Clinical Probes and Endogenous Biomarkers as Substrates for Transporter Drug-Drug Interaction Evaluation: Perspectives From the International Transporter Consortium

Insights into the Pharmacogenetics of Tacrolimus Pharmacokinetics and Pharmacodynamics

The influence of pharmacogenetics in tacrolimus pharmacokinetics and pharmacodynamics needs further investigation, considering its potential in assisting clinicians to predict the optimal starting dosage and the need for a personalized adjustment of the dose, as well as to identify patients at a high risk of rejection, drug-related adverse effects, or poor outcomes. In the past decade, new pharmacokinetic strategies have been developed to improve personalized tacrolimus treatment. Several studies have shown that patients with tacrolimus doses C0/D < 1 ng/mL/mg may demonstrate a greater incidence of drug-related adverse events and infections. In addition, C0 tacrolimus intrapatient variability (IPV) has been identified as a potential biomarker to predict poor outcomes related to drug over- and under-exposure. With regard to tacrolimus pharmacodynamics, inconsistent genotype-phenotype relationships have been identified. The aim of this review is to provide a concise summary of currently available data regarding the influence of pharmacogenetics on the clinical outcome of patients with high intrapatient variability and/or a fast metabolizer phenotype. Moreover, the role of membrane transporters in the interindividual variability of responses to tacrolimus is critically discussed from a transporter scientist’s perspective. Indeed, the relationship between transporter polymorphisms and intracellular tacrolimus concentrations will help to elucidate the interplay between the biological mechanisms underlying genetic variations impacting drug concentrations and clinical effects.

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.

Transporters in Regulatory Science: Notable Contributions from Dr. Giacomini in the Past Two Decades

Transporters govern the access of molecules to cells or their exit from cells, thereby controlling the overall distribution of drugs to their intracellular site of action. Clinically relevant drug-drug interactions mediated by transporters are of increasing interest in drug development. Drug transporters, acting alone or in concert with drug metabolizing enzymes, can play an important role in modulating drug absorption, distribution, metabolism, and excretion, thus affecting the pharmacokinetics and/or pharmacodynamics of a drug. Dr. Kathy Giacomini from the University of California, San Francisco is one of the world leaders in transporters and pharmacogenetics with key contributions to transporter science. Her contributions to transporter science are noteworthy. This review paper will summarize Dr. Giacomini's key contributions and influence on transporters in regulatory science in the past two decades. Regulatory science research highlighted in this review covers various aspects of transporter science including understanding the effect of renal impairment on transporters, transporter ontogeny, biomarkers for transporters, and interactions of excipients with transporters affecting drug absorption. Significance Statement This review paper highlights Dr. Giacomini's key contributions and influence on transporters in regulatory science in the past two decades. She has been at the cutting edge of science pertaining to drug transport, drug disposition, and regulatory science, leading to new era of translational sciences pertaining to drug disposition and transporter biology. Her research has and will continue to bring enormous impact on gaining new knowledge in guiding drug development and inspire scientists from all sectors in the field.

Current Perspective on Residual Knowledge Gaps in the Assessment of Transporter-Mediated Drug Interactions

Assessment of transporter-mediated drug-drug interaction (DDI) is integral to drug development. A risk-based approach leveraging in vitro, in vivo, and in silico information is used to evaluate the DDI liability of drugs and inform the instructions of use. While tremendous advances have been made in recent decades, there are knowledge gaps warranting further research. Herein, we focus on select areas to advance assessment of DDI potential for drugs as substrates, inhibitors, or inducers of certain transporters.

An approach for mixture testing and prioritization based on common kinetic groups

In light of an ever-increasing exposure to chemicals, the topic of potential mixture toxicity has gained increased attention, particularly as the toxicological toolbox to address such questions has vastly improved. Routinely toxicological risk assessments will rely on the analysis of individual compounds with mixture effects being considered only in those specific cases where co-exposure is foreseeable, for example for pesticides or food contact materials. In the field of pesticides, active substances are summarized in so-called cumulative assessment groups (CAG) which are primarily based on their toxicodynamic properties, that is, respective target organs and mode of action (MoA). In this context, compounds causing toxicity by a similar MoA are assumed to follow a model of dose/concentration addition (DACA). However, the respective approach inherently falls short of addressing cases where there are dissimilar or independent MoAs resulting in wider toxicokinetic effects. Yet, the latter are often the underlying cause when effects deviate from the DACA model. In the present manuscript, we therefore suggest additionally to consider toxicokinetic effects (especially related to xenobiotic metabolism and transporter interaction) for the grouping of substances to predict mixture toxicity. In line with the concept of MoA-based CAGs, we propose common kinetics groups (CKGs) as an additional tool for grouping of chemicals and mixture prioritization. Fundamentals of the CKG concept are discussed, along with challenges for its implementation, and methodological approaches and examples are explored.

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.

Challenges and Opportunities for Improved Drug-Drug Interaction Predictions for Renal OCT2 and MATE1/2-K Transporters

Transporters contribute to renal elimination of drugs; therefore drug disposition can be impacted if transporters are inhibited by comedicant drugs. Regulatory agencies have provided guidelines to assess potential drug-drug interaction (DDI) risk for renal organic cation transporter 2 (OCT2) and multidrug and toxin extrusion 1 and 2-K (MATE1/2-K) transporters. Despite this, there are challenges with translating in vitro data using currently available tools to obtain a quantitative assessment of DDI risk in the clinic. Given the high number of drugs and new molecular entities showing in vitro inhibition toward OCT2 and/or MATE1/2-K and the lack of translation to clinically significant effects, it is reasonable to question whether the current in vitro assay design and modeling practice has led to unnecessary clinical evaluation. The aim of this review is to assess and discuss available in vitro and clinical data along with prediction models intended to provide clinical context of risk, including static models proposed by regulatory agencies and physiologically-based pharmacokinetic models, in order to identify best practices and areas of future opportunity. This analysis highlights that different in vitro assay designs, including substrate and cell systems used, strongly influence the derived concentration of drug producing 50% inhibition values and contribute to high variability observed across laboratories. Furthermore, the lack of sensitive index substrates coupled with specific inhibitors for individual transporters necessitates the use of complex models to evaluate clinical DDI risk.

