Mechanistic in vitro studies confirm that inhibition of the renal apical efflux transporter multidrug and toxin extrusion (MATE) 1, and not altered absorption, underlies the increased metformin exposure observed in clinical interactions with cimetidine, trimethoprim or pyrimethamine

Novel method of measurement of in vitro drug uptake in OATP1B3 overexpressing cells in the presence of dextran

BACKGROUND

In predictions about hepatic clearance (CLH), a number of studies explored the role of albumin and transporters in drug uptake by liver cells, challenging the traditional free-drug theory. It was proposed that liver uptake can occur for transporter substrate compounds not only from the drug's unbound form but also directly from the drug-albumin complex, a phenomenon known as uptake facilitated by albumin. In contrast to albumin, dextran does not exhibit binding properties for compounds. However, as a result of its inherent capacity for stabilization, it is widely used to mimic conditions within cells.

METHODS

The uptake of eight known substrates of the organic anion-transporting polypeptide 1B3 (OATP1B3) was assessed using a human embryonic kidney cell line (HEK293), which stably overexpresses this transporter. An inert polymer, dextran, was used to simulate cellular conditions, and the results were compared with experiments involving human plasma and human serum albumin (HSA).

RESULTS

This study is the first to demonstrate that dextran increases compound uptake in cells with overexpression of the OATP1B3 transporter. Contrary to the common theory that highly protein-bound ligands interact with hepatocytes to increase drug uptake, the results indicate that dextran's interaction with test compounds does not significantly increase concentrations near the cell membrane surface.

CONCLUSIONS

We evaluated the effect of dextran on the uptake of known substrates using OATP1B3 overexpressed in the HEK293 cell line, and we suggest that its impact on drug concentrations in liver cells may differ from the traditional role of plasma proteins and albumin.

Quantitative prediction of transporter-mediated drug-drug interactions using the mechanistic static pharmacokinetic (MSPK) model

Guidance/guidelines on drug-drug interactions (DDIs) have been issued in Japan, the United States, and Europe. These guidance/guidelines provide decision trees for conducting metabolizing enzyme-mediated clinical DDI studies; however, the decision trees for transporter-mediated DDIs lack quantitative prediction methods. In this study, the accuracy of a net-effect mechanistic static pharmacokinetics (MSPK) model containing the fraction transported (ft) of transporters was examined to predict transporter-mediated DDIs. This study collected information on 25 oral drugs with new active reagents that were used in clinical DDI studies as perpetrators (42 cases) from drugs approved in Japan between April 2016 and June 2020. The AUCRs (AUC ratios with and without perpetrators) of victim drugs were predicted using the net-effect MSPK model. As a result, 83 and 95% of the predicted AUCRs were within 1.5- and 2-fold error in the observed AUCRs, respectively. In cases where the victims were statins in which pharmacokinetics several transporters are involved, 70 and 91% of the predicted AUCRs were within 1.5- and 2-fold errors, respectively. Therefore, the net-effect MSPK model was applicable for predicting the AUCRs of victims, which are substrates for multiple transporters.

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.

Imeglimin: A Clinical Pharmacology Review

Imeglimin (PXL008, EMD-387008, Twymeeg®) is a first-in-class novel oral hypoglycemic agent, launched in Japan, for the treatment of type 2 diabetes mellitus. Its mechanism of action targets mitochondrial bioenergetics to ameliorate insulin resistance and to enhance β-cell function. This review summarizes the properties underlying the pharmacokinetic profile of imeglimin, a small cationic drug belonging to the tetrahydrotriazine chemical class, with a complex mechanism of absorption involving an active transport through organic cation transporters (OCTs). Imeglimin absorption decreases when dose increases due to the saturation of the active uptake transport. Post absorption, imeglimin is rapidly and primarily distributed to organs and tissues, and has a half-life ranging from 9.03 to 20.2 h. Plasma protein binding of imeglimin is low, which explains the rapid distribution to the organs observed in all species. Imeglimin is excreted unchanged in urine, indicating a low extent of metabolism. Imeglimin is a substrate of multidrug and toxic compound extrusion (MATE) 2-K and a substrate and inhibitor of OCT1, OCT2, and MATE1. Clinical drug-drug interaction studies confirmed the absence of relevant clinical interaction with substrates or inhibitors of these transporters. Overall, the drug-drug interaction potential of imeglimin is low. Its pharmacokinetics profile has also been characterized in special populations, showing no influence of mild and moderate hepatic impairment but an impact of renal function on imeglimin renal clearance. Dosage adjustment is thus required in moderately and severely renally impaired patients. Imeglimin pharmacokinetics was shown to be insensitive to ethnicity and food intake and to have no effect on QTcF interval.

