Organic anion transporting polypeptide (OATP) 1B1/3 mediated drug-drug interaction (DDI) potential is evaluated in vivo with rosuvastatin (RST) as a probe substrate in clinical studies. We calibrated our assay with RST and estradiol 17-β-D-glucuronide (E217βG)/ cholecystokinin-8 (CCK8) as in vitro probes for qualitative and quantitative prediction of OATP1B-mediated DDI potential for RST. In vitro OATP1B1/1B3 inhibition using E217βG and CCK8 yielded higher AUC ratio (AUCR) values numerically with the static model, but all probes performed similarly from a qualitative cutoff-based prediction, as described in regulatory guidances. However, the magnitudes of DDI were not captured satisfactorily. Considering that clearance of RST is also mediated by gut breast cancer resistance protein (BCRP), inhibition of BCRP was also incorporated in the DDI prediction if the gut inhibitor concentrations were 10 x IC50 for BCRP inhibition. This combined static model closely predicted the magnitude of RST DDI with root mean square error values of 0.767-0.812 and 1.24-1.31, with and without BCRP inhibition, respectively for in vitro-in vivo- correlation of DDI. Physiologically-based pharmacokinetic (PBPK) modeling was also used to simulate DDI between RST and rifampicin, asunaprevir, and velpatasvir. Predicted AUCR for rifampicin and asunaprevir was within 1.5-fold of that observed, whereas that for velpatasvir showed a 2-fold under-prediction. Overall, the combined static model incorporating both OATP1B and BCRP inhibition provides a quick and simple mathematical approach to quantitatively predict the magnitude of transporter-mediated DDI for RST for routine application. PBPK complemented the static model and provides a framework when a dynamic model is needed. Significance Statement Using 22 drugs, we show that a static model for OATP1B1/1B3 inhibition can qualitatively predict potential for DDI using a cut-off based approach as in regulatory guidances. However, consideration of both OATP1B1/3 and gut BCRP inhibition provided a better prediction of the magnitude of the transporter-mediated DDI of these inhibitors with rosuvastatin. Based on these results, we have proposed an empirical mechanistic-static approach for a more reliable prediction of transporter-mediated DDI liability with rosuvastatin that drug development teams can leverage.

Orally administered small molecules may have important therapeutic potential in treating COVID-19 disease. The recently developed antiviral agents, Molnupiravir and Nirmatrelvir, have been reported to be efficient treatments, with only moderate side effects, especially when applied in the early phases of this disease. However, drug–drug and drug–transporter interactions have already been noted by the drug development companies and in the application notes. In the present work, we have studied some of the key human transporters interacting with these agents. The nucleoside analog Molnupiravir (EIDD-2801) and its main metabolite (EIDD-1931) were found to inhibit CNT1,2 in addition to the ENT1,2 nucleoside transporters; however, it did not significantly influence the relevant OATP transporters or the ABCC4 nucleoside efflux transporter. The active component of Paxlovid (PF-07321332, Nirmatrelvir) inhibited the function of several OATPs and of ABCB1 but did not affect ABCG2. However, significant inhibition was observed only at high concentrations of Nirmatrelvir and probably did not occur in vivo. Paxlovid, as used in the clinic, is a combination of Nirmatrelvir (viral protease inhibitor) and Ritonavir (a “booster” inhibitor of Nirmatrelvir metabolism). Ritonavir is known to inhibit several drug transporters; therefore, we have examined these compounds together, in relevant concentrations and ratios. No additional inhibitory effect of Nirmatrelvir was observed compared to the strong transporter inhibition caused by Ritonavir. Our current in vitro results should help to estimate the potential drug–drug interactions of these newly developed agents during COVID-19 treatment.

Background/Objectives: The impact of potential precipitant drugs on plasma or urinary exposure of endogenous biomarkers is emerging as an alternative approach to evaluating drug–drug interaction (DDI) liability. N1-Methylnicotinamide (NMN) has been proposed as a potential biomarker for renal organic cation transporter 2 (OCT2). NMN is synthesized in the liver from nicotinamide by nicotinamide N-methyltransferase (NNMT) and is subsequently metabolized by aldehyde oxidase (AO). Multiple clinical studies have shown a reduction in NMN plasma concentration following the administration of OCT inhibitors such as cimetidine, trimethoprim, and pyrimethamine, which contrasts with their inhibition of NMN renal clearance by OCT2. We hypothesized that OCT1-mediated NMN release from hepatocytes is inhibited by the administration of OCT inhibitors. Methods: Re-analysis of the reported NMN pharmacokinetics with and without OCT inhibitor exposure was performed. We assessed the effect of cimetidine on NMN uptake in OCT1-HEK293 cells and evaluated the potential confounding effects of cimetidine on enzymes involved in NMN formation and metabolism. Results: A re-analysis of previous NMN pharmacokinetic DDI data suggests that NMN plasma systemic exposure decreased by 17–41% during the first 4 h following different OCT inhibitor administration except dolutegravir. Our findings indicate that NMN uptake was significantly higher (by 2.5-fold) in OCT1-HEK293 cells compared to mock cells, suggesting that NMN is a substrate of OCT1. Additionally, our results revealed that cimetidine does not inhibit NNMT and AO activity. Conclusions: Our findings emphasize the limitations of using NMN as an OCT2 biomarker and reveal potential mechanisms behind the reduction in NMN plasma levels associated with OCT inhibitors. Instead, our data suggest that NMN could be tested further as a potential biomarker for OCT1 activity.