Clinical Implications of Altered Drug Transporter Abundance/Function and PBPK Modeling in Specific Populations: An ITC Perspective

The role of membrane transporters on pharmacokinetics (PKs), drug-drug interactions (DDIs), pharmacodynamics (PDs), and toxicity of drugs has been broadly recognized. However, our knowledge of modulation of transporter expression and/or function in the diseased patient population or specific populations, such as pediatrics or pregnancy, is still emerging. This white paper highlights recent advances in studying the changes in transporter expression and activity in various diseases (i.e., renal and hepatic impairment and cancer) and some specific populations (i.e., pediatrics and pregnancy) with the focus on clinical implications. Proposed alterations in transporter abundance and/or activity in diseased and specific populations are based on (i) quantitative transporter proteomic data and relative abundance in specific populations vs. healthy adults, (ii) clinical PKs, and emerging transporter biomarker and/or pharmacogenomic data, and (iii) physiologically-based pharmacokinetic modeling and simulation. The potential for altered PK, PD, and toxicity in these populations needs to be considered for drugs and their active metabolites in which transporter-mediated uptake/efflux is a major contributor to their absorption, distribution, and elimination pathways and/or associated DDI risk. In addition to best practices, this white paper discusses current challenges and knowledge gaps to study and quantitatively predict the effects of modulation in transporter activity in these populations, together with the perspectives from the International Transporter Consortium (ITC) on future directions.

Renal Transporter-Mediated Drug-Biomarker Interactions of the Endogenous Substrates Creatinine and N1 -Methylnicotinamide: A PBPK Modeling Approach

Endogenous biomarkers for transporter-mediated drug-drug interaction (DDI) predictions represent a promising approach to facilitate and improve conventional DDI investigations in clinical studies. This approach requires high sensitivity and specificity of biomarkers for the targets of interest (e.g., transport proteins), as well as rigorous characterization of their kinetics, which can be accomplished utilizing physiologically-based pharmacokinetic (PBPK) modeling. Therefore, the objective of this study was to develop PBPK models of the endogenous organic cation transporter (OCT)2 and multidrug and toxin extrusion protein (MATE)1 substrates creatinine and N¹ -methylnicotinamide (NMN). Additionally, this study aimed to predict kinetic changes of the biomarkers during administration of the OCT2 and MATE1 perpetrator drugs trimethoprim, pyrimethamine, and cimetidine. Whole-body PBPK models of creatinine and NMN were developed utilizing studies investigating creatinine or NMN exogenous administration and endogenous synthesis. The newly developed models accurately describe and predict observed plasma concentration-time profiles and urinary excretion of both biomarkers. Subsequently, models were coupled to the previously built and evaluated perpetrator models of trimethoprim, pyrimethamine, and cimetidine for interaction predictions. Increased creatinine plasma concentrations and decreased urinary excretion during the drug-biomarker interactions with trimethoprim, pyrimethamine, and cimetidine were well-described. An additional inhibition of NMN synthesis by trimethoprim and pyrimethamine was hypothesized, improving NMN plasma and urine interaction predictions. To summarize, whole-body PBPK models of creatinine and NMN were built and evaluated to better assess creatinine and NMN kinetics while uncovering knowledge gaps for future research. The models can support investigations of renal transporter-mediated DDIs during drug development.

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.

Environmental Chemical Contribution to the Modulation of Bile Acid Homeostasis and Farnesoid X Receptor Signaling

Maintaining bile acid (BA) homeostasis is important and regulated by BA activated receptors and signaling pathways. Farnesoid X receptor (FXR) and its regulated target networks in both the liver and the intestines are critical in suppressing BA synthesis and promoting BA transport and enterohepatic circulation. In addition, FXR is critical in regulating lipid metabolism and reducing inflammation, processes critical in the development of cholestasis and fatty liver diseases. BAs are modulated by, but also control, gut microflora. Environmental chemical exposure could affect liver disease development. However, the effects and the mechanisms by which environmental chemicals interact with FXR to affect BA homeostasis are only emerging. In this minireview, our focus is to provide evidence from reports that determine the effects of environmental or therapeutic exposure on altering homeostasis and functions of BAs and FXR. Understanding these effects will help to determine liver disease pathogenesis and provide better prevention and treatment in the future. SIGNIFICANCE STATEMENT: Environmental chemical exposure significantly contributes to the development of cholestasis and nonalcoholic steatohepatitis (NASH). The impact of exposures on bile acid (BA) signaling and Farnesoid X receptor-mediated gut-liver crosstalk is emerging. However, there is still a huge gap in understanding how these chemicals contribute to the dysregulation of BA homeostasis and how this dysregulation may promote NASH development.