Strong inhibition of organic cation transporter 2 by flavonoids and attenuation effects on cisplatin-induced cytotoxicity

Organic cation transporter 2 (OCT2) is predominantly expressed in the basolateral membrane of renal proximal tubule cells and contributes to the renal excretion of various drugs such as metformin, cisplatin, oxaliplatin, cimetidine, and lamivudine. Cisplatin, an anticancer agent for various cancers, is a substrate of OCT2, and cisplatin-induced nephrotoxicity is in part attributed to OCT2 activity in the kidney, which increases the renal accumulation of cisplatin. In this study, we aimed to identify flavone derivatives with strong inhibitory effects on OCT2 transport. Among the 80 flavonoids tested, 24 showed moderate to strong inhibitory effects against OCT2 transport activity. The IC₅₀ values were less than 5 μM for 10 flavonoids. All 10 compounds alleviated cisplatin-induced cytotoxicity in cells expressing OCT2, even though the magnitude of the effects varied depending on the functional moieties in each position. Multiple factor analysis revealed that the methyl group at the R₁ position and methoxy group at the R₆ position of the flavonol backbone are important for OCT2 inhibition. Information on the functional moieties in the flavonol backbone would help develop effective OCT2 inhibitors by providing a structural association with OCT2 inhibitory effects. In addition, the compounds with strong inhibitory effects on OCT2 identified in this study may be potential candidates for clinical use to mitigate cisplatin-induced nephrotoxicity.

Transporter-mediated Natural Product-Drug Interactions

The increasing use of natural products in clinical practice has raised great concerns about the potential natural product-drug interactions (NDIs). Drug transporters mediate the transmembrane passage of a broad range of drugs, and thus are important determinants for drug pharmacokinetics and pharmacodynamics. Generally, transporters can be divided into ATP binding cassette (ABC) family and solute carrier (SLC) family. Numerous natural products have been identified as inhibitors, substrates, inducers, and/or activators of drug transporters. This review article aims to provide a comprehensive summary of the recent progress on the research of NDIs, focusing on the main drug transporters, such as P-glycoprotein (P-gp), breast cancer resistance protein (BCRP), organic anion transporter 1 and 3 (OAT1/OAT3), organic anion-transporting polypeptide 1B1 and 1B3 (OATP1B1/OATP1B3), organic cation transporter 2 (OCT2), multidrug and toxin extrusion protein 1 and 2-K (MATE1/MATE2-K). Additionally, the challenges and strategies of studying NDIs are also discussed.

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.

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

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

Amiloride is a suitable fluorescent substrate for the study of the drug transporter human multidrug and toxin extrusion 1 (MATE1)

Human multidrug and toxin extrusion 1 (MATE1; SLC47A1) is highly expressed in the kidneys and the liver. It plays a significant role in drug and endogenous compound disposition, and therefore, a rapid evaluation of its inhibition is important for drug development and for the understanding of renal and hepatic physiology. Amiloride is a potassium-sparing diuretic used for treating hypertension; it also demonstrates strong fluorescence in organic solvent or detergent solutions. In this study, we investigated the transport characteristics of amiloride by human MATE1. Cellular accumulation of amiloride was evaluated in control vector- or MATE1-transfected HEK293 cells. Cells were lysed with 1% sodium dodecyl sulfate, and fluorescence was measured using a microplate reader at wavelengths of 364_ex and 409_em. With ammonium prepulse-induced intracellular acidification, MATE1 transported amiloride at an extracellular pH of 7.4. The uptake demonstrated an overshoot phenomenon and saturated, with the K_m and V_max being 23.5 μM and 1.01 nmol/mg/min, respectively. MATE1-mediated amiloride transport also presented with a bell-shaped pH profile that reached a maximum pH value of 7.4. The inhibitor sensitivity of MATE1-facilitated amiloride transport was similar to those of known substrates, such as tetraethylammonium and metformin. Among the tested inhibitors, pyrimethamine demonstrated the most potent inhibition with an IC₅₀ value of 0.266 μM. Furthermore, MATE1 was found to be inhibited by fampridine, which was previously considered to be a non-inhibitor of MATE1. This study demonstrates that amiloride is a suitable fluorescent substrate for the in vitro study of the transport activity of MATE1.

