Organic Anion Transporter Polypeptide 1B1 Polymorphism Modulates the Extent of Drug-Drug Interaction and Associated Biomarker Levels in Healthy Volunteers

Innovative Approaches to Optimize Clinical Transporter Drug-Drug Interaction Studies

Of the 450 cell membrane transporters responsible for shuttling substrates, nutrients, hormones, neurotransmitters, antioxidants, and signaling molecules, approximately nine are associated with clinically relevant drug-drug interactions (DDIs) due to their role in drug and metabolite transport. Therefore, a clinical study evaluating potential transporter DDIs is recommended if an investigational product is intestinally absorbed, undergoes renal or hepatic elimination, or is suspected to either be a transporter substrate or perpetrator. However, many of the transporter substrates and inhibitors administered during a DDI study also affect cytochrome P450 (CYP) activity, which can complicate data interpretation. To overcome these challenges, the assessment of endogenous biomarkers can help elucidate the mechanism of complex DDIs when multiple transporters or CYPs may be involved. This perspective article will highlight how creative study designs are currently being utilized to address complex transporter DDIs and the role of physiology-based -pharmacokinetic (PBPK) models can play.

Mechanistic Account of Distinct Change in Organic Anion Transporting Polypeptide 1B (OATP1B) Substrate Pharmacokinetics during OATP1B-Mediated Drug-Drug Interactions Using Physiologically Based Pharmacokinetic Modeling

The role of transporters in drug clearance is widely acknowledged, directly and indirectly by facilitating tissue/enzyme exposure. Through the latter, transporters also affect volume of distribution. Drug-drug interactions (DDIs) involving organic anion transporting polypeptides (OATPs) 1B1/1B3 and SLCO1B1 pharmacogenetics lead to altered pharmacokinetics of OATP1B substrates; however, several factors may confound direct interpretation of pharmacokinetic parameters from these clinical studies using noncompartmental analysis (NCA). A review of clinical data herein indicates a single dose of OATP1B inhibitor rifampin almost never leads to increased substrate half-life but often a decrease and that most clinical OATP1B substrates are CYP3A4 substrates and/or undergo enterohepatic cycling (EHC). Using hypothetically simple OATP1B substrate physiologically based pharmacokinetic (PBPK) models, simulated effect of rifampin differed from specific OATP1B inhibition due to short rifampin half-life causing dissipation of OATP1B inhibition over time combined with CYP3A4 induction. Calculated using simulated tissue data, volume of distribution indeed decreased with OATP1B inhibition and was expectedly limited to the contribution of liver volume. However, an apparent and counterintuitive effect of rifampin on volume greater than that on clearance resulted for CYP3A4 substrates using NCA. The effect of OATP1B inhibition and rifampin on OATP1B substrate models incorporating EHC plus or minus renal clearance was distinct compared with simpler models. Using PBPK models incorporating reversible lactone metabolism for clinical OATP1B substrates atorvastatin and pitavastatin, DDIs reporting decreased half-life with rifampin were reproduced. These simulations provide an explanation for the distinct change in OATP1B substrate pharmacokinetics observed in clinical studies, including changes in volume of distribution and additional mechanisms. SIGNIFICANCE STATEMENT: Transporters are involved in drug clearance and volume of distribution, and distinct changes in OATP1B substrate pharmacokinetics are observed with OATP1B inhibitor rifampin. Using hypothetical and validated PBPK models and simulations, this study addresses the limitations of single-dose rifampin and complicated clinical OATP1B substrate disposition in evaluating the pharmacokinetic parameters of OATP1B substrates during rifampin drug-drug interactions (DDIs). These models account for change in volume of distribution and identify additional mechanisms underlying apparent pharmacokinetic changes in OATP1B DDIs.

Expanding Role of Endogenous Biomarkers for Assessment of Transporter Activity in Drug Development: Current Applications and Future Horizon

The evaluation of transporter-mediated drug-drug interactions (DDIs) during drug development and post-approval contributes to benefit-risk assessment and helps formulate clinical management strategies. The use of endogenous biomarkers, which are substrates of clinically relevant uptake and efflux transporters, to assess the transporter inhibitory potential of a drug has received widespread attention. Endogenous biomarkers, such as coproporphyrin (CP) I and III, have increased mechanistic understanding of complex DDIs. Other endogenous biomarkers are under evaluation, including, but not limited to, sulfated bile acids and 4-pyridoxic acid (PDA). The role of endogenous biomarkers has expanded beyond facilitating assessment of transporter-mediated DDIs and they have also been used to understand alterations in transporter activity in the setting of organ dysfunction and various disease states. We envision that endogenous biomarker-informed approaches will not only help to formulate a prudent and informed DDI assessment strategy but also facilitate quantitative predictions of changes in drug exposures in specific populations.

