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

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

Pharmacokinetic interactions of niclosamide in rats: Involvement of organic anion transporters 1 and 3 and organic cation transporter 2

Niclosamide is an anthelmintic drug with a long history of use and is generally safe and well tolerated in humans. As the conventional dose of niclosamide results in a low but certain level in systemic circulation, drug interactions with concomitant drugs should be considered. We aimed to investigate the interaction between niclosamide and drug transporters, as such information is currently limited. Niclosamide inhibited the transport activity of OATP1B1, OATP1B3, OAT1, OAT3, and OCT2 in vitro. Among them, the inhibitory effects on OAT1, OAT3, and OCT2 were strong, with IC50 values of less than 1 μM. When 3 mg/kg of niclosamide was co-administered to rats, systemic exposure to furosemide (a substrate of OAT1/3) and metformin (a substrate of OCT2) increased, and the renal clearance (CLr) of the drugs significantly decreased. These results suggest that niclosamide inhibits renal transporters, OAT1/3 and OCT2, not only in vitro but also in vivo, resulting in increased systemic exposure to the substrates of the transporters by strongly blocking the urinary elimination pathway in rats. The findings of this study will support a meticulous understanding of the transporter-mediated drug interactions of niclosamide and consequently aid in effective and safe use of niclosamide.

Mechanistic Static Model based Prediction of Transporter Substrate Drug-Drug Interactions Utilizing Atorvastatin and Rifampicin

OBJECTIVE

An in vitro relative activity factor (RAF) technique combined with mechanistic static modeling was examined to predict drug-drug interaction (DDI) magnitude and analyze contributions of different clearance pathways in complex DDIs involving transporter substrates. Atorvastatin and rifampicin were used as a model substrate and inhibitor pair.

METHODS

In vitro studies were conducted with transfected HEK293 cells, hepatocytes and human liver microsomes. Prediction success was defined as predictions being within twofold of observations.

RESULTS

The RAF method successfully translated atorvastatin uptake from transfected cells to hepatocytes, demonstrating its ability to quantify transporter contributions to uptake. Successful translation of atorvastatin's in vivo intrinsic hepatic clearance (CLint,h,in vivo) from hepatocytes to liver was only achieved through consideration of albumin facilitated uptake or through application of empirical scaling factors to transporter-mediated clearances. Transporter protein expression differences between hepatocytes and liver did not affect CLint,h,in vivo predictions. By integrating cis and trans inhibition of OATP1B1/OATP1B3, atorvastatin-rifampicin (single dose) DDI magnitude could be accurately predicted (predictions within 0.77-1.0 fold of observations). Simulations indicated that concurrent inhibition of both OATP1B1 and OATP1B3 caused approximately 80% of atorvastatin exposure increases (AUCR) in the presence of rifampicin. Inhibiting biliary elimination, hepatic metabolism, OATP2B1, NTCP, and basolateral efflux are predicted to have minimal to no effect on AUCR.

CONCLUSIONS

This study demonstrates the effective application of a RAF-based translation method combined with mechanistic static modeling for transporter substrate DDI predictions and subsequent mechanistic interpretation.

Novel inhibitors of breast cancer resistance protein (BCRP, ABCG2) among marketed drugs

Drug-drug interactions (DDIs) are a major concern for the safe use of medications. Breast cancer resistance protein (BCRP) is a clinically relevant ATP-binding cassette (ABC) transporter for drug disposition. Inhibition of BCRP increases the plasma concentrations of BCRP substrate drugs, which potentially could lead to adverse drug reactions. The aim of the present study was to identify BCRP inhibitors amongst a library of 232 commonly used drugs and anticancer drugs approved by the United States Food and Drug Administration (FDA). BCRP inhibition studies were carried out using the vesicular transport assay. We found 75 drugs that reduced the relative transport activity of BCRP to less than 25% of the vehicle control and were categorized as strong inhibitors. The concentration required for 50% inhibition (IC₅₀) was determined for 13 strong inhibitors that were previously poorly characterized for BCRP inhibition. The IC₅₀ ranged from 1.1 to 11 µM, with vemurafenib, dabigatran etexilate and everolimus being the strongest inhibitors. According to the drug interaction guidance documents from the FDA and the European Medicines Agency (EMA), in vivo DDI studies are warranted if the theoretical intestinal luminal concentration of a drug exceeds its IC₅₀ by tenfold. Here, the IC₅₀ values for eight of the drugs were 100-fold lower than their theoretical intestinal luminal concentration. Moreover, a mechanistic static model suggested that vemurafenib, bexarotene, dabigatran etexilate, rifapentine, aprepitant, and ivacaftor could almost fully inhibit intestinal BCRP, increasing the exposure of concomitantly administered rosuvastatin over 90%. Therefore, clinical studies are warranted to investigate whether these drugs cause BCRP-mediated DDIs in humans.

Results From Drug-Drug Interaction Studies In Vitro and In Vivo Investigating the Inhibitory Effect of Finerenone on the Drug Transporters BCRP, OATP1B1, and OATP1B3

BACKGROUND AND OBJECTIVES

In vitro and in vivo studies were performed with the novel, selective, nonsteroidal mineralocorticoid receptor antagonist finerenone to assess the relevance of inhibitory effects on the transporters breast cancer resistance protein (BCRP), organic anion transporting polypeptide 1B1 (OATP1B1), and OATP1B3. These transporters are involved in the disposition of a number of drugs, including statins. Statins are also a frequent comedication in patients receiving finerenone. Therefore, inhibitory effects on BCRP and OATPs are of potential clinical relevance.