Hfq Regulates Efflux Pump Expression and Purine Metabolic Pathway to Increase Trimethoprim Resistance in Aeromonas veronii

Aeromonas veronii (A. veronii) is a zoonotic pathogen. It causes clinically a variety of diseases such as dysentery, bacteremia, and meningitis, and brings huge losses to aquaculture. A. veronii has been documented as a multiple antibiotic resistant bacterium. Hfq (host factor for RNA bacteriophage Qβ replication) participates in the regulations of the virulence, adhesion, and nitrogen fixation, effecting on the growth, metabolism synthesis and stress resistance in bacteria. The deletion of hfq gene in A. veronii showed more sensitivity to trimethoprim, accompanying by the upregulations of purine metabolic genes and downregulations of efflux pump genes by transcriptomic data analysis. Coherently, the complementation of efflux pump-related genes acrA and acrB recovered the trimethoprim resistance in Δhfq. Besides, the accumulations of adenosine and guanosine were increased in Δhfq in metabonomic data. The strain Δhfq conferred more sensitive to trimethoprim after appending 1 mM guanosine to M9 medium, while wild type was not altered. These results demonstrated that Hfq mediated trimethoprim resistance by elevating efflux pump expression and degrading adenosine, and guanosine metabolites. Collectively, Hfq is a potential target to tackle trimethoprim resistance in A. veronii infection.

Substrate-Dependent Trans-Stimulation of Organic Cation Transporter 2 Activity

The search of substrates for solute carriers (SLCs) constitutes a major issue, owing notably to the role played by some SLCs, such as the renal electrogenic organic cation transporter (OCT) 2 (SLC22A2), in pharmacokinetics, drug-drug interactions and drug toxicity. For this purpose, substrates have been proposed to be identified by their cis-inhibition and trans-stimulation properties towards transporter activity. To get insights on the sensitivity of this approach for identifying SLC substrates, 15 various exogenous and endogenous OCT2 substrates were analysed in the present study, using 4-(4-(dimethylamino)styryl)-N-methylpyridinium iodide (DiASP) as a fluorescent OCT2 tracer substrate. All OCT2 substrates cis-inhibited DiASP uptake in OCT2-overexpressing HEK293 cells, with IC₅₀ values ranging from 0.24 µM (for ipratropium) to 2.39 mM (for dopamine). By contrast, only 4/15 substrates, i.e., acetylcholine, agmatine, choline and metformin, trans-stimulated DiASP uptake, with a full suppression of the trans-stimulating effect of metformin by the reference OCT2 inhibitor amitriptyline. An analysis of molecular descriptors next indicated that trans-stimulating OCT2 substrates exhibit lower molecular weight, volume, polarizability and lipophilicity than non-trans-stimulating counterparts. Overall, these data indicated a rather low sensitivity (26.7%) of the trans-stimulation assay for identifying OCT2 substrates, and caution with respect to the use of such assay may therefore be considered.

Classification of drugs for evaluating drug interaction in drug development and clinical management

During new drug development, clinical drug interaction studies are carried out in accordance with the mechanism of potential drug interactions evaluated by in vitro studies. The obtained information should be provided efficiently to medical experts through package inserts and various information materials after the drug's launch. A recently updated Japanese guideline presents general procedures that are considered scientifically valid at the present moment. In this review, we aim to highlight the viewpoints of the Japanese guideline and enumerate drugs that were involved or are anticipated to be involved in evident pharmacokinetic drug interactions and classify them by their clearance pathway and potential intensity based on systematic reviews of the literature. The classification would be informative for designing clinical studies during the development stage, and the appropriate management of drug interactions in clinical practice.