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.

Non-targeted metabolomics for the identification of plasma metabolites associated with organic anion transporting polypeptide 1B1 function

Our aim was to evaluate biomarkers for organic anion transporting polypeptide 1B1 (OATP1B1) function using a hypothesis-free metabolomics approach. We analyzed fasting plasma samples from 356 healthy volunteers using non-targeted metabolite profiling by liquid chromatography high-resolution mass spectrometry. Based on SLCO1B1 genotypes, we stratified the volunteers to poor, decreased, normal, increased, and highly increased OATP1B1 function groups. Linear regression analysis, and random forest (RF) and gradient boosted decision tree (GBDT) regressors were used to investigate associations of plasma metabolite features with OATP1B1 function. Of the 9152 molecular features found, 39 associated with OATP1B1 function either in the linear regression analysis (p < 10-5) or the RF or GBDT regressors (Gini impurity decrease > 0.01). Linear regression analysis showed the strongest associations with two features identified as glycodeoxycholate 3-O-glucuronide (GDCA-3G; p = 1.2 × 10-20 for negative and p = 1.7 × 10-19 for positive electrospray ionization) and one identified as glycochenodeoxycholate 3-O-glucuronide (GCDCA-3G; p = 2.7 × 10-16). In both the RF and GBDT models, the GCDCA-3G feature showed the strongest association with OATP1B1 function, with Gini impurity decreases of 0.40 and 0.17. In RF, this was followed by one GDCA-3G feature, an unidentified feature with a molecular weight of 809.3521, and the second GDCA-3G feature. In GBDT, the second and third strongest associations were observed with the GDCA-3G features. Of the other associated features, we identified with confidence two representing lysophosphatidylethanolamine 22:5. In addition, one feature was putatively identified as pregnanolone sulfate and one as pregnenolone sulfate. These results confirm GCDCA-3G and GDCA-3G as robust OATP1B1 biomarkers in human plasma.

Influence of Slco2b1-knockout and SLCO2B1-humanization on coproporphyrin I and III levels in rats

BACKGROUND AND PURPOSE

Coproporphyrin (CP) I and III are byproducts of haem synthesis currently investigated as biomarkers for drug-drug interactions involving hepatic organic anion transporting polypeptide (OATP) 1B transporters. Another hepatically expressed OATP-member is OATP2B1. The aim of this study was to test the impact of OATP2B1, which specifically transports CPIII, on CP serum levels, applying novel rat models.

EXPERIMENTAL APPROACH

CPIII transport kinetics and the interplay between OATP2B1 and multidrug resistance-associated proteins (MRPs) were determined in vitro using the vTF7 expression system. Novel rSlco2b1-/- and SLCO2B1+/+ rat models were characterized for physiological parameters and for CP serum levels. Hepatic and renal expression of transporters involved in CP disposition were determined by real-time qPCR, Western blot analysis, and immunohistochemistry.

KEY RESULTS

In vitro experiments revealed differences in transport kinetics comparing human and rat OATP2B1 and showed a consistent, species-specific interplay with hMRP3/rMRP3. Deletion of rOATP2B1 was associated with a trend towards lower CPI serum levels compared with wildtype rats, while CPIII remained unchanged. Comparing SLCO2B1+/+ with knockout rats revealed an effect of sex: only in females the genetic modification influenced CP serum levels. Analysis of hepatic and renal transporters revealed marginal, but in part, statistically significant differences in rMRP2 abundance, which may contribute to the observed changes in CP serum levels.

CONCLUSION AND IMPLICATIONS

Our findings support that factors other than OATP1B transporters are of relevance for basal CP levels. Only in female rats, humanization of SLCO2B1 affects basal CPI and CPIII serum levels, despite isomer selectivity of OATP2B1.

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.

Influence of pharmacogenetics on the diversity of response to statins associated with adverse drug reactions

Background

Statins are one of the most prescribed medications in developed countries as the treatment of choice for reducing cholesterol and preventing cardiovascular diseases. However, a large proportion of patients experience adverse drug reactions, especially myotoxicity. Among the factors that influence the diversity of response, pharmacogenetics emerges as a relevant factor of influence in inter-individual differences in response to statins and can be useful in the prevention of adverse drug effects.

