Pharmacokinetic Evaluation of a Drug Transporter Cocktail Consisting of Digoxin, Furosemide, Metformin, and Rosuvastatin

Effect of midostaurin on the pharmacokinetics of P-gp, BCRP, and CYP2D6 substrates: assessing potential drug-drug interactions in healthy participants : Brief title: Drug-drug interaction of midostaurin

PURPOSE

Midostaurin, approved for FLT3-mutated acute myeloid leukemia and advanced systemic mastocytosis, is mainly metabolized by cytochrome P450 (CYP) 3A4. Midostaurin exhibited potential inhibitory effects on P-glycoprotein (P-gp), breast cancer resistance protein (BCRP), organic anion-transporting polyprotein 1B1, and CYP2D6 in in vitro studies. This study investigated the pharmacokinetic (PK) effects of midostaurin on P-gp (digoxin), BCRP (rosuvastatin) and CYP2D6 (dextromethorphan) substrates in healthy adults.

METHODS

This was an open-label, single-sequence, phase I clinical study evaluating the effect of single-dose midostaurin (100 mg) on the PK of digoxin and rosuvastatin (Arm 1), and dextromethorphan (Arm 2). Participants were followed up for safety 30 days after last dose. In addition, the effect of midostaurin on the PK of dextromethorphan metabolite (dextrorphan) was assessed in participants with functional CYP2D6 genes in Arm 2.

RESULTS

The effect of midostaurin on digoxin was minor and resulted in total exposure (AUC) and peak plasma concentration (Cmax) that were only 20% higher. The effect on rosuvastatin was mild and led to an increase in AUCs of approximately 37-48% and of 100% in Cmax. There was no increase in the primary PK parameters (AUCs and Cmax) of dextromethorphan in the presence of midostaurin. The study treatments were very well tolerated with no occurance of severe adverse events (AEs), AEs of grade ≥ 2, or deaths.

CONCLUSION

Midostaurin showed only a minor inhibitory effect on P-gp, a mild inhibitory effect on BCRP, and no inhibitory effect on CYP2D6. Study treatments were well tolerated in healthy adults.

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.

A Pilot Study To Assess the Suitability of Riboflavin As a Surrogate Marker of Breast Cancer Resistance Protein in Healthy Participants

We recently showed that riboflavin is a selected substrate of breast cancer resistance protein (BCRP) over P-glycoprotein (P-gp) and demonstrated its prediction performance in preclinical drug-drug interaction (DDI) studies. The aim of this study was to investigate the suitability of riboflavin to assess BCRP inhibition in humans. First, we assessed the substrate potential of riboflavin toward other major drug transporters using established transfected cell systems. Riboflavin is a substrate for organic anion transporter (OAT)1, OAT3, and multidrug and toxin extrusion protein (MATE)2-K, with uptake ratios ranging from 2.69 to 11.6, but riboflavin is not a substrate of organic anion-transporting polypeptide (OATP)1B1, OATP1B3, organic cation transporter (OCT)2, and MATE1. The effects of BMS-986371, a potent in vitro inhibitor of BCRP (IC 50 0.40 μM), on the pharmacokinetics of riboflavin, isobutyryl carnitine, and arginine were then examined in healthy male adults (N = 14 or 16) after oral administration of methotrexate (MTX) (7.5 mg) and enteric-coated (EC) sulfasalazine (SSZ) (1000 mg) alone or in combination with BMS-986371 (150 mg). Oral administration of BMS-986371 increased the area under the plasma concentration-time curves (AUCs) of rosuvastatin and immediate-release (IR) SSZ to 1.38- and 1.51-fold, respectively, and significantly increased AUC(0-4h), AUC(0-24h), and C max of riboflavin by 1.25-, 1.14-, and 1.11-fold (P-values of 0.003, 0.009, and 0.025, respectively) compared with the MTX/SSZ EC alone group. In contrast, BMS-986371 did not significantly influence the AUC(0-24h) and C max values of isobutyryl carnitine and arginine (0.96- to 1.07-fold, respectively; P > 0.05). Overall, these data indicate that plasma riboflavin is a promising biomarker of BCRP that may offer a possibility to assess drug candidate as a BCRP modulator in early drug development. SIGNIFICANCE STATEMENT: Endogenous compounds that serve as biomarkers for clinical inhibition of breast cancer resistance protein (BCRP) are not currently available. This study provides the initial evidence that riboflavin is a promising BCRP biomarker in humans. For the first time, the value of leveraging the substrate of BCRP with acceptable prediction performance in clinical studies is shown. Additional clinical investigations with known BCRP inhibitors are needed to fully validate and showcase the utility of this biomarker.

Integrating Full Bayesian Inference and Student's t-Distribution Method for Enhanced Outlier Handling in Caffeine Population Pharmacokinetics: Assessing Drug-Drug Interactions with Enasidenib in Relapsed or Refractory AML and MDS Patients

As the first-in-class, selective, and potent inhibitor of the isocitrate dehydrogenase-2 (IDH2) mutant protein, enasidenib was approved by the US Food and Drug Administration (FDA) in 2017 for the treatment of adult patients with relapsed or refractory acute myeloid leukemia (AML) with an IDH2 mutation. Known for its interactions with various cytochrome P450 (CYP) enzymes and transporters in vitro, a clinical pharmacokinetics (PK) trial was initiated to assess the impact of multiple doses of enasidenib on the single-dose PK of sensitive probe substrates of several cytochrome P450 enzymes and transporters. In this study, a population pharmacokinetic analysis approach was employed to address challenges posed by high, nonzero baseline caffeine concentrations. Moreover, we integrated full Bayesian inference into this approach innovatively for a more detailed understanding of parameter uncertainty and greater modeling flexibility, alongside Student's t-distribution for robust error modeling in handling the abnormal outlier caffeine concentration data observed in this trial. Our analyses demonstrated that multiple doses of enasidenib altered caffeine clearance to a clinically meaningful extent, as evidenced by an approximate 8-fold decrease. This finding led to a specific recommendation in the package insert to avoid the concurrent use of certain CYP1A2 substrates with enasidenib, unless directed otherwise in the prescribing information. Furthermore, this research underlines the technical benefits of integrating full Bayesian inference and incorporating Student's t-distribution for residual error modeling in the PK field.

Liver Fibrosis Stages Affect Organic Cation Transporter 1/2 Activities in Hepatitis C Virus-Infected Patients

This study aims to evaluate the impact of liver fibrosis stages of chronic infection with hepatitis C virus (HCV) on the in vivo activity of organic cation transporters (hepatic OCT1 and renal OCT2) using metformin (MET) as a probe drug. Participants allocated in Group 1 (n = 15, mild to moderate liver fibrosis) or 2 (n = 13, advanced liver fibrosis and cirrhosis) received a single MET 50 mg oral dose before direct-acting antiviral (DAA) drug treatment (Phase 1) and 30 days after achieving sustained virologic response (Phase 2). OCT1/2 activity (MET AUC0-24) was found to be reduced by 25% when comparing the two groups in Phase 2 (ratio 0.75 (0.61-0.93), p < 0.05) but not in Phase 1 (ratio 0.81 (0.66-0.98), p > 0.05). When Phases 1 and 2 were compared, no changes were detected in both Groups 1 (ratio 1.10 (0.97-1.24), p > 0.05) and 2 (ratio 1.03 (0.94-1.12), p > 0.05). So, this study shows a reduction of approximately 25% in the in vivo activity of OCT1/2 in participants with advanced liver fibrosis and cirrhosis after achieving sustained virologic response and highlights that OCT1/2 in vivo activity depends on the liver fibrosis stage of chronic HCV infection.

Clinical Evaluation of the Effect of Encorafenib on Bupropion, Rosuvastatin, and Coproporphyrin I and Considerations for Statin Coadministration

BACKGROUND AND OBJECTIVES

Encorafenib is a kinase inhibitor indicated for the treatment of patients with unresectable or metastatic melanoma or metastatic colorectal cancer, respectively, with selected BRAF V600 mutations. A clinical drug-drug interaction (DDI) study was designed to evaluate the effect of encorafenib on rosuvastatin, a sensitive substrate of OATP1B1/3 and breast cancer resistance protein (BCRP), and bupropion, a sensitive CYP2B6 substrate. Coproporphyrin I (CP-I), an endogenous substrate for OATP1B1, was measured in a separate study to deconvolute the mechanism of transporter DDI.

