII concentration was 27% higher (7%, 51%; P = 0.0071) in the poor function group than in the normal function group. CPI and CPIII detected poor OATP1B1 function with areas under the precision‐recall curve (AUPRC) of 0.388 (95% confidence interval, 0.197, 0.689) and 0.0798 (0.0485, 0.203), and receiver operating characteristic curve (AUROC) of 0.888 (0.851, 0.919) and 0.731 (0.682, 0.776). The AUPRC and AUROC of GCDCA‐3G were, however, 0.389 (0.258, 0.563) and 0.100 (−0.0046, 0.204; P = 0.0610) larger than those of CPI, and 0.697 (0.555, 0.831) and 0.257 (0.141, 0.373; P < 0.0001) larger than those of CPIII. In conclusion, these data indicate that plasma CPI outperforms CPIII in detecting altered OATP1B1 function, but GCDCA‐3G is an even more sensitive OATP1B1 biomarker than CPI.

Quantitative prediction of breast cancer resistant protein mediated drug-drug interactions using physiologically-based pharmacokinetic modeling

Quantitative assessment of drug‐drug interactions (DDIs) involving breast cancer resistance protein (BCRP) inhibition is challenged by overlapping substrate/inhibitor specificity. This study used physiologically‐based pharmacokinetic (PBPK) modeling to delineate the effects of inhibitor drugs on BCRP‐ and organic anion transporting polypeptide (OATP)1B‐mediated disposition of rosuvastatin, which is a recommended BCRP clinical probe. Initial static model analysis using in vitro inhibition data suggested BCRP/OATP1B DDI risk while considering regulatory cutoff criteria for a majority of inhibitors assessed (25 of 27), which increased rosuvastatin plasma exposure to varying degree (~ 0–600%). However, rosuvastatin area under plasma concentration‐time curve (AUC) was minimally impacted by BCRP inhibitors with calculated G‐value (= gut concentration/inhibition potency) below 100. A comprehensive PBPK model accounting for intestinal (OATP2B1 and BCRP), hepatic (OATP1B, BCRP, and MRP4), and renal (OAT3) transport mechanisms was developed for rosuvastatin. Adopting in vitro inhibition data, rosuvastatin plasma AUC changes were predicted within 25% error for 9 of 12 inhibitors evaluated via PBPK modeling. This study illustrates the adequacy and utility of a mechanistic model‐informed approach in quantitatively assessing BCRP‐mediated DDIs.

Effects of Probenecid on Hepatic and Renal Disposition of Hexadecanedioate, an Endogenous Substrate of Organic Anion Transporting Polypeptide 1B in Rats

The aim of the present study was to investigate changes in plasma concentrations and tissue distribution of endogenous substrates of organic anion transporting polypeptide (OATP) 1B, hexadecanedioate (HDA), octadecanedioate (ODA), tetradecanedioate (TDA), and coproporphyrin-III, induced by its weak inhibitor, probenecid (PBD), in rats. PBD increased the plasma concentrations of these four compounds regardless of bile duct cannulation, whereas liver-to-plasma (K_p,liver) and kidney-to-plasma concentration ratios of HDA and TDA were reduced. Similar effects of PBD on plasma concentrations and K_p,liver of HDA, ODA, and TDA were observed in kidney-ligated rats, suggesting a minor contribution of renal disposition to the overall distribution of these three compounds. Tissue uptake clearance of deuterium-labeled HDA (d-HDA) in liver was 16-fold higher than that in kidney, and was reduced by 80% by PBD. This was compatible with inhibition by PBD of d-HDA uptake in isolated rat hepatocytes. Such inhibitory effects of PBD were also observed in the human OATP1B1-mediated uptake of d-HDA. Overall, the disposition of HDA is mainly determined by hepatic OATP-mediated uptake, which is inhibited by PBD. HDA might, thus, be a biomarker for OATPs minimally affected by urinary and biliary elimination in rats.