Rutaecarpine enhances the anti-diabetic activity and hepatic distribution of metformin via up-regulation of Oct1 in diabetic rats

Diabetes mellitus is a chronic metabolic disorder with multiple complications, patients who receive metformin may have a simultaneous intake of herbal medicine containing rutaecarpine due to cardiovascular protection and hypolipidemic effects of rutaecarpine. There might be drug interactions between metformin and rutaecarpine. This study aimed to investigate the effects of rutaecarpine on the pharmacodynamics and pharmacokinetics of metformin in diabetic rats.The diabetic rat model was induced with high-fat diet and low dose streptozotocin. Metformin with or without rutaecarpine was administered by oral gavage for 42 days. Pharmacodynamics and pharmacokinetics parameters were evaluated.The pharmacodynamics results revealed that co-administration of rutaecarpine with metformin resulted in a remarkable reduction of serum glucose and lipid profiles in diabetic rats compared to metformin treated alone. The pharmacokinetics results showed that co-treatments of rutaecarpine with metformin did not affect the systemic exposure and renal distribution of metformin, but increased metformin concentration in liver. Furthermore, rutaecarpine increased Oct1-mediated metformin uptake into hepatocytes by upregulation of Oct1 expression in the liver.The above data indicate that rutaecarpine enhanced the anti-diabetic effect of metformin, which may be associated with the increased hepatic distribution of metformin through up-regulation of Oct1 in response to rutaecarpine.

A Whole-Body Physiologically Based Pharmacokinetic Model Characterizing Interplay of OCTs and MATEs in Intestine, Liver and Kidney to Predict Drug-Drug Interactions of Metformin with Perpetrators

Transmembrane transport of metformin is highly controlled by transporters including organic cation transporters (OCTs), plasma membrane monoamine transporter (PMAT), and multidrug/toxin extrusions (MATEs). Hepatic OCT1, intestinal OCT3, renal OCT2 on tubule basolateral membrane, and MATE1/2-K on tubule apical membrane coordinately work to control metformin disposition. Drug–drug interactions (DDIs) of metformin occur when co-administrated with perpetrators via inhibiting OCTs or MATEs. We aimed to develop a whole-body physiologically based pharmacokinetic (PBPK) model characterizing interplay of OCTs and MATEs in the intestine, liver, and kidney to predict metformin DDIs with cimetidine, pyrimethamine, trimethoprim, ondansetron, rabeprazole, and verapamil. Simulations showed that co-administration of perpetrators increased plasma exposures to metformin, which were consistent with clinic observations. Sensitivity analysis demonstrated that contributions of the tested factors to metformin DDI with cimetidine are gastrointestinal transit rate > inhibition of renal OCT2 ≈ inhibition of renal MATEs > inhibition of intestinal OCT3 > intestinal pH > inhibition of hepatic OCT1. Individual contributions of transporters to metformin disposition are renal OCT2 ≈ renal MATEs > intestinal OCT3 > hepatic OCT1 > intestinal PMAT. In conclusion, DDIs of metformin with perpetrators are attributed to integrated effects of inhibitions of these transporters.

Organic Cation Transporter 1 an Intestinal Uptake Transporter: Fact or Fiction?

Intestinal transporter proteins are known to affect the pharmacokinetics and in turn the efficacy and safety of many orally administered drugs in a clinically relevant manner. This knowledge is especially well-established for intestinal ATP-binding cassette transporters such as P-gp and BCRP. In contrast to this, information about intestinal uptake carriers is much more limited although many hydrophilic or ionic drugs are not expected to undergo passive diffusion but probably require specific uptake transporters. A transporter which is controversially discussed with respect to its expression, localization and function in the human intestine is the organic cation transporter 1 (OCT1). This review article provides an up-to-date summary on the available data from expression analysis as well as functional studies in vitro, animal findings and clinical observations. The current evidence suggests that OCT1 is expressed in the human intestine in small amounts (on gene and protein levels), while its cellular localization in the apical or basolateral membrane of the enterocytes remains to be finally defined, but functional data point to a secretory function of the transporter at the basolateral membrane. Thus, OCT1 should not be considered as a classical uptake transporter in the intestine but rather as an intestinal elimination pathway for cationic compounds from the systemic circulation.

Pharmacokinetic Drug-drug Interaction of Antibiotics Used in Sepsis Care in China

BACKGROUND

Many antibiotics have a high potential for interactions with drugs, as a perpetrator and/or victim, in critically ill patients, and particularly in sepsis patients.