Evaluation of the Effect of Abrocitinib on Drug Transporters by Integrated Use of Probe Drugs and Endogenous Biomarkers

Abrocitinib is an oral Janus kinase 1 (JAK1) inhibitor currently approved in the United Kingdom for the treatment of moderate‐to‐severe atopic dermatitis (AD). As patients with AD may use medications to manage comorbidities, abrocitinib could be used concomitantly with hepatic and/or renal transporter substrates. Therefore, we assessed the potential effect of abrocitinib on probe drugs and endogenous biomarker substrates for the drug transporters of interest. In vitro studies indicated that, among the transporters tested, abrocitinib has the potential to inhibit the activities of P‐glycoprotein (P‐gp), breast cancer resistance protein (BCRP), organic anion transporter 3 (OAT3), organic cation transporter 1 (OCT1), and multidrug and toxin extrusion protein 1 and 2K (MATE1/2K). Therefore, subsequent phase I, two‐way crossover, open‐label studies in healthy participants were performed to assess the impact of abrocitinib on the pharmacokinetics of the transporter probe substrates dabigatran etexilate (P‐gp), rosuvastatin (BCRP and OAT3), and metformin (OCT2 and MATE1/2K), as well as endogenous biomarkers for MATE1/2K (N¹‐methylnicotinamide (NMN)) and OCT1 (isobutyryl‐_L‐carnitine (IBC)). Co‐administration with abrocitinib was shown to increase the plasma exposure of dabigatran by ~ 50%. In comparison, the plasma exposure and renal clearance of rosuvastatin and metformin were not altered with abrocitinib co‐administration. Similarly, abrocitinib did not affect the exposure of NMN or IBC. An increase in dabigatran exposure suggests that abrocitinib inhibits P‐gp activity. By contrast, a lack of impact on plasma exposure and/or renal clearance of rosuvastatin, metformin, NMN, or IBC suggests that BCRP, OAT3, OCT1, and MATE1/2K activity are unaffected by abrocitinib.

Evaluation of the Potency of Anti-HIV and Anti-HCV Drugs to Inhibit P-Glycoprotein Mediated Efflux of Digoxin in Caco-2 Cell Line and Human Precision-Cut Intestinal Slices

The inhibition of P-glycoprotein (ABCB1) could lead to increased drug plasma concentrations and hence increase drug toxicity. The evaluation of a drug’s ability to inhibit ABCB1 is complicated by the presence of several transport-competent sites within the ABCB1 binding pocket, making it difficult to select appropriate substrates. Here, we investigate the capacity of antiretrovirals and direct-acting antivirals to inhibit the ABCB1-mediated intestinal efflux of [³H]-digoxin and compare it with our previous rhodamine123 study. At concentrations of up to 100 µM, asunaprevir, atazanavir, daclatasvir, darunavir, elbasvir, etravirine, grazoprevir, ledipasvir, lopinavir, rilpivirine, ritonavir, saquinavir, and velpatasvir inhibited [³H]-digoxin transport in Caco-2 cells and/or in precision-cut intestinal slices prepared from the human jejunum (hPCIS). However, abacavir, dolutegravir, maraviroc, sofosbuvir, tenofovir disoproxil fumarate, and zidovudine had no inhibitory effect. We thus found that most of the tested antivirals have a high potential to cause drug–drug interactions on intestinal ABCB1. Comparing the Caco-2 and hPCIS experimental models, we conclude that the Caco-2 transport assay is more sensitive, but the results obtained using hPCIS agree better with reported in vivo observations. More inhibitors were identified when using digoxin as the ABCB1 probe substrate than when using rhodamine123. However, both approaches had limitations, indicating that inhibitory potency should be tested with at least these two ABCB1 probes.

Prediction of drug-drug interaction potential mediated by transporters between dasatinib and metformin, pravastatin, and rosuvastatin using physiologically based pharmacokinetic modeling

Purpose

Recent in vitro studies demonstrated that dasatinib inhibits organic cation transporter 2 (OCT2), multidrug and toxin extrusion proteins (MATEs), and organic anion transporting polypeptide 1B1/1B3 (OATP1B1/1B3). We developed a physiologically based pharmacokinetic (PBPK) model to assess drug–drug interaction (DDI) potential between dasatinib and known substrates for these transporters in a virtual population.

Methods

The dasatinib PBPK model was constructed using Simcyp^® Simulator by combining its physicochemical properties, in vitro data, in silico predictions, and pharmacokinetic (PK) results from clinical studies. Model validation against three independent clinical trials not used for model development included dasatinib DDI studies with ketoconazole, rifampin, and simvastatin. The validated model was used to simulate DDIs of dasatinib and known substrates for OCT2 and MATEs (metformin) and OATP1B1/1B3 (pravastatin and rosuvastatin).

Results

Simulations of metformin PK in the presence and absence of dasatinib, using inhibitor constant (K_i) values measured in vitro, produced estimated geometric mean ratios (GMRs) of the maximum observed concentration (C_max) and area under the concentration–time curve (AUC) of 1.05 and 1.06, respectively. Sensitivity analysis showed metformin exposure increased < 30% in both AUC and C_max when dasatinib K_i was reduced by tenfold for OCT2 and MATEs simultaneously, and < 40% with a 20-fold K_i reduction. The estimated GMRs of C_max and AUC for pravastatin and rosuvastatin with co-administration of dasatinib were unity (1.00).

Conclusions

This PBPK model accurately described the observed PK profiles of dasatinib. The validated PBPK model predicts low risk of clinically significant DDIs between dasatinib and metformin, pravastatin, or rosuvastatin.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00280-021-04394-z.

The Role of Uptake and Efflux Transporters in the Disposition of Glucuronide and Sulfate Conjugates

Glucuronidation and sulfation are the most typical phase II metabolic reactions of drugs. The resulting glucuronide and sulfate conjugates are generally considered inactive and safe. They may, however, be the most prominent drug-related material in the circulation and excreta of humans. The glucuronide and sulfate metabolites of drugs typically have limited cell membrane permeability and subsequently, their distribution and excretion from the human body requires transport proteins. Uptake transporters, such as organic anion transporters (OATs and OATPs), mediate the uptake of conjugates into the liver and kidney, while efflux transporters, such as multidrug resistance proteins (MRPs) and breast cancer resistance protein (BCRP), mediate expulsion of conjugates into bile, urine and the intestinal lumen. Understanding the active transport of conjugated drug metabolites is important for predicting the fate of a drug in the body and its safety and efficacy. The aim of this review is to compile the understanding of transporter-mediated disposition of phase II conjugates. We review the literature on hepatic, intestinal and renal uptake transporters participating in the transport of glucuronide and sulfate metabolites of drugs, other xenobiotics and endobiotics. In addition, we provide an update on the involvement of efflux transporters in the disposition of glucuronide and sulfate metabolites. Finally, we discuss the interplay between uptake and efflux transport in the intestine, liver and kidneys as well as the role of transporters in glucuronide and sulfate conjugate toxicity, drug interactions, pharmacogenetics and species differences.