Content

A systematic review was performed of current knowledge of the influence of pharmacogenetics on the occurrence and prevention of statin-associated adverse reactions and clinical benefits of preemptive pharmacogenetics testing.

Summary

Genetic variants SLCO1B1 (rs4149056) for all statins; ABCG2 (rs2231142) for rosuvastatin; or CYP2C9 (rs1799853 and rs1057910) for fluvastatin are associated with an increase in muscle-related adverse effects and poor treatment adherence. Besides, various inhibitors of these transporters and biotransformation enzymes increase the systemic exposure of statins, thereby favoring the occurrence of adverse drug reactions.

Outlook

The clinical preemptive testing of this pharmacogenetic panel would largely prevent the incidence of adverse drug reactions. Standardized methods should be used for the identification of adverse effects and the performance and interpretation of genotyping test results. Standardization would allow to obtain more conclusive results about the association between SLCO1B1, ABCG and CYP2C9 variants and the occurrence of adverse drug reactions. As a result, more personalized recommendations could be established for each statin.

Influencia de la farmacogenética en la diversidad de respuesta a las estatinas asociada a las reacciones adversas

Introducción

Las estatinas son unos de los medicamentos más prescritos en los países desarrollados por ser el tratamiento de elección para reducir los niveles de colesterol ayudando así a prevenir la enfermedad cardiovascular. Sin embargo, un gran número de pacientes sufre reacciones adversas, en especial miotoxicidad. Entre los factores que influyen en la diversidad de respuesta, la farmacogenética puede jugar un papel relevante especialmente en la prevención de los efectos adversos asociados a estos medicamentos.

Contenido

Revisión de los conocimientos actuales sobre la influencia de la farmacogenética en la aparición y prevención de las reacciones adversas asociadas a estatinas, así como del beneficio clínico del test farmacogenético anticipado.

Resumen

Variaciones genéticas en SLCO1B1 (rs4149056) para todas las estatinas; en ABCG2 (rs2231142) para rosuvastatina; o en CYP2C9 (rs1799853 y rs1057910) para fluvastatina están asociadas a un incremento de las reacciones adversas de tipo muscular y a una baja adherencia al tratamiento. Además, diversos fármacos inhibidores de estos transportadores y enzimas de biotransformación incrementan la exposición sistémica de las estatinas favoreciendo la aparición de las reacciones adversas.

Perspectiva

La implementación clínica del análisis anticipado de este panel de farmacogenética evitaría en gran parte la aparición de reacciones adversas. Además, la estandarización en la identificación de los efectos adversos, en la metodología e interpretación del genotipo, permitirá obtener resultados más concluyentes sobre la asociación entre las variantes genéticas del SLCO1B1, ABCG y CYP2C9 y la aparición de reacciones adversas y establecer recomendaciones para alcanzar tratamientos más personalizados para cada estatina.

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

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

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

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

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.

Characterization of endogenous markers of hepatic function in patients receiving itraconazole treatment for prophylaxis of deep mycosis

BACKGROUND

Long-term use of itraconazole (ITZ) is associated with a risk of inducing hepatotoxicity. This study aimed to evaluate the associations of plasma concentrations of ITZ and its hydroxylated metabolite (OH-ITZ) with endogenous markers of hepatic function.

METHODS

Thirty six patients treated with oral ITZ solution for prophylaxis of deep mycosis were enrolled. Plasma concentrations of ITZ and OH-ITZ were determined on the 14th day or later after administration of ITZ. Their associations with endogenous marker levels of hepatic function including plasma coproporphyrin (CP)-I and OATP1B1 genotypes were assessed.

RESULTS

The serum level of total bilirubin (T-Bil) was moderately correlated with the plasma concentration of total ITZ (tITZ) and OH-ITZ (tOH-ITZ). T-Bil elevation above 0.3 mg/dL was observed in 19% of patients, although statistically significant difference was not identified. The plasma concentration of tITZ had no correlation with other endogenous markers levels including AST, ALT, albumin, and plasma CP-I. The serum AST and plasma CP-I levels were correlated with the plasma concentration of free OH-ITZ (fOH-ITZ). T-Bil and plasma CP-I, a marker of OATP1B1 activity, were not correlated with each other, and neither was associated with the OATP1B1 genotypes.

CONCLUSIONS

Plasma ITZ and OH-ITZ had a positive association with T-Bil. The patients with a higher fOH-ITZ level had lower OATP1B1 activity on the basis of plasma CP-I level. ITZ and OH-ITZ have the potential to slightly increase endogenous marker levels of hepatic function, although most likely by different mechanisms.