METHODS

The aim of this review is to summarize the pharmacokinetic drug-drug interaction (DDI) of 45 antibiotics commonly used in sepsis care in China. Literature search was conducted to obtain human pharmacokinetics/ dispositions of the antibiotics, their interactions with drug-metabolizing enzymes or transporters, and their associated clinical drug interactions. Potential DDI is indicated by a DDI index ≥ 0.1 for inhibition or a treatedcell/ untreated-cell ratio of enzyme activity being ≥ 2 for induction.

RESULTS

The literature-mined information on human pharmacokinetics of the identified antibiotics and their potential drug interactions is summarized.

CONCLUSION

Antibiotic-perpetrated drug interactions, involving P450 enzyme inhibition, have been reported for four lipophilic antibacterials (ciprofloxacin, erythromycin, trimethoprim, and trimethoprim-sulfamethoxazole) and three antifungals (fluconazole, itraconazole, and voriconazole). In addition, seven hydrophilic antibacterials (ceftriaxone, cefamandole, piperacillin, penicillin G, amikacin, metronidazole, and linezolid) inhibit drug transporters in vitro. Despite no clinical PK drug interactions with the transporters, caution is advised in the use of these antibacterials. Eight hydrophilic antibiotics (all β-lactams; meropenem, cefotaxime, cefazolin, piperacillin, ticarcillin, penicillin G, ampicillin, and flucloxacillin), are potential victims of drug interactions due to transporter inhibition. Rifampin is reported to perpetrate drug interactions by inducing CYP3A or inhibiting OATP1B; it is also reported to be a victim of drug interactions, due to the dual inhibition of CYP3A4 and OATP1B by indinavir. In addition, three antifungals (caspofungin, itraconazole, and voriconazole) are reported to be victims of drug interactions because of P450 enzyme induction. Reports for other antibiotics acting as victims in drug interactions are scarce.

A Physiologically-Based Pharmacokinetic Model of Trimethoprim for MATE1, OCT1, OCT2, and CYP2C8 Drug-Drug-Gene Interaction Predictions

Trimethoprim is a frequently-prescribed antibiotic and therefore likely to be co-administered with other medications, but it is also a potent inhibitor of multidrug and toxin extrusion protein (MATE) and a weak inhibitor of cytochrome P450 (CYP) 2C8. The aim of this work was to develop a physiologically-based pharmacokinetic (PBPK) model of trimethoprim to investigate and predict its drug–drug interactions (DDIs). The model was developed in PK-Sim^®, using a large number of clinical studies (66 plasma concentration–time profiles with 36 corresponding fractions excreted in urine) to describe the trimethoprim pharmacokinetics over the entire published dosing range (40 to 960 mg). The key features of the model include intestinal efflux via P-glycoprotein (P-gp), metabolism by CYP3A4, an unspecific hepatic clearance process, and a renal clearance consisting of glomerular filtration and tubular secretion. The DDI performance of this new model was demonstrated by prediction of DDIs and drug–drug–gene interactions (DDGIs) of trimethoprim with metformin, repaglinide, pioglitazone, and rifampicin, with all predicted DDI and DDGI AUC_last and C_max ratios within 1.5-fold of the clinically-observed values. The model will be freely available in the Open Systems Pharmacology model repository, to support DDI studies during drug development.

Lack of Drug-Drug Interaction Between Cimetidine, a Renal Transporter Inhibitor, and Imeglimin, a Novel Oral Antidiabetic Drug, in Healthy Volunteers

BACKGROUND AND OBJECTIVE: Imeglimin is a novel oral antidiabetic drug to treat type 2 diabetes, targeting the mitochondrial bioenergetics. In vitro, imeglimin was shown to be a substrate of human multidrug and toxic extrusion transporters MATE1 and MATE2-K and organic cation transporters OCT1 and OCT2. The objective of the study was to assess the potential drug-drug interaction between imeglimin and cimetidine, a reference inhibitor of these transporters.

METHODS

A phase 1 study was carried out in 16 subjects who received a single dose of 1500 mg imeglimin alone on day 1 followed by a 6-day treatment (day 5 to day 10) with cimetidine 400 mg twice daily. On day 8, a single dose of imeglimin was co-administered with cimetidine. Blood and urine samples were collected up to 72 h after each imeglimin administration. Pharmacokinetic parameters were determined using non-compartmental methods.