Evaluation of Excipient Risk in BCS Class I and III Biowaivers

The objective of this review article is to summarize literature data pertinent to potential excipient effects on intestinal drug permeability and transit. Despite the use of excipients in drug products for decades, considerable research efforts have been directed towards evaluating their potential effects on drug bioavailability. Potential excipient concerns stem from drug formulation changes (e.g., scale-up and post-approval changes, development of a new generic product). Regulatory agencies have established in vivo bioequivalence standards and, as a result, may waive the in vivo requirement, known as a biowaiver, for some oral products. Biowaiver acceptance criteria are based on the in vitro characterization of the drug substance and drug product using the Biopharmaceutics Classification System (BCS). Various regulatory guidance documents have been issued regarding BCS-based biowaivers, such that the current FDA guidance is more restrictive than prior guidance, specifically about excipient risk. In particular, sugar alcohols have been identified as potential absorption-modifying excipients. These biowaivers and excipient risks are discussed here.

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

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

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

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

Assessment of Pharmacokinetic Interaction Between Gefapixant (MK-7264), a P2X3 Receptor Antagonist, and the OATP1B1 Drug Transporter Substrate Pitavastatin

Gefapixant (MK‐7264, AF‐219), a first‐in‐class P2X3 antagonist, is being developed as oral treatment for refractory or unexplained chronic cough. Based on in vitro data, gefapixant exerts inhibitory activity on the organic anion transporter (OAT) P1B1 transporter. Therefore, a drug‐drug interaction study evaluating the potential effects of gefapixant on the OATP1B1 drug transporter, using pitavastatin as a sensitive probe substrate, was conducted. An open‐label, 2‐period, fixed‐sequence study in 20 healthy adults 18 to 55 years old was conducted. In period 1, a 1‐mg oral dose of pitavastatin was administered to each participant. After a ≥4‐day washout, in period 2 participants received a 45‐mg oral dose of gefapixant twice daily on days 1 through 4. On day 2 of period 2, pitavastatin was coadministered with the morning dose of gefapixant. Pitavastatin exposures following single‐dose administration with and without multiple doses of gefapixant were similar: geometric mean ratio (90% confidence interval) of pitavastatin area under the plasma concentration–time curve from time 0 to infinity (AUC_0‐∞) (pitavastatin + gefapixant/pitavastatin alone) was 0.97 (0.93‐1.02). The ratio of pitavastatin lactone AUC_0‐∞ to pitavastatin AUC_0‐∞ was also comparable between treatments. Administration of gefapixant and pitavastatin was generally well tolerated, with no safety findings of concern. These results support that gefapixant has a low potential to inhibit the OATP1B1 transporter.

The utility of endogenous glycochenodeoxycholate-3-sulfate and 4β-hydroxycholesterol to evaluate the hepatic disposition of atorvastatin in rats

The liver is an important organ for drugs disposition, and thus how to accurately evaluate hepatic clearance is essential for proper drug dosing. However, there are many limitations in drug dosage adjustment based on liver function and pharmacogenomic testing. In this study, we evaluated the ability of endogenous glycochenodeoxycholate-3-sulfate (GCDCA-S) and 4β-hydroxycholesterol (4β-HC) plasma levels to evaluate organic anion-transporting polypeptide (Oatps)-mediated hepatic uptake and Cyp3a-meidated metabolism of atorvastatin (ATV) in rats. The concentration of ATV and its metabolites, 2-OH ATV and 4-OH ATV, was markedly increased after a single injection of rifampicin (RIF), an inhibitor of Oatps. Concurrently, plasma GCDCA-S levels were also elevated. After a single injection of the Cyp3a inhibitor ketoconazole (KTZ), plasma ATV concentrations were significantly increased and 2-OH ATV concentrations were decreased, consistent with the metabolism of ATV by Cyp3a. However, plasma 4β-HC was not affected by KTZ treatment despite it being a Cyp3a metabolite of cholesterol. After repeated oral administration of RIF, plasma concentrations of ATV, 2-OH ATV and 4-OH ATV were markedly increased and the hepatic uptake ratio of ATV and GCDCA-S was decreased. KTZ did not affect plasma concentrations of ATV, 2-OH ATV and 4-OH ATV, but significantly decreased the metabolic ratio of total and 4-OH ATV. However, the plasma level and hepatic metabolism of 4β-HC were not changed by KTZ. The inhibition of hepatic uptake of GCDCA-S by RIF was fully reversed after a 7-d washout of RIF. Plasma concentration and hepatic uptake ratio of GCDCA-S were correlated with the plasma level and hepatic uptake of ATV in rats with ANIT-induced liver injury, respectively. These results demonstrate that plasma GCDCA-S is a sensitive probe for the assessment of Oatps-mediated hepatic uptake of ATV. However, Cyp3a-mediated metabolism of ATV was not predicted by plasma 4β-HC levels in rats.

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.