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.

Statins and Hemostasis: Therapeutic Potential Based on Clinical Evidence

Hemostasis preserves blood fluidity and prevents its loss after vessel injury. The maintenance of blood fluidity requires a delicate balance between pro-coagulant and fibrinolytic status. Endothelial cells (ECs) in the inner face of blood vessels maintain hemostasis through balancing anti-thrombotic and pro-fibrinolytic activities. Dyslipidemias are linked to hemostatic alterations. Thus, it is necessary a better understanding of the underlying mechanisms linking hemostasis with dyslipidemia. Statins are drugs that decrease cholesterol levels in the blood and are the gold standard for treating hyperlipidemias. Statins can be classified into natural and synthetic molecules, approved for the treatment of hypercholesterolemia. The classical mechanism of action of statins is by competitive inhibition of a key enzyme in the synthesis pathway of cholesterol, the HMG-CoA reductase. Statins are frequently administrated by oral ingestion and its interaction with other drugs and food supplements is associated with altered bioavailability. In this review we deeply discuss the actions of statins beyond the control of dyslipidemias, focusing on the actions in thrombotic modulation, vascular and cardiovascular-related diseases, metabolic diseases including metabolic syndrome, diabetes, hyperlipidemia, and hypertension, and chronic diseases such as cancer, chronic obstructive pulmonary disease, and chronic kidney disease. Furthermore, we were prompted to delved deeper in the molecular mechanisms by means statins regulate coagulation acting on liver, platelets, and endothelium. Clinical evidence show that statins are effective regulators of dyslipidemia with a high impact in hemostasis regulation and its deleterious consequences. However, studies are required to elucidate its underlying molecular mechanism and improving their therapeutical actions.

Positive correlation between organic anion transporter 1B function indicated by plasma concentration of coproporphyrin-I and blood concentration of cyclosporin A in real-world patients

AIMS

Cyclosporin A (CyA) has potent inhibitory activity on organic anion transporting polypeptide 1B (OATP1B), causing drug-drug interactions with its substrate drugs. 3-carboxy-4-methyl-5-propyl-2-furanpropionate (CMPF), a uraemic toxin, has also been suggested to inhibit OATP1B activity. Recent study has identified coproporphyrin-I (CP-I) as a specific endogenous substrate for OATP1B, which is useful to indicate OATP1B activity. We investigated the relationship of CP-I with CyA and CMPF concentrations in patients taking CyA.

METHODS

In total, 121 blood samples from 74 patients who took CyA and underwent routine therapeutic drug monitoring were divided into trough and peak samples.

RESULTS

CyA and CP-I concentrations were significantly higher in peak samples than in trough samples. A positive correlation between CP-I and CyA concentrations was found in all samples and in trough and peak samples, while no correlation was observed between CP-I and CMPF concentrations. Multiple regression analysis identified CyA and C-reactive protein concentrations as independent factors affecting CP-I concentration, with blood CyA concentration having markedly greater contribution to plasma CP-I concentration.

CONCLUSION

The present study suggests that CyA inhibits OATP1B activity in a concentration-dependent manner in clinical setting, and that dose adjustment of OATP1B substrate drugs coadministered with CyA according to plasma CMPF concentration may not be necessary.

Machine Learning Models Identify New Inhibitors for Human OATP1B1

The uptake transporter OATP1B1 (SLC01B1) is largely localized to the sinusoidal membrane of hepatocytes and is a known victim of unwanted drug-drug interactions. Computational models are useful for identifying potential substrates and/or inhibitors of clinically relevant transporters. Our goal was to generate OATP1B1 in vitro inhibition data for [3H] estrone-3-sulfate (E3S) transport in CHO cells and use it to build machine learning models to facilitate a comparison of seven different classification models (Deep learning, Adaboosted decision trees, Bernoulli naïve bayes, k-nearest neighbors (knn), random forest, support vector classifier (SVC), logistic regression (lreg), and XGBoost (xgb)] using ECFP6 fingerprints to perform 5-fold, nested cross validation. In addition, we compared models using 3D pharmacophores, simple chemical descriptors alone or plus ECFP6, as well as ECFP4 and ECFP8 fingerprints. Several machine learning algorithms (SVC, lreg, xgb, and knn) had excellent nested cross validation statistics, particularly for accuracy, AUC, and specificity. An external test set containing 207 unique compounds not in the training set demonstrated that at every threshold SVC outperformed the other algorithms based on a rank normalized score. A prospective validation test set was chosen using prediction scores from the SVC models with ECFP fingerprints and were tested in vitro with 15 of 19 compounds (84% accuracy) predicted as active (≥20% inhibition) showed inhibition. Of these compounds, six (abamectin, asiaticoside, berbamine, doramectin, mobocertinib, and umbralisib) appear to be novel inhibitors of OATP1B1 not previously reported. These validated machine learning models can now be used to make predictions for drug-drug interactions for human OATP1B1 alongside other machine learning models for important drug transporters in our MegaTrans software.