METHODS

The effect on the transport of specific substrates of BCRP and OATP1B1/1B3 was assessed in cell-based in vitro assays with finerenone or its metabolites. A fixed-sequence crossover study in 14 healthy male volunteers investigated the effects of finerenone (40 mg once daily) on the pharmacokinetics of the index substrate rosuvastatin (5 mg) administered alone, simultaneously with, or approximately 4 h before finerenone. The effect of finerenone on the endogenous OATP substrates coproporphyrin I and III was also assessed.

RESULTS

Based on in vitro findings and threshold values proposed in regulatory guidelines, finerenone appeared to be a potentially relevant inhibitor of all three transporters. Relevant inhibition could also not be ruled out for the finerenone metabolites M1a (OATP1B1) and M3a (OATP1B1 and OAT1B3), which prompted an investigation into the relevance of these findings in vivo. After administration on a background of finerenone 40 mg, all point estimates of area under the curve ratios (114.47% [rosuvastatin], 99.62% [coproporphyrin I; simultaneous], and 105.28% [rosuvastatin; 4 h separation]) and maximum concentration ratios (111.24% [rosuvastatin], 101.22% [coproporphyrin I], 89.14% [coproporphyrin III; simultaneous], and 96.84% [rosuvastatin; 4 h separation]) of the investigated substrates were within 80.0-125%. In addition, the 90% confidence intervals of the ratios were within the conventional no-effect boundaries of 80.0% and 125% for rosuvastatin after temporally separated administration, and for coproporphyrin I and III.

CONCLUSION

Administration of finerenone 40 mg once daily confers no risk of clinically relevant drug-drug interactions with substrates of BCRP, OATP1B1, or OATP1B3. The potential for relevant inhibition of these transporters suggested by in vitro findings was not confirmed in vivo.

A simple and sensitive HPLC-FL method for bioanalysis of velpatasvir, a novel hepatitis C virus NS5A inhibitor, in rat plasma: Investigation of factors determining its oral bioavailability

Velpatasvir is a novel inhibitor of hepatitis C virus nonstructural protein 5A that received US Food and Drug Administration approval for the treatment of patients with chronic hepatitis C virus genotypes 1-6. In the present study, a sensitive bioanalytical method for velpatasvir was developed using high-performance liquid chromatography coupled with a fluorescence detector system, which was applied to elucidate the factors determining the oral bioavailability and disposition of velpatasvir. This method offered sufficient sensitivity, with a lower limit of quantification of 0.5 ng/mL, which is comparable to previously reported methods using liquid chromatography coupled with tandem mass spectrometry. Velpatasvir exhibited low oral bioavailability, moderate intestinal permeability, and significant biliary excretion in rats. It was also found to be significantly metabolized in the liver, with a low-to-moderate extraction ratio; however, its intestinal metabolism and enterohepatic circulation did not occur. Thus, our present results demonstrate that the oral bioavailability of velpatasvir is primarily dependent on gut absorption and hepatic first-pass metabolism. The fractions of velpatasvir dose unabsorbed from the gut and eliminated by the liver before reaching the systemic circulation following oral administration were estimated to be 32.8%-58.6% and 4.74%-30.54% of the oral dose, respectively. To our knowledge, this is the first systematic study to investigate the contributory roles of biopharmaceutical and pharmacokinetic factors on the oral bioavailability of velpatasvir, together with a new bioanalytical method for velpatasvir.

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.

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.

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

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

Evaluation of Ipatasertib Interactions with Itraconazole and Coproporphyrin I and III in a Single Drug Interaction Study in Healthy Subjects

Ipatasertib is a pan-AKT inhibitor in development for the treatment of cancer. Ipatasertib was metabolized by CYP3A4 to its major metabolite, M1 (G-037720), and was a P-gp substrate and OATP1B1/1B3 inhibitor in vitro. A phase I drug-drug interaction (DDI) study (n = 15) was conducted in healthy subjects to evaluate the effect of itraconazole (200-mg solution QD, 4 days), a strong CYP3A4 and P-gp inhibitor, on pharmacokinetics of ipatasertib (100-mg single dose). Itraconazole increased the C_max and AUC_{0 -∞} of ipatasertib by 2.3- and 5.5-fold, respectively, increased the half-life by 53%, and delayed the t_max by 1 hour. The C_max and AUC_0-72h of its metabolite M1 (G-037720) reduced by 91% and 68%, respectively. This study confirmed that CYP3A4 plays a major role in ipatasertib clearance. Furthermore, the interaction of ipatasertib with coproporphyrin (CP) I and CPIII, the two endogenous substrates of OATP1B1/1B3, was evaluated in this study. CPI and CPIII plasma levels were unchanged in the presence of ipatasertib, both at exposures of 100 mg and at higher exposures in combination with itraconazole. This indicated no in vivo inhibition of OATP1B1/1B3 by ipatasertib. Additionally, it was shown that CPI and CPIII were not P-gp substrates in vitro, and itraconazole had no effect on CPI and CPIII concentrations in vivo. The latter is an important finding because it will simplify interpretation of future DDI studies using CPI/CPIII as OATP1B1/1B3 biomarkers. SIGNIFICANCE STATEMENT: This drug-drug interaction study in healthy volunteers demonstrated that CYP3A4 plays a major role in ipatasertib clearance, and that ipatasertib is not an organic anion transporting polypeptide 1B1/1B3 inhibitor. Furthermore, it was demonstrated that itraconazole, an inhibitor of CYP3A4 and several transporters, did not affect CPI/CPIII levels in vivo. This increases the understanding and application of these endogenous substrates as well as itraconazole in complex drug interaction studies.