Validation of a Drug Transporter Probe Cocktail Using the Prototypical Inhibitors Rifampin, Probenecid, Verapamil, and Cimetidine

Background and Objective

A novel cocktail containing four substrates of key drug transporters was previously optimized to eliminate mutual drug–drug interactions between the probes digoxin (P-glycoprotein substrate), furosemide (organic anion transporter 1/3), metformin (organic cation transporter 2, multidrug and toxin extrusion protein 1/2-K), and rosuvastatin (organic anion transporting polypeptide 1B1/3, breast cancer resistance protein). This clinical trial investigated the effects of four commonly employed drug transporter inhibitors on cocktail drug pharmacokinetics.

Methods

In a randomized open-label crossover trial in 45 healthy male subjects, treatment groups received the cocktail with or without single oral doses of rifampin, verapamil, cimetidine or probenecid. Concentrations of the probe drugs in serial plasma samples and urine fractions were measured by validated liquid chromatography-tandem mass spectrometry assays to assess systemic exposure.

Results

The results were generally in accordance with known in vitro and/or clinical drug–drug interaction data. Single-dose rifampin increased rosuvastatin area under the plasma concentration–time curve up to the last quantifiable concentration (AUC_0–tz) by 248% and maximum plasma concentration (C_max) by 1025%. Probenecid increased furosemide AUC_0–tz by 172% and C_max by 23%. Cimetidine reduced metformin renal clearance by 26%. The effect of single-dose verapamil on digoxin systemic exposure was less than expected from multiple-dose studies (AUC_0–tz unaltered, C_max + 22%).

Conclusions

Taking all the interaction results together, the transporter cocktail is considered to be validated as a sensitive and specific tool for evaluating transporter-mediated drug–drug interactions in drug development.

Clinical Trial Registration

EudraCT number 2017-001549-29.

Electronic supplementary material

The online version of this article (10.1007/s40262-020-00907-w) contains supplementary material, which is available to authorized users.

The Transporter-Mediated Cellular Uptake and Efflux of Pharmaceutical Drugs and Biotechnology Products: How and Why Phospholipid Bilayer Transport Is Negligible in Real Biomembranes

Over the years, my colleagues and I have come to realise that the likelihood of pharmaceutical drugs being able to diffuse through whatever unhindered phospholipid bilayer may exist in intact biological membranes in vivo is vanishingly low. This is because (i) most real biomembranes are mostly protein, not lipid, (ii) unlike purely lipid bilayers that can form transient aqueous channels, the high concentrations of proteins serve to stop such activity, (iii) natural evolution long ago selected against transport methods that just let any undesirable products enter a cell, (iv) transporters have now been identified for all kinds of molecules (even water) that were once thought not to require them, (v) many experiments show a massive variation in the uptake of drugs between different cells, tissues, and organisms, that cannot be explained if lipid bilayer transport is significant or if efflux were the only differentiator, and (vi) many experiments that manipulate the expression level of individual transporters as an independent variable demonstrate their role in drug and nutrient uptake (including in cytotoxicity or adverse drug reactions). This makes such transporters valuable both as a means of targeting drugs (not least anti-infectives) to selected cells or tissues and also as drug targets. The same considerations apply to the exploitation of substrate uptake and product efflux transporters in biotechnology. We are also beginning to recognise that transporters are more promiscuous, and antiporter activity is much more widespread, than had been realised, and that such processes are adaptive (i.e., were selected by natural evolution). The purpose of the present review is to summarise the above, and to rehearse and update readers on recent developments. These developments lead us to retain and indeed to strengthen our contention that for transmembrane pharmaceutical drug transport "phospholipid bilayer transport is negligible".

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.

Ontogeny of Drug-Metabolizing Enzymes

Almost 50% of prescription drugs lack age-appropriate dosing guidelines and therefore are used "off-label." Only ~10% drugs prescribed to neonates and infants have been studied for safety or efficacy. Immaturity of drug metabolism in children is often associated with drug toxicity. This chapter summarizes data on the ontogeny of major human metabolizing enzymes involved in oxidation, reduction, hydrolysis, and conjugation of drugs. The ontogeny data of individual drug-metabolizing enzymes are important for accurate prediction of drug pharmacokinetics and toxicity in children. This information is critical for designing clinical studies to appropriately test pharmacological hypotheses and develop safer pediatric drugs, and to replace the long-standing practice of body weight- or surface area-normalized drug dosing. The application of ontogeny data in physiologically based pharmacokinetic model and regulatory submission are discussed.

Identification of Food-Derived Isoflavone Sulfates as Inhibition Markers for Intestinal Breast Cancer Resistance Proteins

Potential inhibition of the breast cancer resistance protein (BCRP), a drug efflux transporter, is a key issue during drug development, and the use of its physiologic substrates as biomarkers can be advantageous to assess inhibition. In this study, we aimed to identify BCRP substrates by an untargeted metabolomic approach. Mice were orally administered lapatinib to inhibit BCRP in vivo, and plasma samples were assessed by liquid chromatography/time of flight/mass spectrometry with all-ion fragmentation acquisition and quantified by liquid chromatography with tandem mass spectrometry. A differential metabolomic analysis was also performed for plasma from Bcrp ^-/- and wild-type mice. Plasma peaks of food-derived isoflavone metabolites, daidzein sulfate (DS), and genistein sulfate (GS) increased after lapatinib administration and in Bcrp ^-/- mice. Administration of lapatinib and another BCRP inhibitor febuxostat increased the area under the plasma concentration-time curve (AUC) of DS, GS, and equol sulfate (ES) by 3.6- and 1.8-, 5.6- and 4.1-, and 1.6- and 4.8-fold, respectively. BCRP inhibitors also increased the AUC and maximum plasma concentration of DS and ES after coadministration with each parent compound. After adding parent compounds to the apical side of induced pluripotent stem cell-derived small intestinal epithelial-like cells, DS, GS, and ES in the basal compartment significantly increased in the presence of lapatinib and febuxostat, suggesting the inhibition of intestinal BCRP. ATP-dependent uptake of DS and ES in BCRP-expressing membrane vesicles was reduced by both inhibitors, indicating inhibition of BCRP-mediated DS and ES transport. Thus, we propose the first evidence of surrogate markers for BCRP inhibition. SIGNIFICANCE STATEMENT: This study performed untargeted metabolomics to identify substrates of BCRP/ABCG2 to assess changes in its transport activity in vivo by BCRP/ABCG2 inhibitors. Food-derived isoflavone sulfates were identified as useful markers for evaluating changes in BCRP-mediated transport in the small intestine by its inhibitors.

