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

Drug transporters in drug disposition - highlights from the year 2023

Drug transporter field is rapidly evolving with significant progress in in vitro and in vivo tools and, computational models to assess transporter-mediated drug disposition and drug-drug interactions (DDIs) in humans. On behalf of all coauthors, I am pleased to share the fourth annual review highlighting articles published and deemed influential in the field of drug transporters in the year 2023. Each coauthor independently selected peer-reviewed articles published or available online in the year 2023 and summarized them as shown previously (Chothe et al. 2021; Chothe et al. 2022, 2023) with unbiased perspectives. Based on selected articles, this review was categorized into four sections: (1) transporter structure and in vitro evaluation, (2) novel in vitro/ex vivo models, (3) endogenous biomarkers, and (4) PBPK modeling for evaluating transporter DDIs (Table 1). As the scope of this review is not to comprehensively review each article, readers are encouraged to consult original paper for specific details. Finally, I appreciate all the authors for their time and continued support in writing this review.

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.

Utilising Endogenous Biomarkers in Drug Development to Streamline the Assessment of Drug-Drug Interactions Mediated by Renal Transporters: A Pharmaceutical Industry Perspective

The renal secretion of many drugs is facilitated by membrane transporters, including organic cation transporter 2, multidrug and toxin extrusion protein 1/2-K and organic anion transporters 1 and 3. Inhibition of these transporters can reduce renal excretion of drugs and thereby pose a safety risk. Assessing the risk of inhibition of these membrane transporters by investigational drugs remains a key focus in the evaluation of drug-drug interactions (DDIs). Current methods to predict DDI risk are based on generating in vitro data followed by a clinical assessment using a recommended exogenous probe substrate for the individual drug transporter. More recently, monitoring plasma-based and urine-based endogenous biomarkers to predict transporter-mediated DDIs in early phase I studies represents a promising approach to facilitate, improve and potentially avoid conventional clinical DDI studies. This perspective reviews the evidence for use of these endogenous biomarkers in the assessment of renal transporter-mediated DDI, evaluates how endogenous biomarkers may help to expand the DDI assessment toolkit and offers some potential knowledge gaps. A conceptual framework for assessment that may complement the current paradigm of predicting the potential for renal transporter-mediated DDIs is outlined.

Membrane transporters in drug development and as determinants of precision medicine

The effect of membrane transporters on drug disposition, efficacy and safety is now well recognized. Since the initial publication from the International Transporter Consortium, significant progress has been made in understanding the roles and functions of transporters, as well as in the development of tools and models to assess and predict transporter-mediated activity, toxicity and drug-drug interactions (DDIs). Notable advances include an increased understanding of the effects of intrinsic and extrinsic factors on transporter activity, the application of physiologically based pharmacokinetic modelling in predicting transporter-mediated drug disposition, the identification of endogenous biomarkers to assess transporter-mediated DDIs and the determination of the cryogenic electron microscopy structures of SLC and ABC transporters. This article provides an overview of these key developments, highlighting unanswered questions, regulatory considerations and future directions.

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.

Development of 4-Pyridoxic Acid PBPK Model to Support Biomarker-Informed Evaluation of OAT1/3 Inhibition and Effect of Chronic Kidney Disease

Monitoring endogenous biomarkers is increasingly used to evaluate transporter-mediated drug-drug interactions (DDIs) in early drug development and may be applied to elucidate changes in transporter activity in disease. 4-pyridoxic acid (PDA) has been identified as the most sensitive plasma endogenous biomarker of renal organic anion transporters (OAT1/3). Increase in PDA baseline concentrations was observed after administration of probenecid, a strong clinical inhibitor of OAT1/3 and also in patients with chronic kidney disease (CKD). The aim of this study was to develop and verify a physiologically-based pharmacokinetic (PBPK) model of PDA, to predict the magnitude of probenecid DDI and predict the CKD-related changes in PDA baseline. The PBPK model for PDA was first developed in healthy population, building on from previous population pharmacokinetic modeling, and incorporating a mechanistic kidney model to consider OAT1/3-mediated renal secretion. Probenecid PBPK model was adapted from the Simcyp database and re-verified to capture its dose-dependent pharmacokinetics (n = 9 studies). The PBPK model successfully predicted the PDA plasma concentrations, area under the curve, and renal clearance in healthy subjects at baseline and after single/multiple probenecid doses. Prospective simulations in severe CKD predicted successfully the increase in PDA plasma concentration relative to healthy (within 2-fold of observed data) after accounting for 60% increase in fraction unbound in plasma and additional 50% decline in OAT1/3 activity beyond the decrease in glomerular filtration rate. The verified PDA PBPK model supports future robust evaluation of OAT1/3 DDI in drug development and increases our confidence in predicting exposure and renal secretion in patients with CKD.