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.

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.

Recent advances in the translation of drug metabolism and pharmacokinetics science for drug discovery and development

Drug metabolism and pharmacokinetics (DMPK) is an important branch of pharmaceutical sciences. The nature of ADME (absorption, distribution, metabolism, excretion) and PK (pharmacokinetics) inquiries during drug discovery and development has evolved in recent years from being largely descriptive to seeking a more quantitative and mechanistic understanding of the fate of drug candidates in biological systems. Tremendous progress has been made in the past decade, not only in the characterization of physiochemical properties of drugs that influence their ADME, target organ exposure, and toxicity, but also in the identification of design principles that can minimize drug-drug interaction (DDI) potentials and reduce the attritions. The importance of membrane transporters in drug disposition, efficacy, and safety, as well as the interplay with metabolic processes, has been increasingly recognized. Dramatic increases in investments on new modalities beyond traditional small and large molecule drugs, such as peptides, oligonucleotides, and antibody-drug conjugates, necessitated further innovations in bioanalytical and experimental tools for the characterization of their ADME properties. In this review, we highlight some of the most notable advances in the last decade, and provide future perspectives on potential major breakthroughs and innovations in the translation of DMPK science in various stages of drug discovery and development.

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.

Organic Anion Transporting Polypeptide 2B1 (OATP2B1) Genetic Variants: In Vitro Functional Characterization and Association With Circulating Concentrations of Endogenous Substrates

Organic anion transporting polypeptide 2B1 (OATP2B1, gene SLCO2B1) is an uptake transporter that is thought to determine drug disposition and in particular, the oral absorption of medications. At present, the clinical relevance of SLCO2B1 genetic variation on pharmacokinetics is poorly understood. We sought to determine the functional activity of 5 of the most common missense OATP2B1 variants (c.76_84del, c.601G>A, c.917G>A, c.935G>A, and c.1457C>T) and a predicted dysfunctional variant (c.332G>A) in vitro. Furthermore, we measured the basal plasma concentrations of endogenous OATP2B1 substrates, namely estrone sulfate, dehydroepiandrosterone sulfate (DHEAS), pregnenolone sulfate, coproporphyrin I (CPI), and CPIII, and assessed their relationships with SLCO2B1 genotypes in 93 healthy participants. Compared to reference OATP2B1, the transport activities of the c.332G>A, c.601G>A and c.1457C>T variants were reduced among the substrates examined (estrone sulfate, DHEAS, CPI, CPIII and rosuvastatin), although there were substrate-dependent effects. Lower transport function of OATP2B1 variants could be explained by diminished cell surface expression. Other OATP2B1 variants (c.76-84del, c.917G>A and c.935G>A) had similar activity to the reference transporter. In the clinical cohort, the SLCO2B1 c.935G>A allele was associated with both higher plasma CPI (42%) and CPIII (31%) concentrations, while SLCO2B1 c.917G>A was linked to lower plasma CPIII by 28% after accounting for the effects of age, sex, and SLCO1B1 genotypes. No association was observed between SLCO2B1 variant alleles and estrone sulfate or DHEAS plasma concentrations, however 45% higher plasma pregnenolone sulfate level was associated with SLCO2B1 c.1457C>T. Taken together, we found that the impacts of OATP2B1 variants on transport activities in vitro were not fully aligned with their associations to plasma concentrations of endogenous substrates in vivo. Additional studies are required to determine whether circulating endogenous substrates reflect OATP2B1 activity.

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.

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.