RESULTS

Imeglimin maximum plasma concentration (C_max) and area under the plasma concentration-time curve (AUC) were 1.3-fold [90% CI (1.12-1.62) and (1.10-1.46) for C_max and AUC_0-last, respectively] higher when imeglimin was co-administered with cimetidine but this increase was not considered clinically relevant. This increase could be mainly explained by a reduction in renal elimination, mediated through the cimetidine inhibition of renal MATE1 transporter. Imeglimin taken alone or with cimetidine was safe and well tolerated in all subjects.

CONCLUSIONS

No clinically significant drug-drug interaction exists between imeglimin and cimetidine, a reference inhibitor of MATE1, MATE2-K, OCT1 and OCT2 transporters.

CLINICAL TRIAL REGISTRATION

EudraCT 2018-001103-36.

Metformin Transport in Native MDCK-Wt and MDCK-II Monolayers Unveils Functional Inter-Strains Differences Influencing Drug Permeability

PURPOSE

MDCK cells are commonly used to assess drug permeability, but the existence of various strains merits a comparative functional study. Since metformin absorption is largely mediated by transporters and paracellular diffusion, we used it to functionally compare MDCK-wt and MDCK-II.

METHODS

Uptake, bidirectional transport and efflux experiments were performed using different buffers, pH, and a panel of transporter inhibitors. Relative contributions to total transport in both strains were estimated.

RESULTS

Metformin uptake into MDCK-wt was linear but saturable in MDCK-II. Uptake into MDCK-wt or -II was promoted at pH 5.4 or 8.4, respectively. Quinidine and cimetidine similarly inhibited uptake in both strains. Lopinavir (PMAT specific) at pH 5.4 or pyrimethamine (MATE specific) at pH 8.4 differentially inhibited MDCK-wt or -II, respectively. Transport at pH 7.4 was absorptive regardless of strains, but secretory (MDCK-II) or absorptive (MDCK-wt) at pH 5.4. Efflux was largely basolateral in both strains. While paracellular permeability was similar between strains, total transport was dominated by transporters in MDCK-II or paracellular diffusion in MDCK-wt.

CONCLUSIONS

Metformin transport revealed functional differences between MDCK strains. Apical uptake was governed by MATE in MDCK-II or PMAT in MDCK-wt, such that metformin transport was either secretory or absorptive, respectively.

Transporter-Mediated Drug-Drug Interactions and Their Significance

Drug transporters are considered to be determinants of drug disposition and effects/toxicities by affecting the absorption, distribution, and excretion of drugs. Drug transporters are generally divided into solute carrier (SLC) family and ATP binding cassette (ABC) family. Widely studied ABC family transporters include P-glycoprotein (P-GP), breast cancer resistance protein (BCRP), and multidrug resistance proteins (MRPs). SLC family transporters related to drug transport mainly include organic anion-transporting polypeptides (OATPs), organic anion transporters (OATs), organic cation transporters (OCTs), organic cation/carnitine transporters (OCTNs), peptide transporters (PEPTs), and multidrug/toxin extrusions (MATEs). These transporters are often expressed in tissues related to drug disposition, such as the small intestine, liver, and kidney, implicating intestinal absorption of drugs, uptake of drugs into hepatocytes, and renal/bile excretion of drugs. Most of therapeutic drugs are their substrates or inhibitors. When they are comedicated, serious drug-drug interactions (DDIs) may occur due to alterations in intestinal absorption, hepatic uptake, or renal/bile secretion of drugs, leading to enhancement of their activities or toxicities or therapeutic failure. This chapter will illustrate transporter-mediated DDIs (including food drug interaction) in human and their clinical significances.