METHODS

DDI study participants received a single oral dose of rosuvastatin (10 mg) and bupropion (75 mg) on days - 7, 1, and 14 and continuous doses of encorafenib (450 mg QD) and binimetinib (45 mg BID) starting on day 1. The CP-I data were collected from participants in a phase 3 study who received encorafenib (300 mg QD) and cetuximab (400 mg/m2 initial dose, then 250 mg/m2 QW). Pharmacokinetic and pharmacodynamic analysis was performed using noncompartmental and compartmental methods.

RESULTS

Bupropion exposure was not increased, whereas rosuvastatin Cmax and area under the receiver operating characteristic curve (AUC) increased approximately 2.7 and 1.6-fold, respectively, following repeated doses of encorafenib and binimetinib. Increase in CP-I was minimal, suggesting that the primary effect of encorafenib on rosuvastatin is through BCRP. Categorization of statins on the basis of their metabolic and transporter profile suggests pravastatin would have the least potential for interaction when coadministered with encorafenib.

CONCLUSION

The results from these clinical studies suggest that encorafenib does not cause clinically relevant CYP2B6 induction or inhibition but is an inhibitor of BCRP and may also inhibit OATP1B1/3 to a lesser extent. Based on these results, it may be necessary to consider switching statins or reducing statin dosage accordingly for coadministration with encorafenib.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov NCT03864042, registered 6 March 2019.

Identification and characterization of an endogenous biomarker of the renal vectorial transport (OCT2-MATE1)

The renal tubular organic cation transporter 2 (OCT2) and multidrug and toxin extrusion protein 1 (MATE1) mediate the vectorial elimination of many drugs and toxins from the kidney, and endogenous biomarkers for vectorial transport (OCT2-MATE1) would allow more accurate drug dosing and help to characterize drug-drug interactions and toxicity. Human serum uptake in OCT2-overexpressing cells and metabolomics analysis were carried out. Potential biomarkers were verified in vitro and in vivo. The specificity of biomarkers was validated in renal transporter overexpressing cells and the sensitivity was investigated by Km . The results showed that the uptake of thiamine, histamine, and 5-hydroxytryptamine was significantly increased in OCT2-overexpressing cells. In vitro assays confirmed that thiamine, histamine, and 5-hydroxytryptamine were substrates of both OCT2 and MATE1. In vivo measurements indicated that the serum thiamine level was increased significantly in the presence of the rOCT2 inhibitor cimetidine, and the level in renal tissue was increased significantly by the rMATE1 inhibitor pyrimethamine. There were no significant changes in the uptake or efflux of thiamine in cell lines overexpressed OAT1, OAT2, OAT3, MRP4, organic anion transporting polypeptide 4C1, P-gp, peptide transporter 2, urate transporter 1, and OAT4. The Km for thiamine with OCT2 and MATE1 were 71.2 and 10.8 μM, respectively. In addition, the cumulative excretion of thiamine at 2 and 4 h was strongly correlated with metformin excretion (R2  > 0.6). Thus, thiamine is preferentially secreted by the OCT2 and MATE1 in renal tubules and can provide a reference value for evaluating the function of the renal tubular OCT2-MATE1.

The Effect of BI 730357 (Retinoic Acid-Related Orphan Receptor Gamma t Antagonist, Bevurogant) on the Pharmacokinetics of a Transporter Probe Cocktail, Including Digoxin, Furosemide, Metformin, and Rosuvastatin: An Open-Label, Non-randomized, 2-Period Fixed-Sequence Trial in Healthy Subjects

Evaluating Drug-Drug Interactions (DDIs) for new investigational compounds requires several trials evaluating different drugs with different transporter specificities. By using a cocktail of drugs with different transporter specificities, a single trial could evaluate the pharmacokinetics (PKs) of each cocktail drug simultaneously, reducing the number of clinical DDI trials required for clinical development. We aimed to investigate the effect of steady-state Boehringer Ingelheim (BI) 730357 (bevurogant) on the PKs of a validated and optimized 4-component transporter cocktail. This open-label, non-randomized, 2-period fixed-sequence phase I trial compared transporter cocktail (0.25 mg digoxin/1 mg furosemide/10 mg metformin hydrochloride/10 mg rosuvastatin) with and without BI 730357 in healthy subjects aged 18-55 years with body mass index 18.5-29.9 kg/m2 . During reference treatment/period 1, transporter cocktail was administered 90 minutes after breakfast. After a washout period, during test treatment/period 2, BI 730357 was dosed twice daily for 13 days, with transporter cocktail administered on day 1. The primary endpoints were the area under the concentration-time curve of the analyte in plasma over the time interval from 0 extrapolated to infinity (AUC0-∞ ) and the maximum measured concentration of the analyte in plasma (Cmax ), and the secondary endpoint was the area under the concentration-time curve of the analyte in plasma over the time interval from 0 to the last quantifiable data point (AUC0-tz ). Steady-state BI 730357 increased digoxin (+48% to +94%), minimally affected metformin (-2% to -9%), furosemide (+12% to +18%), and rosuvastatin (+19% to +39%) exposure. Therefore, no clinically relevant inhibition of transporters OCT2/MATE-1/MATE-2K, OAT1/OAT3, OATP1B1/OATP1B3 was observed. Potential inhibition of breast cancer resistance protein noted as PK parameters of coproporphyrin I/III (OATP1B1/OATP1B3 biomarkers) remained within bioequivalence boundaries while rosuvastatin PK parameters (AUC0-∞ /Cmax /AUC0-tz ) exceeded the bioequivalence boundary. BI 730357 was safe and well tolerated. This trial confirms the usefulness and tolerability of the transporter cocktail consisting of digoxin, furosemide, metformin, and rosuvastatin in assessing drug-transporter interactions in vivo.

Determination of furosemide and its glucuronide metabolite in plasma, plasma ultrafiltrate and urine by HPLC-MS/MS with application to secretion and metabolite formation clearances in non-pregnant and pregnant women

Furosemide (FUR) has been used in probe drugs cocktails for in vivo evaluation of the renal transporters OAT1 and OAT3 activities in studies of drug-drug interactions (generally using probenecid as an inhibitor) and drug-disease interactions. The objective of this study was to develop and validate methods for FUR and its glucuronide metabolite (FUR-GLU) analysis in plasma, plasma ultrafiltrate and urine for application in pharmacokinetics studies: a pilot drug-drug interaction study in pregnant women (n = 2), who received a single oral dose of FUR (40 mg) and in another occasion a single oral dose of probenecid (750 mg) before a single oral dose of FUR (40 mg), and in non-pregnant women participants (n = 12), who only received a single oral dose of FUR (40 mg). The samples preparation for FUR in 50 µL of plasma and plasma lysate were carried by acidified liquid-liquid extraction, while 50 µL of urine and 200 µL of plasma ultrafiltrate were simply diluted with the mobile phase. The methods presented linearities in the range of 0.50 - 2500 ng/mL of plasma and plasma lysate, 0.125 - 250 ng/mL of plasma ultrafiltrate, and 50 - 20,000 ng/mL of urine. FUR-GLU methods presented linearities in the range of 0.125 - 250 ng/mL of plasma ultrafiltrate and 50 - 20,000 ng/mL of urine. Precision and accuracy evaluations showed coefficients of variation and relative errors < 15%. In the pregnant women participants, the mean values of FUR CLrenal, CLsecretion, CLformation. FUR-GLU and CLnon-renal were all reduced when probenecid was administered with FUR (8.24 vs 2.89 L/h, 8.15 vs 2.80 L/h, 3.86 vs 1.75 L/h, 48.26 vs 22.10 L/h, respectively). Non-pregnant women presented similar values of FUR CLrenal, CLsecretion, CLformation. FUR-GLU to the pregnant women who received FUR only. Finally, FUR fraction unbound (fu) resulted in values of approximately 1% in pregnant women and to 0.22% in non-pregnant women. These developed and validated methods for FUR and FUR-GLU quantification in multiple matrices can allow the further investigation of UGT1A9/1A1 and the fu when FUR is administered as an OAT 1 and 3 in vivo probe.