Comparison of Hepatic Transporter Tissue Expression in Rodents and Interspecies Hepatic OCT1 Activity

Hepatic clearance may be uptake rate limited by organic anion transporting polypeptides (OATPs) and organic cation transporter 1 (OCT1). While comparison of OATP activity has been investigated across species, little has been reported for OCT1. Additionally, while data on interspecies transporter expression in the liver exist, quantitative comparison of these transporters in multiple tissues is lacking. In the current research, the pharmacokinetics of OCT1 substrates (sumatriptan and metformin) were assessed in Oct knockout rats for comparison with previous Oct1/2-/- mice data and OCT1 pharmacogenetics in humans. Effect of OCT1 inhibitors verapamil and erlotinib on OCT1 substrate liver partitioning was also evaluated in rats. Expression of 18 transporters, including Oatps and Octs, in 9 tissues from mice and rats was quantitated using nanoLC/MS-MS, along with uptake transporters in hepatocytes from 5 species. Interspecies differences in OCT1 activity were further evaluated via uptake of OCT1 substrates in hepatocytes with corresponding in vivo liver partitioning in rodents and monkey. In Oct1-/- rats, sumatriptan hepatic clearance and liver partitioning decreased; however, metformin pharmacokinetics were unaffected. OCT1 inhibitor coadministration decreased sumatriptan liver partitioning. In rodents, Oatp expression was highest in the liver, although comparable expression of Oatps in other tissues was determined. Expression of Octs was highest in the kidney, with liver Oct1 expression comparably lower than Oatps. Liver partitioning of OCT1 substrates was lower in rodents than in monkey, in agreement with the highest OCT1 expression and uptake of OCT1 substrates in monkey hepatocytes. Species-dependent OCT1 activity requires consideration when translating preclinical data to the clinic.

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.

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.

Multi-factorial pharmacokinetic interactions: unraveling complexities in precision drug therapy

Introduction: Precision drug therapy requires accounting for pertinent factors in pharmacokinetic (PK) inter-individual variability (i.e., pharmacogenetics, diseases, polypharmacy, and natural product use) that can cause sub-therapeutic or adverse effects. Although each of these individual factors can alter victim drug PK, multi-factorial interactions can cause additive, synergistic, or opposing effects. Determining the magnitude and direction of these complex multi-factorial effects requires understanding the rate-limiting redundant and/or sequential PK processes for each drug.Areas covered: Perturbations in drug-metabolizing enzymes and/or transporters are integral to single- and multi-factorial PK interactions. Examples of single factor PK interactions presented include gene-drug (pharmacogenetic), disease-drug, drug-drug, and natural product-drug interactions. Examples of multi-factorial PK interactions presented include drug-gene-drug, natural product-gene-drug, gene-gene-drug, disease-natural product-drug, and disease-gene-drug interactions. Clear interpretation of multi-factorial interactions can be complicated by study design, complexity in victim drug PK, and incomplete mechanistic understanding of victim drug PK.Expert opinion: Incorporation of complex multi-factorial PK interactions into precision drug therapy requires advances in clinical decision tools, intentional PK study designs, drug-metabolizing enzyme and transporter fractional contribution determinations, systems and computational approaches (e.g., physiologically-based pharmacokinetic modeling), and PK phenotyping of progressive diseases.

Substantially Increased Plasma Coproporphyrin-I Concentrations Associated With OATP1B1*15 Allele in Japanese General Population

Coproporphyrin-I (CP-I) in plasma is a sensitive and specific endogenous probe for phenotyping organic anion transporting polypeptides 1B (OATP1B, encoded by SLCO1B). A few small-scale studies suggested that plasma CP-I concentration is affected by OATP1B1 polymorphism, but detailed studies are lacking. In this large-scale study, we measured plasma CP-I concentrations in 391 subjects from the Japanese general population, and evaluated the relationship between plasma CP-I concentrations and OATP1B1 polymorphisms to further assess the utility of plasma CP-I concentrations as an endogenous OATP1B probe. Plasma CP-I concentrations were 0.45 ± 0.12, 0.47 ± 0.16, 0.47 ± 0.20, 0.50 ± 0.15, 0.54 ± 0.14, and 0.74 ± 0.31 ng/mL in participants with OATP1B1*1b/*1b (n = 103), *1a/*1b (n = 122), *1a/*1a (n = 40), *1b/*15 (n = 74), *1a/*15 (n = 41), and *15/*15 (n = 11), respectively, showing an ascending rank order with significant difference (P < 0.0001). Post hoc analysis revealed significant increases in plasma CP-I concentration in OATP1B1*1b/*15 (P = 0.036), *1a/*15 (P = 0.0005), and *15/*15 (P = 0.0003) groups compared with the OATP1B1*1b/*1b group. There was no significant difference among OATP1B genotypes in plasma concentration of 3-carboxy-4-methyl-5-propyl-2-furanpropanoic acid, a uremic toxin reported to decrease OATP1B activity in vivo. These findings confirm the utility of plasma CP-I concentrations as an endogenous biomarker for phenotyping of OATP1B activity. Plasma CP-I concentration is potentially useful for the study of drug-drug interactions via OATP1B or individual dose adjustment of OATP1B substrates.