Elucidation of N 1-methyladenosine as a Potential Surrogate Biomarker for Drug Interaction Studies Involving Renal Organic Cation Transporters

Endogenous substrates are emerging biomarkers for drug transporters, which serve as surrogate probes in drug-drug interaction (DDI) studies. In this study, the results of metabolome analysis using wild-type and Oct1/2 double knockout mice suggested that N ¹-methyladenosine (m¹A) was a novel organic cation transporter (OCT) 2 substrate. An in vitro transport study revealed that m¹A is a substrate of mouse Oct1, Oct2, Mate1, human OCT1, OCT2, and multidrug and toxin exclusion protein (MATE) 2-K, but not human MATE1. Urinary excretion accounted for 77% of the systemic elimination of m¹A in mice. The renal clearance (46.9 ± 4.9 ml/min per kilogram) of exogenously given m¹A was decreased to near the glomerular filtration rates by Oct1/2 double knockout or Mate1 inhibition by pyrimethamine (16.6 ± 2.6 and 24.3 ± 0.6 ml/min per kilogram, respectively), accompanied by significantly higher plasma concentrations. In vivo inhibition of OCT2/MATE2-K by a single dose of 7-[(3R)-3-(1-aminocyclopropyl)pyrrolidin-1-yl]-1-[(1R,2S)-2-fluorocyclopropyl]-8-methoxy-4-oxoquinoline-3-carboxylic acid in cynomolgus monkeys resulted in the elevation of the area under the curve of m¹A (1.72-fold) as well as metformin (2.18-fold). The plasma m¹A concentration profile showed low diurnal and interindividual variation in healthy volunteers. The renal clearance of m¹A in younger (21-45 year old) and older (65-79 year old) volunteers (244 ± 58 and 169 ± 22 ml/min per kilogram, respectively) was about 2-fold higher than the creatinine clearance. The renal clearances of m¹A and creatinine were 31% and 17% smaller in older than in younger volunteers. Thus, m¹A could be a surrogate probe for the evaluation of DDIs involving OCT2/MATE2-K. SIGNIFICANCE STATEMENT: Endogenous substrates can serve as surrogate probes for clinical drug-drug interaction studies involving drug transporters or enzymes. In this study, m¹A was found to be a novel substrate of renal cationic drug transporters OCT2 and MATE2-K. N ¹-methyladenosine was revealed to have some advantages compared to other OCT2/MATE substrates (creatinine and N ¹-methylnicotinamide). The genetic or chemical impairment of OCT2 or MATE2-K caused a significant increase in the plasma m¹A concentration in mice and cynomolgus monkeys due to the high contribution of tubular secretion to the net elimination of m¹A. The plasma m¹A concentration profile showed low diurnal and interindividual variation in healthy volunteers. Thus, m¹A could be a better biomarker of variations in OCT2/MATE2-K activity caused by inhibitory drugs.

Physiologically-Based Pharmacokinetic Modeling Analysis for Quantitative Prediction of Renal Transporter-Mediated Interactions Between Metformin and Cimetidine

Metformin is an important antidiabetic drug and often used as a probe for drug–drug interactions (DDIs) mediated by renal transporters. Despite evidence supporting the inhibition of multidrug and toxin extrusion proteins as the likely DDI mechanism, the previously reported physiologically‐based pharmacokinetic (PBPK) model required the substantial lowering of the inhibition constant values of cimetidine for multidrug and toxin extrusion proteins from those obtained in vitro to capture the clinical DDI data between metformin and cimetidine.¹ We constructed new PBPK models in which the transporter‐mediated uptake of metformin is driven by a constant membrane potential. Our models successfully captured the clinical DDI data using in vitro inhibition constant values and supported the inhibition of multidrug and toxin extrusion proteins by cimetidine as the DDI mechanism upon sensitivity analysis and data fitting. Our refined PBPK models may facilitate prediction approaches for DDI involving metformin using in vitro inhibition constant values.

Nephrotoxicity: Role and significance of renal biomarkers in the early detection of acute renal injury

Nephrotoxicity is defining as rapid deterioration in the kidney function due to toxic effect of medications and chemicals. There are various forms, and some drugs may affect renal function in more than one way. Nephrotoxins are substances displaying nephrotoxicity. Different mechanisms lead to nephrotoxicity, including renal tubular toxicity, inflammation, glomerular damage, crystal nephropathy, and thrombotic microangiopathy. The traditional markers of nephrotoxicity and renal dysfunction are blood urea and serum creatinine which are regarded as low sensitive in the detection of early renal damage. Thus, the detection of the initial renal injures required new biomarkers which are more sensitive and highly specific that gives an insight into the site of underlying renal damage. Kidney injury molecule-1, Cystatin C, and neutrophil gelatinase-associated lipocalin sera levels are more sensitive than blood urea and serum creatinine in the detection of acute kidney injury during nephrotoxicity.