The Impact of Inflammation on the In Vivo Activity of the Renal Transporters OAT1/3 in Pregnant Women Diagnosed with Acute Pyelonephritis

Inflammation can regulate hepatic drug metabolism enzymes and transporters. The impact of inflammation on renal drug transporters remains to be elucidated. We aimed to quantify the effect of inflammation (caused by acute pyelonephritis) on the in vivo activity of renal OAT1/3, using the probe drug furosemide. Pregnant women (second or third trimester) received a single oral dose of furosemide 40 mg during acute pyelonephritis (Phase 1; n = 7) and after its resolution (Phase 2; n = 7; by treatment with intravenous cefuroxime 750 mg TID for 3-7 days), separated by 10 to 14 days. The IL-6, IFN-γ, TNF-α, MCP-1, and C-reactive protein plasma concentrations were higher in Phase I vs. Phase II. The pregnant women had a lower geometric mean [CV%] furosemide CLsecretion (3.9 [43.4] vs. 6.7 [43.8] L/h) and formation clearance to the glucuronide (1.1 [85.9] vs. 2.3 [64.1] L/h) in Phase 1 vs. Phase 2. Inflammation reduced the in vivo activity of renal OAT1/3 (mediating furosemide CLsecretion) and UGT1A9/1A1 (mediating the formation of furosemide glucuronide) by approximately 40% and 54%, respectively, presumably by elevating the plasma cytokine concentrations. The dosing regimens of narrow therapeutic window OAT drug substrates may need to be adjusted during inflammatory conditions.

Pharmacokinetic and Pharmacodynamic Drug-Drug Interactions: Research Methods and Applications

Because of the high research and development cost of new drugs, the long development process of new drugs, and the high failure rate at later stages, combining past drugs has gradually become a more economical and attractive alternative. However, the ensuing problem of drug-drug interactions (DDIs) urgently need to be solved, and combination has attracted a lot of attention from pharmaceutical researchers. At present, DDI is often evaluated and investigated from two perspectives: pharmacodynamics and pharmacokinetics. However, in some special cases, DDI cannot be accurately evaluated from a single perspective. Therefore, this review describes and compares the current DDI evaluation methods based on two aspects: pharmacokinetic interaction and pharmacodynamic interaction. The methods summarized in this paper mainly include probe drug cocktail methods, liver microsome and hepatocyte models, static models, physiologically based pharmacokinetic models, machine learning models, in vivo comparative efficacy studies, and in vitro static and dynamic tests. This review aims to serve as a useful guide for interested researchers to promote more scientific accuracy and clinical practical use of DDI studies.

In vitro validation of an in vivo phenotyping drug cocktail for major drug transporters in humans

PURPOSE

Cocktails of transporter probe drugs are used in vivo to assess transporter activity and respective drug-drug interactions. An inhibitory effect of components on transporter activities should be ruled out. Here, for a clinically tested cocktail consisting of adefovir, digoxin, metformin, sitagliptin, and pitavastatin, inhibition of major transporters by individual probe substrates was investigated in vitro.

METHODS

Transporter transfected HEK293 cells were used in all evaluations. Cell-based assays were applied for uptake by human organic cation transporters 1/2 (hOCT1/2), organic anion transporters 1/3 (hOAT1/3), multidrug and toxin extrusion proteins 1/2K (hMATE1/2K), and organic anion transporter polypeptide 1B1 (hOATP1B1). For P-glycoprotein (hMDR1) a cell-based efflux assay was used whereas an inside-out vesicle-based assay was used for the bile salt export pump (hBSEP). All assays used standard substrates and established inhibitors (as positive controls). Inhibition experiments using clinically achievable concentrations of potential perpetrators at the relevant transporter expression site were carried out initially. If there was a significant effect, the inhibition potency (K_i) was studied in detail.

RESULTS

In the inhibition tests, only sitagliptin had an effect and reduced hOCT1- and hOCT2- mediated metformin uptake and hMATE2K mediated MPP⁺ uptake by more than 70%, 80%, and 30%, respectively. The ratios of unbound C_max (observed clinically) to K_i of sitagliptin were low with 0.009, 0.03, and 0.001 for hOCT1, hOCT2, and hMATE2K, respectively.

CONCLUSION

The inhibition of hOCT2 in vitro by sitagliptin is in agreement with the borderline inhibition of renal metformin elimination observed clinically, supporting a dose reduction of sitagliptin in the cocktail.

Phenotyping Indices of CYP450 and P-Glycoprotein in Human Volunteers and in Patients Treated with Painkillers or Psychotropic Drugs

Drug-metabolizing enzymes and drug transporters are key determinants of drug pharmacokinetics and response. The cocktail-based cytochrome P450 (CYP) and drug transporter phenotyping approach consists in the administration of multiple CYP or transporter-specific probe drugs to determine their activities simultaneously. Several drug cocktails have been developed over the past two decades in order to assess CYP450 activity in human subjects. However, phenotyping indices were mostly established for healthy volunteers. In this study, we first performed a literature review of 27 clinical pharmacokinetic studies using drug phenotypic cocktails in order to determine 95%,95% tolerance intervals of phenotyping indices in healthy volunteers. Then, we applied these phenotypic indices to 46 phenotypic assessments processed in patients having therapeutic issues when treated with painkillers or psychotropic drugs. Patients were given the complete phenotypic cocktail in order to explore the phenotypic activity of CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A, and P-glycoprotein (P-gp). P-gp activity was evaluated by determining AUC_0-6h for plasma concentrations over time of fexofenadine, a well-known substrate of P-gp. CYP metabolic activities were assessed by measuring the CYP-specific metabolite/parent drug probe plasma concentrations, yielding single-point metabolic ratios at 2 h, 3 h, and 6 h or AUC_0-6h ratio after oral administration of the cocktail. The amplitude of phenotyping indices observed in our patients was much wider than those observed in the literature for healthy volunteers. Our study helps define the range of phenotyping indices with "normal" activities in human volunteers and allows classification of patients for further clinical studies regarding CYP and P-gp activities.

Studying the right transporter at the right time: an in vitro strategy for assessing drug-drug interaction risk during drug discovery and development

INTRODUCTION

Transporters are significant in dictating drug pharmacokinetics, thus inhibition of transporter function can alter drug concentrations resulting in drug-drug interactions (DDIs). Because they can impact drug toxicity, transporter DDIs are a regulatory concern for which prediction of clinical effect from in vitro data is critical to understanding risk.

AREA COVERED

The authors propose in vitro strategies to assist mitigating/removing transporter DDI risk during development by frontloading specific studies, or managing patient risk in the clinic. An overview of clinically relevant drug transporters and observed DDIs are provided, alongside presentation of key considerations/recommendations for in vitro study design evaluating drugs as inhibitors or substrates. Guidance on identifying critical co-medications, clinically relevant disposition pathways and using mechanistic static equations for quantitative prediction of DDI is compiled.

EXPERT OPINION

The strategies provided will facilitate project teams to study the right transporter at the right time to minimise development risks associated with DDIs. To truly alleviate or manage clinical risk, the industry will benefit from moving away from current qualitative basic static equation approaches to transporter DDI hazard assessment towards adopting the use of mechanistic models to enable quantitative DDI prediction, thereby contextualising risk to ascertain whether a transporter DDI is simply pharmacokinetic or clinically significant requiring intervention.

Pharmacoproteomics of Brain Barrier Transporters and Substrate Design for the Brain Targeted Drug Delivery

One of the major reasons why central nervous system (CNS)-drug development has been challenging in the past, is the barriers that prevent substances entering from the blood circulation into the brain. These barriers include the blood-brain barrier (BBB), blood-spinal cord barrier (BSCB), blood-cerebrospinal fluid barrier (BCSFB), and blood-arachnoid barrier (BAB), and they differ from each other in their transporter protein expression and function as well as among the species. The quantitative expression profiles of the transporters in the CNS-barriers have been recently revealed, and in this review, it is described how they affect the pharmacokinetics of compounds and how these expression differences can be taken into account in the prediction of brain drug disposition in humans, an approach called pharmacoproteomics. In recent years, also structural biology and computational resources have progressed remarkably, enabling a detailed understanding of the dynamic processes of transporters. Molecular dynamics simulations (MDS) are currently used commonly to reveal the conformational changes of the transporters and to find the interactions between the substrates and the protein during the binding, translocation in the transporter cavity, and release of the substrate on the other side of the membrane. The computational advancements have also aided in the rational design of transporter-utilizing compounds, including prodrugs that can be actively transported without losing potency towards the pharmacological target. In this review, the state-of-art of these approaches will be also discussed to give insights into the transporter-mediated drug delivery to the CNS.