Identification of Glycochenodeoxycholate 3-O-Glucuronide and Glycodeoxycholate 3-O-Glucuronide as Highly Sensitive and Specific OATP1B1 Biomarkers

The aim of this study was to investigate the sensitivity and specificity of endogenous glycochenodeoxycholate and glycodeoxycholate 3-O-glucuronides (GCDCA-3G and GDCA-3G) as substrates for organic anion transporting polypeptide 1B1 (OATP1B1) in humans. We measured fasting levels of plasma GCDCA-3G and GDCA-3G using liquid chromatography-tandem mass spectrometry in 356 healthy volunteers. The mean plasma levels of both compounds were ~ 50% lower in women than in men (P = 2.25 × 10^-18 and P = 4.73 × 10^-9 ). In a microarray-based genome-wide association study, the SLCO1B1 rs4149056 (c.521T>C, p.Val174Ala) variation showed the strongest association with the plasma GCDCA-3G (P = 3.09 × 10^-30 ) and GDCA-3G (P = 1.60 × 10^-17 ) concentrations. The mean plasma concentration of GCDCA-3G was 9.2-fold (P = 8.77 × 10^-31 ) and that of GDCA-3G was 6.4-fold (P = 2.45x10^-13 ) higher in individuals with the SLCO1B1 c.521C/C genotype than in those with the c.521T/T genotype. No other variants showed independent genome-wide significant associations with GCDCA-3G or GDCA-3G. GCDCA-3G was highly efficacious in detecting the SLCO1B1 c.521C/C genotype with an area under the receiver operating characteristic curve of 0.996 (P < 0.0001). The sensitivity (98-99%) and specificity (100%) peaked at a cutoff value of 180 ng/mL for men and 90 ng/mL for women. In a haplotype-based analysis, SLCO1B1*5 and *15 were associated with reduced, and SLCO1B1*1B, *14, and *35 with increased OATP1B1 function. In vitro, both GCDCA-3G and GDCA-3G showed at least 6 times higher uptake by OATP1B1 than OATP1B3 or OATP2B1. These data indicate that the hepatic uptake of GCDCA-3G and GDCA-3G is predominantly mediated by OATP1B1. GCDCA-3G, in particular, is a highly sensitive and specific OATP1B1 biomarker in humans.

Current progress in identifying endogenous biomarker candidates for drug transporter phenotyping and their potential application to drug development

Drug transporters play important roles in the elimination of various compounds from the blood. Genetic variation and drug-drug interactions underlie the pharmacokinetic differences for the substrates of drug transporters. Some endogenous substrates of drug transporters have emerged as biomarkers to assess differences in drug transporter activity-not only in animals, but also in humans. Metabolomic analysis is a promising approach for identifying such endogenous substrates through their metabolites. The appropriateness of metabolites is supported by studies in vitro and in vivo, both in animals and through pharmacogenomic or drug-drug interaction studies in humans. This review summarizes current progress in identifying such endogenous biomarkers and applying them to drug transporter phenotyping.

An updated review of pharmacokinetic drug interactions and pharmacogenetics of statins

INTRODUCTION

Hydroxymethylglutaryl-coenzyme A reductase inhibitors (statins) lower cholesterol synthesis in patients with hypercholesterolemia. Increased statin exposure is an important risk factor for skeletal muscle toxicity. Potent inhibitors of cytochrome P450 (CYP) 3A4 significantly increase plasma concentrations of the active forms of simvastatin, lovastatin, and atorvastatin. Fluvastatin is metabolized by CYP2C9, whereas pravastatin, rosuvastatin, and pitavastatin are unaffected by inhibition by either CYP. Statins also have different affinities for membrane transporters involved in processes such as intestinal absorption, hepatic absorption, biliary excretion, and renal excretion.

AREAS COVERED

In this review, the pharmacokinetic aspects of drug-drug interactions with statins and genetic polymorphisms of CYPs and drug transporters involved in the pharmacokinetics of statins are discussed.