A phase 1, open-label, drug-drug interaction study of rucaparib with rosuvastatin and oral contraceptives in patients with advanced solid tumors

Purpose

This study aimed at evaluating the effect of rucaparib on the pharmacokinetics of rosuvastatin and oral contraceptives in patients with advanced solid tumors and the safety of rucaparib with and without coadministration of rosuvastatin or oral contraceptives.

Methods

Patients received single doses of oral rosuvastatin 20 mg (Arm A) or oral contraceptives ethinylestradiol 30 µg + levonorgestrel 150 µg (Arm B) on days 1 and 19 and continuous doses of rucaparib 600 mg BID from day 5 to 23. Serial blood samples were collected with and without rucaparib for pharmacokinetic analysis.

Results

Thirty-six patients (n = 18 each arm) were enrolled and received at least 1 dose of study drug. In the drug–drug interaction analysis (n = 15 each arm), the geometric mean ratio (GMR) of maximum concentration (C_max) with and without rucaparib was 1.29 for rosuvastatin, 1.09 for ethinylestradiol, and 1.19 for levonorgestrel. GMR of area under the concentration–time curve from time zero to last quantifiable measurement (AUC_0–last) was 1.34 for rosuvastatin, 1.43 for ethinylestradiol, and 1.56 for levonorgestrel. There was no increase in frequency of treatment-emergent adverse events (TEAEs) when rucaparib was given with either of the probe drugs. In both arms, most TEAEs were mild in severity and considered unrelated to study treatment.

Conclusion

Rucaparib 600 mg BID weakly increased the plasma exposure to rosuvastatin or oral contraceptives. Rucaparib safety profile when coadministered with rosuvastatin or oral contraceptives was consistent with that of rucaparib monotherapy. Dose adjustments of rosuvastatin and oral contraceptives are not necessary when coadministered with rucaparib.

ClinicalTrials.gov NCT03954366; Date of registration May 17, 2019.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00280-021-04338-7.

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

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

Reduced physiologically-based pharmacokinetic model of dabigatran etexilate-dabigatran and its application for prediction of intestinal P-gp-mediated drug-drug interactions

BACKGROUND

Dabigatran etexilate (DABE) has been suggested as a clinical probe for intestinal P-glycoprotein (P-gp)-mediated drug-drug interaction (DDI) studies and, as an alternative to digoxin. Clinical DDI data with various P-gp inhibitors demonstrated a dose-dependent inhibition of P-gp with DABE. The aims of this study were to develop a joint DABE (prodrug)-dabigatran reduced physiologically-based-pharmacokinetic (PBPK) model and to evaluate its ability to predict differences in P-gp DDI magnitude between a microdose and a therapeutic dose of DABE.

METHODS

A joint DABE-dabigatran PBPK model was developed with a mechanistic intestinal model accounting for the regional P-gp distribution in the gastrointestinal tract. Model input parameters were estimated using DABE and dabigatran pharmacokinetic (PK) clinical data obtained after administration of DABE alone or with a strong P-gp inhibitor, itraconazole, and over a wide range of DABE doses (from 375 µg to 400 mg). Subsequently, the model was used to predict extent of DDI with additional P-gp inhibitors and with different DABE doses.

RESULTS

The reduced DABE-dabigatran PBPK model successfully described plasma concentrations of both prodrug and metabolite following administration of DABE at different dose levels and when co-administered with itraconazole. The model was able to capture the dose dependency in P-gp mediated DDI. Predicted magnitude of itraconazole P-gp DDI was higher at the microdose (predicted vs. observed median fold-increase in AUC_+inh/AUC_control (min-max) = 5.88 (4.29-7.93) vs. 6.92 (4.96-9.66) ) compared to the therapeutic dose (predicted median fold-increase in AUC_+inh/AUC_control = 3.48 (2.37-4.84) ). In addition, the reduced DABE-dabigatran PBPK model predicted successfully the extent of DDI with verapamil and clarithromycin as P-gp inhibitors. Model-based simulations of dose staggering predicted the maximum inhibition of P-gp when DABE microdose was concomitantly administered with itraconazole solution; simulations also highlighted dosing intervals required to minimise the DDI risk depending on the DABE dose administered (microdose vs. therapeutic).

CONCLUSIONS

This study provides a modelling framework for the evaluation of P-gp inhibitory potential of new molecular entities using DABE as a clinical probe. Simulations of dose staggering and regional differences in the extent of intestinal P-gp inhibition for DABE microdose and therapeutic dose provide model-based guidance for design of prospective clinical P-gp DDI studies.