Effect of enzalutamide on PK of P-gp and BCRP substrates in cancer patients: CYP450 induction may not always predict overall effect on transporters

Drug‐drug interaction (DDI) is an important consideration for clinical decision making in prostate cancer treatment. The objective of this study was to evaluate the effect of enzalutamide, an oral androgen receptor inhibitor, on the pharmacokinetics (PK) of digoxin (P‐glycoprotein [P‐gp] probe substrate) and rosuvastatin (breast cancer resistance protein [BCRP] probe substrate) in men with metastatic castration‐resistant prostate cancer (mCRPC). This was a phase I, open‐label, fixed‐sequence, crossover study (NCT04094519). Eligible men with mCRPC received a single dose of transporter probe cocktail containing 0.25 mg digoxin and 10 mg rosuvastatin plus enzalutamide placebo‐to‐match on day 1. On day 8, patients started 160 mg enzalutamide once daily through day 71. On day 64, patients also received a single dose of the cocktail. The primary end points were digoxin and rosuvastatin plasma maximum concentration (C_max), area under the concentration‐time curve from the time of dosing to the last measurable concentration (AUC_last), and AUC from the time of dosing extrapolated to time infinity (AUC_inf). Secondary end points were enzalutamide and N‐desmethyl enzalutamide (metabolite) plasma C_max, AUC during a dosing interval, where tau is the length of the dosing interval (AUC_tau), and concentration immediately prior to dosing at multiple dosing (C_trough). When administered with enzalutamide, there was a 17% increase in C_max, 29% increase in AUC_last, and 33% increase in AUC_inf of plasma digoxin compared to digoxin alone, indicating that enzalutamide is a “mild” inhibitor of P‐gp. No PK interaction was observed between enzalutamide and rosuvastatin (BCRP probe substrate). The PK of enzalutamide and N‐desmethyl enzalutamide were in agreement with previously reported data. The potential for transporter‐mediated DDI between enzalutamide and digoxin and rosuvastatin is low in men with prostate cancer. Therefore, concomitant administration of enzalutamide with medications that are substrates for P‐gp and BCRP does not require dose adjustment in this patient population.

Assessment of drug-drug interactions of CC-90001, a potent and selective inhibitor of c-Jun N-terminal kinase

CC-90001 is predominantly metabolised via glucuronidation, while oxidative metabolism is a minor pathway in human hepatocytes and liver microsomes. In vitro, CC-90001 glucuronidation was catalysed by UGT1A9, UGT1A4, and UGT1A1, while oxidative metabolism was primarily mediated by CYP3A4/5 with minor contributions from CYP1A2, CYP2C9, CYP2B6, and CYP2D6.CC-90001 in vitro inhibits CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, and CYP3A4 ≤ 55% at 100 μM, and the inhibition was negligible at ≤30 μM. CC-90001 is not a time-dependent CYP inhibitor.In human hepatocytes CC-90001 is an inducer of CYP2B6 and CYP3A, with mRNA levels increased 34.4% to 52.8% relative to positive controls.In vitro CC-90001 is a substrate of P-gp, and an inhibitor of P-gp, BCRP, OAT3, OATP1B1, OATP1B3, OCT2, MATE1, and MATE2k with IC₅₀ values of 30.3, 25.8, 17.7, 0.417, 19.9, 0.605, 4.17, and 20 μM, respectively.A clinical study demonstrated that CC-90001 has no or little impact on the exposure of warfarin (CYP2C9), omeprazole (CYP2C19), midazolam (CYP3A) or metformin (OCT2, MATE1/2k). CC-90001 co-administration increases the AUC_t and C_max 176% and 339% for rosuvastatin (BCRP/OATP1B1/3), 116% and 171% for digoxin (P-gp), and 266% and 321% for nintedanib (CYP3A & P-gp), respectively.In conclusion, CC-90001 in unlikely to be a victim or perpetrator of clinically relevant interactions involving CYPs or UGTs. Weak to moderate interactions are expected in clinic with substrates of P-gp and OATP1B1 due to CC-90001 inhibition of these transporters.

Physiologically Based Pharmacokinetic Modeling of Rosuvastatin to Predict Transporter-Mediated Drug-Drug Interactions

Purpose

To build a physiologically based pharmacokinetic (PBPK) model of the clinical OATP1B1/OATP1B3/BCRP victim drug rosuvastatin for the investigation and prediction of its transporter-mediated drug-drug interactions (DDIs).

Methods

The Rosuvastatin model was developed using the open-source PBPK software PK-Sim®, following a middle-out approach. 42 clinical studies (dosing range 0.002–80.0 mg), providing rosuvastatin plasma, urine and feces data, positron emission tomography (PET) measurements of tissue concentrations and 7 different rosuvastatin DDI studies with rifampicin, gemfibrozil and probenecid as the perpetrator drugs, were included to build and qualify the model.

Results

The carefully developed and thoroughly evaluated model adequately describes the analyzed clinical data, including blood, liver, feces and urine measurements. The processes implemented to describe the rosuvastatin pharmacokinetics and DDIs are active uptake by OATP2B1, OATP1B1/OATP1B3 and OAT3, active efflux by BCRP and Pgp, metabolism by CYP2C9 and passive glomerular filtration. The available clinical rifampicin, gemfibrozil and probenecid DDI studies were modeled using in vitro inhibition constants without adjustments. The good prediction of DDIs was demonstrated by simulated rosuvastatin plasma profiles, DDI AUC_last ratios (AUC_last during DDI/AUC_last without co-administration) and DDI C_max ratios (C_max during DDI/C_max without co-administration), with all simulated DDI ratios within 1.6-fold of the observed values.

Conclusions

A whole-body PBPK model of rosuvastatin was built and qualified for the prediction of rosuvastatin pharmacokinetics and transporter-mediated DDIs. The model is freely available in the Open Systems Pharmacology model repository, to support future investigations of rosuvastatin pharmacokinetics, rosuvastatin therapy and DDI studies during model-informed drug discovery and development (MID3).

Supplementary Information

The online version contains supplementary material available at 10.1007/s11095-021-03109-6.

Assessment of Transporter-Mediated Drug Interactions for Enasidenib Based on a Cocktail Study in Patients With Relapse or Refractory Acute Myeloid Leukemia or Myelodysplastic Syndrome

As a first-in-class, selective, potent inhibitor of the isocitrate dehydrogenase-2 (IDH2) mutant protein, enasidenib was approved by the US Food and Drug Administration in 2017 for the treatment of adult patients with relapsed or refractory acute myeloid leukemia with an isocitrate dehydrogenase-2 mutation. An in vitro study showed that enasidenib at clinically relevant concentrations has effects on multiple drug metabolic enzymes and transporters, including inhibition of P-glycoprotein, breast cancer resistance protein, organic anion transporter (OAT) P1B1, and OATP1B3 transporters. Therefore, a drug-drug interaction study was conducted to assess the impact of enasidenib at steady state on the pharmacokinetics of several probe compounds in patients with relapsed or refractory acute myeloid leukemia or myelodysplastic syndrome, including the probes herein described in this article, digoxin and rosuvastatin. Results from 8 patients (all Asian) with a mean age of 67.1 years showed that following coadministration of enasidenib (100 mg, 28-day once-daily schedule) for 28 days (at steady state), digoxin's (0.25 mg) area under the plasma concentration-time curve from time 0 to 30 days was 1.2-fold (90% confidence interval, 0.9-1.6), compared with digoxin alone. Following coadministration of enasidenib (100 mg, 28-day once-daily schedule) for 28 days (at steady state), rosuvastatin's (10 mg) area under the plasma concentration-time curve from time 0 to infinity was 3.4-fold (90% confidence interval, 2.6-4.5) compared with rosuvastatin alone. These results should serve as the basis for dose recommendations for drugs that are substrates of P-glycoprotein, breast cancer resistance protein, OATP1B1, and OATP1B3 transporters, when used concomitantly with enasidenib.

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.