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.

Importance of OCT2 and MATE1 for the Cimetidine-Metformin Interaction: Insights from Investigations of Polarized Transport in Single- And Double-Transfected MDCK Cells with a Focus on Perpetrator Disposition

Cimetidine decreases the renal clearance of metformin by inhibition of renal tubular cation transport, and the underlying molecular mechanisms are still not fully understood. We investigated polarized metformin transport without and with the addition of cimetidine as well as polarized cimetidine transport in double-transfected MDCK-OCT2-MATE1 cells that mimic organic cation transport processes in proximal renal tubule cells and in MDCK vector control and single-transfected MDCK-OCT2 and MDCK-MATE1 cells. At all tested concentrations (1, 10, 100 μM), the intracellular accumulation of cimetidine after administration to the basal compartment was considerably higher in MDCK-OCT2 cells compared to that in all other cells ( p < 0.001). Whereas cimetidine transcellular, basal-to-apical transport was only slightly higher in MDCK-OCT2 cells, the presence of MATE1 in the apical membrane caused a pronounced translocation of cimetidine in both single- and double-transfected cells ( p < 0.001). Transcellular, basal-to-apical metformin net transport was reduced by 89.1, 74.5, and 91.0% in MDCK-OCT2-MATE1 cells after the addition of cimetidine (100 μM) to the basal, the apical, or both compartments ( p < 0.001). In MDCK-MATE1 and MDCK-OCT2-MATE1 cells, transcellular net transport of metformin was inhibited by cimetidine with IC₅₀ values of 8.0 and 6.6 μM, respectively. Our data confirm the relevance of MATE1 and suggest the relevance of OCT2 for the cimetidine-metformin interaction, primarily because OCT2 mediates uptake of the perpetrator cimetidine into renal proximal tubular cells and thereby to the site of the metformin exporter MATE1. This work supports the notion that a thorough understanding of transporter-mediated drug-drug interactions may require investigations on the impact of transporters on cellular uptake and transcellular transport of victim as well as perpetrator drugs.

Mechanistic in vitro studies confirm that inhibition of the renal apical efflux transporter multidrug and toxin extrusion (MATE) 1, and not altered absorption, underlies the increased metformin exposure observed in clinical interactions with cimetidine, trimethoprim or pyrimethamine

Metformin is a common co‐medication for many diseases and the victim of clinical drug‐drug interactions (DDIs) perpetrated by cimetidine, trimethoprim and pyrimethamine, resulting in decreased active renal clearance due to inhibition of organic cation transport proteins and increased plasma exposure of metformin. To understand whether area under the plasma concentration–time curve (AUC) increases relate to absorption, in vitro inhibitory potencies of these drugs against metformin transport by human organic cation transporter (OCT) 1, and the apical to basolateral absorptive permeability of metformin across Caco‐2 cells in the presence of therapeutic intestinal concentrations of cimetidine, trimethoprim or pyrimethamine, were determined. Whilst all inhibited OCT1, none enhanced metformin's absorptive permeability (~0.5 × 10⁻⁶ cm/sec) suggesting that DDI AUC changes are not related to absorption. Subsequently, to understand whether inhibition of renal transporters are responsible for AUC increases, in vitro inhibitory potencies against metformin transport by human OCT2, multidrug and toxin extrusion (MATE) 1 and MATE2‐K were determined. Ensuing IC₅₀ values were incorporated into mechanistic static equations, alongside unbound maximal plasma concentration and transporter fraction excreted values, in order to calculate theoretical increases in metformin AUC due to inhibition by cimetidine, trimethoprim or pyrimethamine. Calculated theoretical fold‐increases in metformin exposure confirmed solitary inhibition of renal MATE1 to be the likely mechanism underlying the observed exposure changes in clinical DDIs. Interestingly, clinically observed increases in metformin AUC were predicted more closely when the renal transporter fraction excreted value derived from oral metformin administration, rather than intravenous, was utilized in theoretical calculations, likely reflecting the “flip‐flop” pharmacokinetic profile of the drug.