Assessment of the Effect of Pyrimethamine, a Potent Inhibitor of Multidrug and Toxin Extrusion Protein 1/2K, on the Pharmacokinetics of Gefapixant (MK-7264), a P2X3 Receptor Antagonist

Gefapixant (MK-7264, AF-219) is a first-in-class P2X3 antagonist in development for refractory or unexplained chronic cough. Gefapixant is primarily cleared by renal excretion. To assess the importance of the multidrug and toxin extrusion protein 1 (MATE1) and MATE2K transporters in the elimination of gefapixant, a drug-drug interaction study was conducted evaluating the effect of coadministration of a single dose of pyrimethamine, a competitive inhibitor of MATE1 and MATE2K, on the single-dose pharmacokinetics of gefapixant in healthy participants. Safety and tolerability were also assessed. In this open-label, 2-period, fixed-sequence study, a 45-mg dose of gefapixant was administered to 12 participants in period 1. After a 7-day washout, a 50-mg dose of pyrimethamine was administered 3 hours before a 45-mg dose of gefapixant in period 2. Compared with the administration of gefapixant alone, concomitant dosing of gefapixant with pyrimethamine increased the total gefapixant plasma exposure (area under the plasma concentration-time curve from time 0 to infinity) by 24%, reduced gefapixant renal clearance by 30%, and increased gefapixant mean terminal half-life from 7.7 to 10.3 hours. The most frequently reported adverse events were dysgeusia, hypogeusia, and dry mouth; all adverse events were considered of mild intensity and resolved by the end of the study. These results support that MATE1 and/or MATE2K contribute to the renal clearance of gefapixant, but the effect of inhibition of these transporters on gefapixant pharmacokinetics is not considered clinically meaningful.

Isobutyrylcarnitine as a Biomarker of OCT1 Activity and Interspecies Differences in its Membrane Transport

Genome-wide association studies have identified an association between isobutyrylcarnitine (IBC) and organic cation transporter 1 (OCT1) genotypes. Higher IBC blood concentrations in humans with active OCT1 genotypes and experimental studies with mouse OCT1 suggested an OCT1-mediated efflux of IBC. In this study, we wanted to confirm the suggested use of IBC as an endogenous biomarker of OCT1 activity and contribute to a better understanding of the mechanisms behind the association between blood concentrations of carnitine derivatives and OCT1 genotype. Blood and urine IBC concentrations were quantified in healthy volunteers regarding intra- and interindividual variation and correlation with OCT1 genotype and with pharmacokinetics of known OCT1 substrates. Furthermore, IBC formation and transport were studied in cell lines overexpressing OCT1 and its naturally occurring variants. Carriers of high-activity OCT1 genotypes had about 3-fold higher IBC blood concentrations and 2-fold higher amounts of IBC excreted in urine compared to deficient OCT1. This was likely due to OCT1 function, as indicated by the fact that IBC correlated with the pharmacokinetics of known OCT1 substrates, like fenoterol, and blood IBC concentrations declined with a 1 h time delay following peak concentrations of the OCT1 substrate sumatriptan. Thus, IBC is a suitable endogenous biomarker reflecting both, human OCT1 (hOCT1) genotype and activity. While murine OCT1 (mOCT1) was an efflux transporter of IBC, hOCT1 exhibited no IBC efflux activity. Inhibition experiments confirmed this data showing that IBC and other acylcarnitines, like butyrylcarnitine, 2-methylbutyrylcarnitine, and hexanoylcarnitine, showed reduced efflux upon inhibition of mOCT1 but not of hOCT1. IBC and other carnitine derivatives are endogenous biomarkers of hOCT1 genotype and phenotype. However, in contrast to mice, the mechanisms underlying the IBC-OCT1 correlation in humans is apparently not directly the OCT1-mediated efflux of IBC. A plausible explanation could be that hOCT1 mediates cellular concentrations of specific regulators or co-substrates in lipid and energy metabolism, which is supported by our in vitro finding that at baseline intracellular IBC concentration is about 6-fold lower alone by OCT1 overexpression.

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

CLINICAL TRIAL REGISTRATION

EudraCT number: 2016-003923-49.

Chiral Transplacental Pharmacokinetics of Fexofenadine: Impact of P-Glycoprotein Inhibitor Fluoxetine Using the Human Placental Perfusion Model

PURPOSE

Fexofenadine is a well-identified in vivo probe substrate of P-glycoprotein (P-gp) and/or organic anion transporting polypeptide (OATP). This work aimed to investigate the transplacental pharmacokinetics of fexofenadine enantiomers with and without the selective P-gp inhibitor fluoxetine.

METHODS

The chiral transplacental pharmacokinetics of fexofenadine-fluoxetine interaction was determined using the ex vivo human placenta perfusion model (n = 4). In the Control period, racemic fexofenadine (75 ng of each enantiomer/ml) was added in the maternal circuit. In the Interaction period, racemic fluoxetine (50 ng of each enantiomer/mL) and racemic fexofenadine (75 ng of each enantiomer/mL) were added to the maternal circulation. In both periods, maternal and fetal perfusate samples were taken over 90 min.

RESULTS

The (S)-(-)- and (R)-(+)-fexofenadine fetal-to-maternal ratio values in Control and Interaction periods were similar (~0.18). The placental transfer rates were similar between (S)-(-)- and (R)-(+)-fexofenadine in both Control (0.0024 vs 0.0019 min^-1) and Interaction (0.0019 vs 0.0021 min^-1) periods. In both Control and Interaction periods, the enantiomeric fexofenadine ratios [R-(+)/S-(-)] were approximately 1.

CONCLUSIONS

Our study showed a low extent, slow rate of non-enantioselective placental transfer of fexofenadine enantiomers, indicating a limited fetal fexofenadine exposure mediated by placental P-gp and/or OATP2B1. The fluoxetine interaction did not affect the non-enantioselective transplacental transfer of fexofenadine. The ex vivo placental perfusion model accurately predicts in vivo placental transfer of fexofenadine enantiomers with remarkably similar values (~0.17), and thus estimates the limited fetal exposure.