EXPERT OPINION

Understanding the mechanisms underlying statin interactions can help minimize drug interactions and reduce the adverse side effects caused by statins. Since recent studies have shown the involvement of drug transporters such as OATP and BCRP as well as CYPs in statin pharmacokinetics, further clinical studies focusing on the drug transporters are necessary. The establishment of biomarkers based on novel mechanisms, such as the leakage of microRNAs into the peripheral blood associated with the muscle toxicity, is important for the early detection of statin side effects.

A Microdose Cocktail to Evaluate Drug Interactions in Patients with Renal Impairment

Renal impairment (RI) is known to influence the pharmacokinetics of nonrenally eliminated drugs, although the mechanism and clinical impact is poorly understood. We assessed the impact of RI and single dose oral rifampin (RIF) on the pharmacokinetics of CYP3A, OATP1B, P-gp, and BCRP substrates using a microdose cocktail and OATP1B endogenous biomarkers. RI alone had no impact on midazolam (MDZ), maximum plasma concentration (C_max ), and area under the curve (AUC), but a progressive increase in AUC with RI severity for dabigatran (DABI), and up to ~2-fold higher AUC for pitavastatin (PTV), rosuvastatin (RSV), and atorvastatin (ATV) for all degrees of RI was observed. RIF did not impact MDZ, had a progressively smaller DABI drug-drug interaction (DDI) with increasing RI severity, a similar 3.1-fold to 4.4-fold increase in PTV and RSV AUC in healthy volunteers and patients with RI, and a diminishing DDI with RI severity from 6.1-fold to 4.7-fold for ATV. Endogenous biomarkers of OATP1B (bilirubin, coproporphyrin I/III, and sulfated bile salts) were generally not impacted by RI, and RIF effects on these biomarkers in RI were comparable or larger than those in healthy volunteers. The lack of a trend with RI severity of PTV and several OATP1B biomarkers, suggests that mechanisms beyond RI directly impacting OATP1B activity could also be considered. The DABI, RSV, and ATV data suggest an impact of RI on intestinal P-gp, and potentially BCRP activity. Therefore, DDI data from healthy volunteers may represent a worst-case scenario for clinically derisking P-gp and BCRP substrates in the setting of RI.

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.

Organic Anion-Transporting Polypeptide Genes Are Not Induced by the Pregnane X Receptor Activator Rifampin: Studies in Hepatocytes In Vitro and in Monkeys In Vivo

Induction potentials of the pregnane X receptor (PXR) activator rifampin (RIF) on transporter genes [e.g., organic anion-transporting polypeptides (OATPs)] are still in its infancy or remain controversial in the field. The present investigations characterized changes in transporter gene expression by RIF in sandwich-cultured hepatocytes from multiple donors of human and cynomolgus monkey using real-time quantitative reverse transcription polymerase chain reaction method. Three-day treatment of RIF significantly induced CYP3A4 (∼60-fold induction), but not CYP1A2 and CYP2D6 genes. SLC51B was the most highly induced uptake transporter gene (>10-fold) in both human and monkey hepatocytes. A greater induction of CYP2C9 was observed in monkey hepatocytes than that in humans. ATP-binding cassette (ABC)B1 and ABCC2 were induced slightly above 2-fold in human and monkey hepatocytes and appeared to be dose-dependent. The induction of OATP and other transporter genes was generally less than 2-fold and considered not clinically relevant. SLCO2B1 was not detectable in monkey hepatocytes. To investigate in vivo OATP induction, RIF (18 mg/kg per day) was orally dosed to cynomolgus monkeys for 7 days. Pitavastatin and antipyrine were intravenously dosed before and after RIF treatment as exogenous probes of OATP and CYP activities, respectively. Plasma coproporphyrin-I (CP-I) and coproporphyrin-III (CP-III) were measured as OATP endogenous biomarkers. Although a significant increase of antipyrine clearance (CL) was observed after RIF treatment, the plasma exposures of pitavastatin, CP-I, and CP-III remained unchanged, suggesting that OATP function was not significantly altered. The results suggested that OATP transporters were not significantly induced by PXR ligand RIF. The data are consistent with current regulatory guidances that the in vitro characterization of transporter induction during drug development is not required. SIGNIFICANCE STATEMENT: Organic anion-transporting polypeptide (OATP) genes were not induced by rifampin in sandwich-cultured human and monkey hepatocytes OATP functions measured by OATP probe pitavastatin and endogenous marker coproporphyrins were not altered in monkeys in vivo by 7-day rifampin treatment. The data suggested that OATP transporters are unlikely induced by the pregnane X receptor ligand rifampin, which are consistent with current regulatory guidances that the in vitro characterization of OATP1B induction during drug development is not required.