ABCB4 is almost exclusively expressed in the liver, where it plays an essential role in bile formation by transporting phospholipids into the bile. ABCB4 polymorphisms and deficiencies in humans are associated with a wide spectrum of hepatobiliary disorders, attesting to its crucial physiological function. Inhibition of ABCB4 by drugs may lead to cholestasis and drug-induced liver injury (DILI), although compared with other drug transporters, there are only a few identified substrates and inhibitors of ABCB4. Since ABCB4 shares up to 76% identity and 86% similarity in the amino acid sequence with ABCB1, also known to have common drug substrates and inhibitors, we aimed to develop an ABCB4 expressing Abcb1-knockout MDCKII cell line for transcellular transport assays. This in vitro system allows the screening of ABCB4-specific drug substrates and inhibitors independently of ABCB1 activity. Abcb1KO-MDCKII-ABCB4 cells constitute a reproducible, conclusive, and easy to use assay to study drug interactions with digoxin as a substrate. Screening a set of drugs with different DILI outcomes proved that this assay is applicable to test ABCB4 inhibitory potency. Our results are consistent with prior findings concerning hepatotoxicity causality and provide new insights for identifying drugs as potential ABCB4 inhibitors and substrates.

Caco-2 screens are routinely used in laboratories to measure the permeability of compounds and can identify substrates of efflux transporters. In this study, we hypothesized that efflux transporter inhibition of a compound can be predicted by an intracellular metabolic signature in Caco-2 cells in the assay used to test intestinal permeability. Using selective inhibitors and transporter knock-out (KO) cells and a targeted Liquid Chromatography tandem Mass Spectrometry (LC-MS) method, we identified 11 metabolites increased in cells with depleted P-glycoprotein (Pgp) activity. Four metabolites were altered with Breast Cancer Resistance (BCRP) inhibition and nine metabolites were identified in the Multidrug Drug Resistance Protein 2 (MRP2) signature. A scoring system was created that could discriminate among the three transporters and validated with additional inhibitors. Pgp and MRP2 substrates did not score as inhibitors. In contrast, BCRP substrates and inhibitors showed a similar intracellular metabolomic signature. Network analysis of signature metabolites led us to investigate changes of enzymes in one-carbon metabolism (folate and methionine cycles). Our data shows that methylenetetrahydrofolate reductase (MTHFR) protein levels increased with Pgp inhibition and Thymidylate synthase (TS) protein levels were reduced with Pgp and MRP2 inhibition. In addition, the methionine cycle is also affected by both Pgp and MRP2 inhibition. In summary, we demonstrated that the routine Caco-2 assay has the potential to identify efflux transporter inhibitors in parallel with substrates in the assays currently used in many DMPK laboratories and that inhibition of efflux transporters has biological consequences.

Implementing the 3R initiative to reduce animal experiments in brain penetration prediction for CNS-targeting drugs requires more predictive in vitro and in silico models. However, animal studies are still indispensable to obtaining brain concentration and determining the prediction performance of in vitro models. To reveal species differences and provide reliable data for IVIVE, in vitro models are required. Systems overexpressing MDR1 and BCRP are widely used to predict BBB penetration, highlighting the impact of the in vitro system on predictive performance. In this study, endogenous Abcb1 knock-out MDCKII cells overexpressing MDR1 of human, mouse, rat or cynomolgus monkey origin were used. Good correlations between ERs of 83 drugs determined in each cell line suggest limited species specificities. All cell lines differentiated CNS-penetrating compounds based on ERs with high efficiency and sensitivity. The correlation between in vivo and predicted K_p,uu,brain was the highest using total ER of human MDR1 and BCRP and optimized scaling factors. MDR1 interactors were tested on all MDR1 orthologs using digoxin and quinidine as substrates. We found several examples of inhibition dependent on either substrate or transporter abundance. In summary, this assay system has the potential for early-stage brain penetration screening. IC₅₀ comparison between orthologs is complex; correlation with transporter abundance data is not necessarily proportional and requires the understanding of modes of transporter inhibition.