Impact of fedratinib on the pharmacokinetics of transporter probe substrates using a cocktail approach

INTRODUCTION

Fedratinib, an oral, selective Janus kinase 2 inhibitor, has been shown to inhibit P-glycoprotein (P-gp), breast cancer resistance protein (BCRP), organic anion transporting polypeptide (OATP) 1B1, OATP1B3, organic cation transporter (OCT) 2, and multidrug and toxin extrusion (MATE) 1 and MATE2-K in vitro. The objective of this study was to evaluate the influence of fedratinib on the pharmacokinetics (PK) of digoxin (P-gp substrate), rosuvastatin (OATP1B1/1B3 and BCRP substrate), and metformin (OCT2 and MATE1/2-K substrate).

METHODS

In this nonrandomized, fixed-sequence, open-label study, 24 healthy adult participants received single oral doses of digoxin 0.25 mg, rosuvastatin 10 mg, and metformin 1000 mg administered as a drug cocktail (day 1, period 1). After a 6-day washout, participants received oral fedratinib 600 mg 1 h before the cocktail on day 7 (period 2). An oral glucose tolerance test (OGTT) was performed to determine possible influences of fedratinib on the antihyperglycemic effect of metformin.

RESULTS

Plasma exposure to the three probe drugs was generally comparable in the presence or absence of fedratinib. Reduced metformin renal clearance by 36% and slightly higher plasma glucose levels after OGTT were observed in the presence of fedratinib. Single oral doses of the cocktail ± fedratinib were generally well tolerated.

CONCLUSIONS

These results suggest that fedratinib has minimal impact on the exposure of P-gp, BCRP, OATP1B1/1B3, OCT2, and MATE1/2-K substrates. Since renal clearance of metformin was decreased in the presence of fedratinib, caution should be exercised in using coadministered drugs that are renally excreted via OCT2 and MATEs.

TRIAL REGISTRATION

Clinicaltrials.gov NCT04231435 on January 18, 2020.

Feature, Function, and Information of Drug Transporter Related Databases

With the rapid progress in pharmaceutical experiments and clinical investigations, extensive knowledge of drug transporters (DTs) has accumulated, which is valuable data for the understanding of drug metabolism and disposition. However, such data is largely dispersed in the literature, which hampers its utility and significantly limits its possibility for comprehensive analysis. A variety of databases have, therefore, been constructed to provide DT-related data, and they were reviewed in this study. First, several knowledge bases providing data regarding clinically important drugs and their corresponding transporters were discussed, which constituted the most important resources of DT-centered data. Second, some databases describing the general transporters and their functional families were reviewed. Third, various databases offering transporter information as part of their entire data collection were described. Finally, customized database functions that are available to facilitate DT-related research were discussed. This review provided an overview of the whole collection of DT-related databases, which might facilitate research on precision medicine and rational drug use. Significance Statement A collection of well-established databases related to DTs were comprehensively reviewed, which were organized according to their importance in drug ADME research. These databases could collectively contribute to the research on rational drug use.

Evaluation of Pharmacokinetics, Safety, and Drug-Drug Interactions of an Oral Suspension of Edaravone in Healthy Adults

Intravenous (IV) edaravone is approved as an amyotrophic lateral sclerosis (ALS) treatment. Because IV administration places a burden on patients, development of orally administered ALS treatments is needed. Therefore, 2 phase 1 studies of oral formulations of edaravone in healthy subjects examined the pharmacokinetics (PK), safety, racial differences, and drug‐drug interactions (DDIs) and investigated the dose of the oral formulation considered to be bioequivalent to the approved dose of the IV formulation. Study 1 was a placebo‐controlled, randomized, single‐blind study of single‐ascending‐dose oral edaravone with the dose range of 30 to 300 mg (n = 56). Study 2 was conducted in 2 cohorts (n = 84); the first assessed DDIs with multiple‐dose edaravone 120 mg/day given over 5 or 8 days (coadministered with single‐dose rosuvastatin, sildenafil, or furosemide), and the second evaluated PK and racial (Japanese/White) differences in PK parameters with doses of 100‐mg edaravone. The oral formulation of edaravone was well absorbed, and plasma concentrations of unchanged edaravone increased more than dose proportionally within the dose range of 30 to 300 mg. No effect of race on oral edaravone PK and no notable DDI effects possibly caused by orally administered edaravone were observed. The oral edaravone formulations were safe and tolerable under the assessed conditions. Mathematical modeling determined that equivalent exposures in plasma with the approved dose of the IV edaravone formulation, as reported previously, could be achieved when the oral edaravone formulation was administered at a dose of  ≈100 mg, with an absolute bioavailability of ≈60%.

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.

Evaluation of drug interaction potential of zanubrutinib with cocktail probes representative of CYP3A4, CYP2C9, CYP2C19, P-gp and BCRP

Aim

This study aims to assess the potential effects of zanubrutinib on the activity of cytochrome P450 (CYP) enzymes and drug transporter proteins using a cocktail probe approach.

Methods

Patients received single oral doses of probe drugs alone and after at least 8 days of treatment with zanubrutinib 160 mg twice daily in a single‐sequence study in 18 healthy male volunteers. Simultaneous doses of 10 mg warfarin (CYP2C9) and 2 mg midazolam (CYP3A) were administered on Day 1 and Day 14, 0.25 mg digoxin (P‐glycoprotein [P‐gp]) and 10 mg rosuvastatin (breast cancer resistance protein [BCRP]) on Day 3 and Day 16, and 20 mg omeprazole (CYP2C19) on Day 5 and Day 18. Pharmacokinetic (PK) parameters were estimated from samples obtained up to 12 h post dose for zanubrutinib; 24 h for digoxin, omeprazole and midazolam; 48 h for rosuvastatin; and 144 h for warfarin.

Results

The ratios (%) of geometric least squares means (90% confidence intervals) for the area under the concentration–time curve from time zero to the last quantifiable concentration in the presence/absence of zanubrutinib were 99.80% (97.41–102.2%) for S‐warfarin; 52.52% (48.49–56.88%) for midazolam; 111.3% (103.8–119.3%) for digoxin; 89.45% (78.73–101.6%) for rosuvastatin; and 63.52% (57.40–70.30%) for omeprazole. Similar effects were observed for maximum plasma concentrations.

Conclusions

Zanubrutinib 320 mg total daily dose had minimal or no effect on the activity of CYP2C9, BCRP and P‐gp, but decreased the systemic exposure of CYP3A and CYP2C19 substrates (mean reduction <50%).

Contribution of Uptake and Efflux Transporters to Oral Pharmacokinetics of Furosemide

Furosemide is a widely used diuretic for treating excessive fluid accumulation caused by disease conditions like heart failure and liver cirrhosis. Furosemide tablet formulation exhibits variable pharmacokinetics (PK) with bioavailability ranging from 10 to almost 100%. To explain the variable absorption, we integrated the physicochemical, in vitro dissolution, permeability, distribution, and the elimination parameters of furosemide in a physiologically-based pharmacokinetic (PBPK) model. Although the intravenous PBPK model reasonably described the observed in vivo PK data, the reported low passive permeability failed to capture the observed data after oral administration. To mechanistically justify this discrepancy, we hypothesized that transporter-mediated uptake contributes to the oral absorption of furosemide in conjunction with passive permeability. Our in vitro results confirmed that furosemide is a substrate of intestinal breast cancer resistance protein (BCRP), multidrug resistance-associated protein 4 (MRP4), and organic anion transporting polypeptide 2B1 (OATP2B1), but it is not a substrate of P-glycoprotein (P-gp) and MRP2. We then estimated the net transporter-mediated intestinal uptake and integrated it into the PBPK model under both fasting and fed conditions. Our in vitro data and PBPK model suggest that the absorption of furosemide is permeability-limited, and OATP2B1 and MRP4 are important for its permeability across intestinal membrane. Further, as furosemide has been proposed as a probe substrate of renal organic anion transporters (OATs) for assessing clinical drug-drug interactions (DDIs) during drug development, the confounding effects of intestinal transporters identified in this study on furosemide PK should be considered in the clinical transporter DDI studies.

Digoxin: Pharmacology and toxicology-A review

Digoxin is a cardiac glycoside used as drug in case of heart problems, including congestive heart failure, atrial fibrillation or flutter, and certain cardiac arrhythmias. It has a very narrow therapeutic window of the medication. Digoxin is toxic substance with well known cardiotoxic effect. In this work, pharmacology and toxicology of digoxin are summarized; Its pharmacokinetics, pharmacodynamics, available acute toxicity data (different species, different administration routes) are summarized in this article. Moreover, its treatment side effect and human poisonings are thoroughly discussed. Finally, appropriate therapy regimen is proposed.