Quantitative Consideration of Clinical Increases in Serum Creatinine Caused by Renal Transporter Inhibition

Creatinine is a common biomarker of renal function and is secreted in the renal tubular cells via drug transporters, such as organic cation transporter 2 and multidrug and toxin extrusion (MATE) 1/2-K. To differentiate between drug-induced acute kidney injury (AKI) and drug interactions through the renal transporter, it has been examined whether these transporter inhibitions quantitatively explained increases in serum creatinine (SCr) at their clinically relevant concentrations using drugs without any changes in renal function. For such renal transporter inhibitors and recently approved tyrosine kinase inhibitors (TKIs), this mini-review describes clinical increases in SCr and inhibitory potentials against the renal transporters. Most cases of SCr elevations can be explained by considering the renal transporter inhibitions based on unbound maximum plasma concentrations, except for drugs associated with obvious changes in renal function. SCr increases for cobicistat, dolutegravir, and dronedarone, and some TKIs were significantly underestimated, and these underestimations were suggested to be associated with low plasma unbound fractions. Sensitivity analysis of SCr elevations regarding inhibitory potentials of MATE1/2-K demonstrated that typical inhibitors such as cimetidine, DX-619, pyrimethamine, and trimethoprim could give false interpretations of AKI according to the criteria based on relative or absolute levels of SCr elevations. Recent progress and current challenges of physiologically-based pharmacokinetics modeling for creatinine disposition were also summarized. Although it should be noted for the potential impact of in vitro assay designs on clinical translatability of transporter inhibitions data, mechanistic approaches could support decision-making in clinical development to differentiate between AKI and creatinine-drug interactions. SIGNIFICANCE STATEMENT: Serum creatinine (SCr) is widely used as an indicator of kidney function, but it increases due to inhibitions of renal transporters, such as multidrug and toxin extrusion protein 1/2-K despite no functional changes in the kidney. Such SCr elevations were quantitatively explained by renal transporter inhibitions except for some drugs with high protein binding. The present analysis demonstrated that clinically relevant inhibitors of the renal transporters could cause SCr elevations above levels corresponding to acute kidney injury criteria.

Progress in the Quantitative Assessment of Transporter-Mediated Drug-Drug Interactions Using Endogenous Substrates in Clinical Studies

Variations in drug transporter activities, caused by genetic polymorphism and drug-drug interactions (DDIs), alter the systemic exposure of substrate drugs, leading to differences in drug responses. Recently, some endogenous substrates of drug transporters, particularly the solute carrier family transporters such as OATP1B1, OATP1B3, OAT1, OAT3, OCT1, OCT2, MATE1, and MATE2-K, have been identified to investigate variations in drug transporters in humans. Clinical data obtained support their performance as surrogate probes in terms of specificity and reproducibility. Pharmacokinetic parameters of the endogenous biomarkers depend on the genotypes of drug transporters and the systemic exposure to perpetrator drugs. Furthermore, the development of physiologically based pharmacokinetic models for the endogenous biomarkers has enabled a top-down approach to obtain insights into the effect of perpetrators on drug transporters and to more precisely simulate the DDI with victim drugs, including probe drugs. The endogenous biomarkers can address the uncertainty in the DDI prediction in the preclinical and early phases of clinical development and have the potential to fulfill regulatory requirements. Therefore, the endogenous biomarkers should be able to predict disease effects on the variations in drug transporter activities observed in patients. This mini-review focuses on recent progress in the identification and use of the endogenous drug transporter substrate biomarkers and their application in drug development. SIGNIFICANCE STATEMENT: Advances in analytical methods have enabled the identification of endogenous substrates of drug transporters. Changes in the pharmacokinetic parameters (Cmax, AUC, or CLR) of these endogenous biomarkers relative to baseline values can serve as a quantitative index to assess variations in drug transporter activities during clinical studies and thereby provide more precise DDI predictions.

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.