Modeling Pharmacokinetic Natural Product-Drug Interactions for Decision-Making: A NaPDI Center Recommended Approach

The popularity of botanical and other purported medicinal natural products (NPs) continues to grow, especially among patients with chronic illnesses and patients managed on complex prescription drug regimens. With few exceptions, the risk of a given NP to precipitate a clinically significant pharmacokinetic NP-drug interaction (NPDI) remains understudied or unknown. Application of static or dynamic mathematical models to predict and/or simulate NPDIs can provide critical information about the potential clinical significance of these complex interactions. However, methods used to conduct such predictions or simulations are highly variable. Additionally, published reports using mathematical models to interrogate NPDIs are not always sufficiently detailed to ensure reproducibility. Consequently, guidelines are needed to inform the conduct and reporting of these modeling efforts. This recommended approach from the Center of Excellence for Natural Product Drug Interaction Research describes a systematic method for using mathematical models to interpret the interaction risk of NPs as precipitants of potential clinically significant pharmacokinetic NPDIs. A framework for developing and applying pharmacokinetic NPDI models is presented with the aim of promoting accuracy, reproducibility, and generalizability in the literature. SIGNIFICANCE STATEMENT: Many natural products (NPs) contain phytoconstituents that can increase or decrease systemic or tissue exposure to, and potentially the efficacy of, a pharmaceutical drug; however, no regulatory agency guidelines exist to assist in predicting the risk of these complex interactions. This recommended approach from a multi-institutional consortium designated by National Institutes of Health as the Center of Excellence for Natural Product Drug Interaction Research provides a framework for modeling pharmacokinetic NP-drug interactions.

Drugs in COVID-19 Clinical Trials: Predicting Transporter-Mediated Drug-Drug Interactions Using In Vitro Assays and Real-World Data

Numerous drugs are currently under accelerated clinical investigation for the treatment of coronavirus disease 2019 (COVID‐19); however, well‐established safety and efficacy data for these drugs are limited. The goal of this study was to predict the potential of 25 small molecule drugs in clinical trials for COVID‐19 to cause clinically relevant drug‐drug interactions (DDIs), which could lead to potential adverse drug reactions (ADRs) with the use of concomitant medications. We focused on 11 transporters, which are targets for DDIs. In vitro potency studies in membrane vesicles or HEK293 cells expressing the transporters coupled with DDI risk assessment methods revealed that 20 of the 25 drugs met the criteria from regulatory authorities to trigger consideration of a DDI clinical trial. Analyses of real‐world data from electronic health records, including a database representing nearly 120,000 patients with COVID‐19, were consistent with several of the drugs causing transporter‐mediated DDIs (e.g., sildenafil, chloroquine, and hydroxychloroquine). This study suggests that patients with COVID‐19, who are often older and on various concomitant medications, should be carefully monitored for ADRs. Future clinical studies are needed to determine whether the drugs that are predicted to inhibit transporters at clinically relevant concentrations, actually result in DDIs.

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.

Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling to Support Waivers of In Vivo Clinical Studies: Current Status, Challenges, and Opportunities

Physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling has been extensively applied to quantitatively translate in vitro data, predict the in vivo performance, and ultimately support waivers of in vivo clinical studies. In the area of biopharmaceutics and within the context of model-informed drug discovery and development (MID3), there is a rapidly growing interest in applying verified and validated mechanistic PBPK models to waive in vivo clinical studies. However, the regulatory acceptance of PBPK analyses for biopharmaceutics and oral drug absorption applications, which is also referred to variously as "PBPK absorption modeling" [Zhang et al. CPT: Pharmacometrics Syst. Pharmacol. 2017, 6, 492], "physiologically based absorption modeling", or "physiologically based biopharmaceutics modeling" (PBBM), remains rather low [Kesisoglou et al. J. Pharm. Sci. 2016, 105, 2723] [Heimbach et al. AAPS J. 2019, 21, 29]. Despite considerable progress in the understanding of gastrointestinal (GI) physiology, in vitro biopharmaceutic and in silico tools, PBPK models for oral absorption often suffer from an incomplete understanding of the physiology, overparameterization, and insufficient model validation and/or platform verification, all of which can represent limitations to their translatability and predictive performance. The complex interactions of drug substances and (bioenabling) formulations with the highly dynamic and heterogeneous environment of the GI tract in different age, ethnic, and genetic groups as well as disease states have not been yet fully elucidated, and they deserve further research. Along with advancements in the understanding of GI physiology and refinement of current or development of fully mechanistic in silico tools, we strongly believe that harmonization, interdisciplinary interaction, and enhancement of the translational link between in vitro, in silico, and in vivo will determine the future of PBBM. This Perspective provides an overview of the current status of PBBM, reflects on challenges and knowledge gaps, and discusses future opportunities around PBPK/PD models for oral absorption of small and large molecules to waive in vivo clinical studies.

Post-translational regulation of the major drug transporters in the families of organic anion transporters and organic anion-transporting polypeptides

The organic anion transporters (OATs) and organic anion-transporting polypeptides (OATPs) belong to the solute carrier (SLC) transporter superfamily and play important roles in handling various endogenous and exogenous compounds of anionic charge. The OATs and OATPs are often implicated in drug therapy by impacting the pharmacokinetics of clinically important drugs and, thereby, drug exposure in the target organs or cells. Various mechanisms (e.g. genetic, environmental, and disease-related factors, drug-drug interactions, and food-drug interactions) can lead to variations in the expression and activity of the anion drug-transporting proteins of OATs and OATPs, possibly impacting the therapeutic outcomes. Previous investigations mainly focused on the regulation at the transcriptional level and drug-drug interactions as competing substrates or inhibitors. Recently, evidence has accumulated that cellular trafficking, post-translational modification, and degradation mechanisms serve as another important layer for the mechanisms underlying the variations in the OATs and OATPs. This review will provide a brief overview of the major OATs and OATPs implicated in drug therapy and summarize recent progress in our understanding of the post-translational modifications, in particular ubiquitination and degradation pathways of the individual OATs and OATPs implicated in drug therapy.