Probe Cocktail to Assess Transporter Function in Sandwich-Cultured Human Hepatocytes

PURPOSE

Probe substrates are used routinely to assess transporter function in vitro. Administration of multiple probe substrates together as a "cocktail" in sandwich-cultured human hepatocytes (SCHH) could increase the throughput of transporter function assessment in a physiologically-relevant in vitro system. This study was designed to compare transporter function between cocktail and single agent administration in SCHH.

METHODS

Rosuvastatin, digoxin, and metformin were selected as probe substrates of hepatic transporters OATP1B1, OATP1B3, BCRP, P-gp, and OCT1. Total accumulation (Cells+Bile) and biliary excretion index (BEI) values derived from administration of the cocktail were compared to values obtained after administration of single agents in the absence and presence of a model inhibitor, erythromycin estolate.

RESULTS

For rosuvastatin and metformin accumulation, the ratio of means [90% confidence interval (CI)] for cocktail to single agent administration was 100% [94%, 106%] and 90% [82%, 99%], respectively. Therefore, the cocktail and single-agent mode of administration were deemed equivalent per standard equivalence criterion of 80-120% for rosuvastatin and metformin accumulation, but not for digoxin accumulation (77% [62%, 92%]). The ratio of means [90% CI] for rosuvastatin BEI values between the two administration modes (105% [97%, 114%]) also was deemed equivalent. The ratio for digoxin BEI values between the two administration modes was 99% [78%, 120%]. In the presence of erythromycin estolate, the two administration modes were deemed equivalent for evaluation of rosuvastatin, digoxin, and metformin accumulation; the ratio of means [90% CI] was 104% [94%, 115%], 94% [82%, 105%], and 100% [88%, 111%], respectively. However, rosuvastatin and digoxin BEI values were low and quite variable in the presence of the inhibitor, so the BEI results were inconclusive.

CONCLUSIONS

These data suggest that rosuvastatin and metformin can be administered as a cocktail to evaluate the function of OATP1B1, OATP1B3, BCRP, and OCT1 in SCHH, and that digoxin may not be an ideal component of such a cocktail.

A Pilot Study of the Maternal-Fetal Pharmacokinetics of Furosemide in Plasma, Urine, and Amniotic Fluid of Hypertensive Parturient Women Under Cesarean Section

The third trimester of pregnancy is related to physiological changes that can modify the process of absorption, distribution, metabolism, and excretion and, consequently, the efficacy and toxicity of drugs. However, little is known about furosemide pharmacokinetics and placental transfer in pregnancy. This study evaluated the maternal-fetal pharmacokinetics and distribution to amniotic fluid of furosemide in hypertensive parturient women under cesarean section. Twelve hypertensive parturient women under methyldopa (250 mg/8 h) and/or pindolol (10 mg/12 h) treatment received a 40-mg single oral dose of furosemide 1 to 10 hours before delivery by cesarean section. Blood and urine samples were collected for 12 hours after furosemide administration. At delivery, samples were obtained from maternal and umbilical cord blood (n = 8) to assess the transplacental transfer. Amniotic fluid (n = 4) was collected at the time of delivery. The following furosemide pharmacokinetic parameters were obtained as median (interquartile range): C_max , 403 ng/mL (229 to 715 ng/mL); T_max , 2.00 hours (1.50 to 4.83 hours); elimination half-life (t_1/2 ), 2.50 hours (1.77 to 2.97 hours); AUC_{0-12 h} , 1366 ng⋅h/mL (927 to 2531 ng⋅h/mL); AUC_0-∞ , 1580 ng⋅h/mL (1270 to 2881 ng⋅h/mL); CL/F 25.3 L/h (13.8 to 31.4 L/h); CLR, 2.50 L/h (1.77 to 2.97 L/h); CLNR, 22.7 L/h (12.1 to 25.6 L/h); and V_d /F 82.8 L (34.4 to 173 L). The transplacental transfer of furosemide was 0.43 (0.10 to 0.73), and the amniotic fluid concentration was 11.0 ng/mL (5.51 to 14.6 ng/mL). From a clinical point of view, these results suggest that substrates of uridine diphosphate-glucuronosyltransferase isoenzymes such as furosemide may have increased clearance during pregnancy and could require dose adjustment in this population.

VARIDT 1.0: variability of drug transporter database

The absorption, distribution and excretion of drugs are largely determined by their transporters (DTs), the variability of which has thus attracted considerable attention. There are three aspects of variability: epigenetic regulation and genetic polymorphism, species/tissue/disease-specific DT abundances, and exogenous factors modulating DT activity. The variability data of each aspect are essential for clinical study, and a collective consideration among multiple aspects becomes crucial in precision medicine. However, no database is constructed to provide the comprehensive data of all aspects of DT variability. Herein, the Variability of Drug Transporter Database (VARIDT) was introduced to provide such data. First, 177 and 146 DTs were confirmed, for the first time, by the transporting drugs approved and in clinical/preclinical, respectively. Second, for the confirmed DTs, VARIDT comprehensively collected all aspects of their variability (23 947 DNA methylations, 7317 noncoding RNA/histone regulations, 1278 genetic polymorphisms, differential abundance profiles of 257 DTs in 21 781 patients/healthy individuals, expression of 245 DTs in 67 tissues of human/model organism, 1225 exogenous factors altering the activity of 148 DTs), which allowed mutual connection between any aspects. Due to huge amount of accumulated data, VARIDT made it possible to generalize characteristics to reveal disease etiology and optimize clinical treatment, and is freely accessible at: https://db.idrblab.org/varidt/ and http://varidt.idrblab.net/.

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

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

Physiologically-Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug-Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations

Physiologically-based pharmacokinetic (PBPK) modeling has been extensively used to quantitatively translate in vitro data and evaluate temporal effects from drug-drug interactions (DDIs), arising due to reversible enzyme and transporter inhibition, irreversible time-dependent inhibition, enzyme induction, and/or suppression. PBPK modeling has now gained reasonable acceptance with the regulatory authorities for the cytochrome-P450-mediated DDIs and is routinely used. However, the application of PBPK for transporter-mediated DDIs (tDDI) in drug development is relatively uncommon. Because the predictive performance of PBPK models for tDDI is not well established, here, we represent and discuss examples of PBPK analyses included in regulatory submission (the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), and the Pharmaceuticals and Medical Devices Agency (PMDA)) across various tDDIs. The goal of this collaborative effort (involving scientists representing 17 pharmaceutical companies in the Consortium and from academia) is to reflect on the use of current databases and models to address tDDIs. This challenges the common perceptions on applications of PBPK for tDDIs and further delves into the requirements to improve such PBPK predictions. This review provides a reflection on the current trends in PBPK modeling for tDDIs and provides a framework to promote continuous use, verification, and improvement in industrialization of the transporter PBPK modeling.

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

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

A Clinical Drug-Drug Interaction Study Assessing a Novel Drug Transporter Phenotyping Cocktail With Adefovir, Sitagliptin, Metformin, Pitavastatin, and Digoxin

A new probe drug cocktail containing substrates of important drug transporters was tested for mutual interactions in a clinical trial. The cocktail consisted of (predominant transporter; primary phenotyping metric): 10 mg adefovir-dipivoxil (OAT1; renal clearance (CL_R )), 100 mg sitagliptin (OAT3; CL_R ), 500 mg metformin (several renal transporters; CL_R ), 2 mg pitavastatin (OATP1B1; clearance/F), and 0.5 mg digoxin (intestinal P-gp, renal P-gp, and OATP4C1; peak plasma concentration (C_max ) and CL_R ). Using a randomized six-period, open change-over design, single oral doses were administrated either concomitantly or separately to 24 healthy male and female volunteers. Phenotyping metrics were evaluated by noncompartmental analysis and compared between periods by the standard average bioequivalence approach (boundaries for ratios 0.80-1.25). Primary metrics supported the absence of relevant interactions, whereas secondary metrics suggested that mainly adefovir was a victim of minor drug-drug interactions (DDIs). All drugs were well tolerated. This cocktail may be another useful tool to assess transporter-based DDIs in vivo.

No Effect of Digoxin on Rosuvastatin Pharmacokinetics in Healthy Subjects: Utility of Oita Combination for Clinical Drug-Drug Interaction Study

This study evaluated the utility of combination of digoxin (0.25 mg) and rosuvastatin (5 mg) as a new transporter (P-glycoprotein/breast cancer resistance protein/organic anion-transporting polypeptide (OATP)1B1/OATP1B3) probe cocktail (Oita combination) for drug-drug interaction (DDI) studies by demonstrating lack of DDI of digoxin on the pharmacokinetics (PKs) of rosuvastatin, as it was already known that rosuvastatin did not affect digoxin PK. This was an open-label, two-period study in which the primary end points were the geometric mean ratio (GMR) of the area under the plasma rosuvastatin concentration-time curve from time zero to last (AUC_last ) after rosuvastatin administration combined with digoxin to that after rosuvastatin administration alone and its 90% confidence interval (CI). As the GMR of AUC_last was 0.974 and its 90% CI was 0.911-1.042, it was judged that digoxin does not affect rosuvastatin PK. Results of this study have rationalized utility of the Oita combination as a transporter probe cocktail for clinical DDI studies.

Clinical Studies on Drug-Drug Interactions Involving Metabolism and Transport: Methodology, Pitfalls, and Interpretation

Many drug-drug interactions (DDIs) are based on alterations of the plasma concentrations of a victim drug due to another drug causing inhibition and/or induction of the metabolism or transporter-mediated disposition of the victim drug. In the worst case, such interactions cause more than tenfold increases or decreases in victim drug exposure, with potentially life-threatening consequences. There has been tremendous progress in the predictability and modeling of DDIs. Accordingly, the combination of modeling approaches and clinical studies is the current mainstay in evaluation of the pharmacokinetic DDI risks of drugs. In this paper, we focus on the methodology of clinical studies on DDIs involving drug metabolism or transport. We specifically present considerations related to general DDI study designs, recommended enzyme and transporter index substrates and inhibitors, pharmacogenetic perspectives, index drug cocktails, endogenous substrates, limited sampling strategies, physiologically-based pharmacokinetic modeling, complex DDIs, methodological pitfalls, and interpretation of DDI information.

ABCG2/BCRP: variants, transporter interaction profile of substrates and inhibitors

INTRODUCTION

ABCG2 has a broad substrate specificity and is one of the most important efflux proteins modulating pharmacokinetics of drugs, nutrients and toxicokinetics of toxicants. ABCG2 is an important player in transporter-mediated drug-drug interactions (tDDI). Areas covered: The aims of the review are i) to cover transporter interaction profile of substrates and inhibitors that can be utilized to test interaction of drug candidates with ABCG2, ii) to highlight main characteristics of in vitro testing and iii) to describe the structural basis of the broad substrate specificity of the protein. Preclinical data utilizing Abcg2/Bcrp1 knockouts and clinical studies showing effect of ABCG2 c.421C>A polymorphism on pharmacokinetics of drugs have provided evidence for a broad array of drug substrates and support drug - ABCG2 interaction testing. A consensus on using rosuvastatin and sulfasalazine as intestinal substrates for clinical studies is in the formation. Other substrates relevant to the therapeutic area can be considered. Monolayer efflux assays and vesicular transport assays have been extensively utilized in vitro. Expert opinion: Clinical substrates display complex pharmacokinetics due to broad interaction profiles with multiple transporters and metabolic enzymes. Substrate-dependent inhibition has been observed for several inhibitors. Harmonization of in vitro and in vivo testing makes sense. However, rosuvastatin and sulfasalazine are not efficiently transported in either MDCKII or LLC-PK1-based monolayers. Caco-2 monolayer assays and vesicular transport assays are potential alternatives.

Biomarkers for In Vivo Assessment of Transporter Function

Drug-drug interactions are a major concern not only during clinical practice, but also in drug development. Due to limitations of in vitro-in vivo predictions of transporter-mediated drug-drug interactions, multiple clinical Phase I drug-drug interaction studies may become necessary for a new molecular entity to assess potential drug interaction liabilities. This is a resource-intensive process and exposes study participants, who frequently are healthy volunteers without benefit from study treatment, to the potential risks of a new drug in development. Therefore, there is currently a major interest in new approaches for better prediction of transporter-mediated drug-drug interactions. In particular, researchers in the field attempt to identify endogenous compounds as biomarkers for transporter function, such as hexadecanedioate, tetradecanedioate, coproporphyrins I and III, or glycochenodeoxycholate sulfate for hepatic uptake via organic anion transporting polypeptide 1B or N¹-methylnicotinamide for multidrug and toxin extrusion protein-mediated renal secretion. We summarize in this review the currently proposed biomarkers and potential limitations of the substances identified to date. Moreover, we suggest criteria based on current experiences, which may be used to assess the suitability of a biomarker for transporter function. Finally, further alternatives and supplemental approaches to classic drug-drug interaction studies are discussed.

A Strategy to Refine the Phenotyping Approach and Its Implementation to Predict Drug Clearance: A Physiologically Based Pharmacokinetic Simulation Study

The phenotyping approach to predict drug metabolism activity is often hampered by a lack of correlation between the probe and the drug of interest. In this article, we present a strategy to refine the phenotyping approach based on a physiologically based pharmacokinetic simulation (implemented in Simcyp Simulator version 17) using previously published models. The apparent clearance (CL/F) of erlotinib was better predicted by the sum of caffeine and i.v. midazolam CL/F (r²  = 0.60) compared to that of either probe drug alone. The clearance of atorvastatin and repaglinide had a strong correlation (r²  = 0.70 and 0.63, respectively) with that of pitavastatin (a SLCO1B1 probe). Use of multiple probes for drugs that are predominantly metabolized by more than one cytochrome P450 (CYP) enzyme should be considered. In a case in which hepatic uptake transporters play a significant role in the disposition of a drug, the pharmacokinetic of a transporter probe will provide better predictions of the drug clearance.

Assessment of Pharmacokinetic Drug-Drug Interactions in Humans: In Vivo Probe Substrates for Drug Metabolism and Drug Transport Revisited

Pharmacokinetic parameters of selective probe substrates are used to quantify the activity of an individual pharmacokinetic process (PKP) and the effect of perpetrator drugs thereon in clinical drug-drug interaction (DDI) studies. For instance, oral caffeine is used to quantify hepatic CYP1A2 activity, and oral dagibatran etexilate for intestinal P-glycoprotein (P-gp) activity. However, no probe substrate depends exclusively on the PKP it is meant to quantify. Lack of selectivity for a given enzyme/transporter and expression of the respective enzyme/transporter at several sites in the human body are the main challenges. Thus, a detailed understanding of the role of individual PKPs for the pharmacokinetics of any probe substrate is essential to allocate the effect of a perpetrator drug to a specific PKP; this is a prerequisite for reliably informed pharmacokinetic models that will allow for the quantitative prediction of perpetrator effects on therapeutic drugs, also in respective patient populations not included in DDI studies.

Effects of Metformin and Furosemide on Rosuvastatin Pharmacokinetics in Healthy Volunteers: Implications for Their Use as Probe Drugs in a Transporter Cocktail

Background

In a recently described probe drug cocktail for clinically relevant drug transporters containing digoxin, furosemide, metformin and rosuvastatin, mutual interactions were essentially absent except for increases in the systemic exposure of rosuvastatin. To optimize the cocktail, we further examined the dose dependence of the effects of metformin and furosemide on rosuvastatin pharmacokinetics.

Methods

This was a randomized, open label, single center, six-treatment, six-period, six-sequence crossover trial. Eighteen healthy male subjects received 10 mg rosuvastatin as reference treatment and, as test treatments, 10 mg rosuvastatin combined with 10, 50 or 500 mg metformin (T1, T2 and T3) or with 1 or 5 mg furosemide (T4 and T5). Primary pharmacokinetic endpoints were rosuvastatin C_max (maximum plasma concentration) and AUC_0–tz (area under the plasma concentration–time curve from time zero to the last quantifiable concentration).

Results

The relative bioavailability of rosuvastatin was essentially unchanged when administered with metformin in T1 and T2, but in T3 it increased to 152% for AUC_0–tz (90% CI 135–171%) and 154% for C_max (90% CI 132–180%). Coadministration with furosemide did not change rosuvastatin relative bioavailability in T4, but in T5 it increased slightly to 116% for AUC_0–tz (90% CI 102–132%) and 118% for C_max (90% CI 98–142%).

Conclusion

The increased systemic exposure of rosuvastatin when administered as part of the proposed transporter cocktail is most likely attributable to metformin and only to a minor degree to furosemide. Reduction of the doses of metformin and furosemide is expected to eliminate the previously described interaction.

EudraCT no. 2015-003052-46, ClinicalTrials.gov identifier NCT02574845.

Simultaneous Determination of Five Cytochrome P450 Probe Substrates and Their Metabolites and Organic Anion Transporting Polypeptide Probe Substrate in Human Plasma Using Liquid Chromatography-Tandem Mass Spectrometry

A rapid and selective liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous determination of organic anion transporting polypeptide 1B1 (OATP1B1) and cytochrome P450 (P450) probe substrates and their phase I metabolites in human plasma was developed. The OATP1B1 (pitavastatin) and five P450 probe substrates, caffeine (CYP1A2), losartan (CYP2C9), omeprazole (CYP2C19), dextromethorphan (CYP2D6), and midazolam (CYP3A) and their metabolites were extracted from human plasma (50 µL) using methanol. Analytes were separated on a C18 column followed by selected reaction monitoring detection using MS/MS. All analytes were separated simultaneously within a 9 min run time. The developed method was fully validated over the expected clinical concentration range for all analytes tested. The intra- and inter-day precisions for all analytes were lower than 11.3% and 8.82%, respectively, and accuracy was 88.5–117.3% and 96.1–109.2%, respectively. The lower limit of quantitation was 0.05 ng/mL for dextromethorphan, dextrorphan, midazolam, and 1′-hydroxymidazolam; 0.5 ng/mL for losartan, EXP-3174, omeprazole, 5′-hydroxyomeprazole, and pitavastatin; and 5 ng/mL for caffeine and paraxanthine. The method was successfully used in a pharmacokinetic study in healthy subjects after oral doses of five P450 and OATP1B1 probes. This analytical method provides a simple, sensitive, and accurate tool for the determination of OATP1B1 and five major P450 activities in vivo drug interaction studies.

Optimization of a drug transporter probe cocktail: potential screening tool for transporter-mediated drug-drug interactions

AIMS

Previous pharmacokinetic characterization of a transporter probe cocktail containing digoxin (P-gp), furosemide (OAT1, OAT3), metformin (OCT2, MATE1, MATE2-K) and rosuvastatin (OATP1B1, OATP1B3, BCRP) in healthy subjects showed increases in rosuvastatin systemic exposure compared to rosuvastatin alone. In this trial, the doses of metformin and furosemide as putative perpetrators were reduced to eliminate their drug-drug interaction (DDI) with rosuvastatin.

METHODS

In a randomized, open-label, single-centre, five-treatment, five-period crossover trial, 30 healthy male subjects received as reference treatments separately 0.25 mg digoxin, 1 mg furosemide, 10 mg metformin and 10 mg rosuvastatin, and as test treatment all four drugs administered together as a cocktail. Primary pharmacokinetic endpoints were AUC_0-tz (area under the plasma concentration-time curve from time zero to the last quantifiable concentration) and C_max (maximum plasma concentration) of each probe drug.

RESULTS

Geometric mean ratios and 90% confidence intervals of test (cocktail) to reference (single drug) for AUC_0-tz were 96.4% (88.2-105.3%) for digoxin, 102.6% (93.8-112.3%) for furosemide, 97.5% (93.5-101.6%) for metformin and 105.0% (96.4-114.4%) for rosuvastatin, indicating lack of interaction. The same analysis for C_max and for pharmacokinetic parameters of urinary excretion of all cocktail components also indicated no DDI.

CONCLUSIONS

Digoxin (0.25 mg), furosemide (1 mg), metformin (10 mg) and rosuvastatin (10 mg) exhibit no mutual pharmacokinetic interactions and are well tolerated administered as a cocktail. The cocktail is thus optimized and has the potential to be used as a screening tool for clinical investigation of transporter-mediated DDI.

Simultaneous Assessment of Transporter-Mediated Drug-Drug Interactions Using a Probe Drug Cocktail in Cynomolgus Monkey

We aim to establish an in vivo preclinical model to enable simultaneous assessment of inhibition potential of an investigational drug on clinically relevant drug transporters, organic anion-transporting polypeptide (OATP)1B, breast cancer resistance protein (BCRP), P-glycoprotein (P-gp), and organic anion transporter (OAT)3. Pharmacokinetics of substrate cocktail consisting of pitavastatin (OATP1B substrate), rosuvastatin (OATP1B/BCRP/OAT3), sulfasalazine (BCRP), and talinolol (P-gp) were obtained in cynomolgus monkey-alone or in combination with transporter inhibitors. Single-dose rifampicin (30 mg/kg) significantly (P < 0.01) increased the plasma exposure of all four drugs, with a marked effect on pitavastatin and rosuvastatin [area under the plasma concentration-time curve (AUC) ratio ∼21-39]. Elacridar, BCRP/P-gp inhibitor, increased the AUC of sulfasalazine, talinolol, as well as rosuvastatin and pitavastatin. An OAT1/3 inhibitor (probenecid) significantly (P < 0.05) impacted the renal clearance of rosuvastatin (∼8-fold). In vitro, rifampicin (10 µM) inhibited uptake of pitavastatin, rosuvastatin, and sulfasalazine by monkey and human primary hepatocytes. Transport studies using membrane vesicles suggested that all probe substrates, except talinolol, are transported by cynoBCRP, whereas talinolol is a cynoP-gp substrate. Elacridar and rifampicin inhibited both cynoBCRP and cynoP-gp in vitro, indicating potential for in vivo intestinal efflux inhibition. In conclusion, a probe substrate cocktail was validated to simultaneously evaluate perpetrator impact on multiple clinically relevant transporters using the cynomolgus monkey. The results support the use of the cynomolgus monkey as a model that could enable drug-drug interaction risk assessment, before advancing a new molecular entity into clinical development, as well as providing mechanistic insights on transporter-mediated interactions.

Clinical Drug-Drug Interaction Potential of BFE1224, Prodrug of Antifungal Ravuconazole, Using Two Types of Cocktails in Healthy Subjects

BFE1224, prodrug of ravuconazole, is a novel, once-daily, oral, triazole antifungal drug, and currently in development for the treatment of onychomycosis. The clinical drug-drug interaction (DDI) potential of BFE1224 with cytochrome P450 (CYP) and transporter was assessed by using two types of cocktails in healthy subjects in separate clinical studies. The CYP and transporter cocktails consisted of caffeine/tolbutamide/omeprazole/dextromethorphan/midazolam used in study 1 and digoxin/rosuvastatin used in study 2. In addition, repaglinide was separately administered to the same subjects in study 2. There were no major effects on the pharmacokinetics of CYP and transporter substrates, except for an approximate threefold increase in midazolam exposure after oral administration of BFE1224. The clinical DDIs of BFE1224 were mild for CYP3A and minor for other major CYPs (CYP1A2/2C8/2C9/2C19/2D6) as well as those of P-glycoprotein (P-gp), breast cancer resistance protein (BCRP), organic anion transporting polypeptide (OATP) 1B1, and OATP1B3.

Regulation of Organic Anion Transporting Polypeptides (OATP) 1B1- and OATP1B3-Mediated Transport: An Updated Review in the Context of OATP-Mediated Drug-Drug Interactions

Organic anion transporting polypeptides (OATP) 1B1 and OATP1B3 are important hepatic transporters that mediate the uptake of many clinically important drugs, including statins from the blood into the liver. Reduced transport function of OATP1B1 and OATP1B3 can lead to clinically relevant drug-drug interactions (DDIs). Considering the importance of OATP1B1 and OATP1B3 in hepatic drug disposition, substantial efforts have been given on evaluating OATP1B1/1B3-mediated DDIs in order to avoid unwanted adverse effects of drugs that are OATP substrates due to their altered pharmacokinetics. Growing evidences suggest that the transport function of OATP1B1 and OATP1B3 can be regulated at various levels such as genetic variation, transcriptional and post-translational regulation. The present review summarizes the up to date information on the regulation of OATP1B1 and OATP1B3 transport function at different levels with a focus on potential impact on OATP-mediated DDIs.