A Novel Physiologically Based Model of Creatinine Renal Disposition to Integrate Current Knowledge of Systems Parameters and Clinical Observations

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.

Development of a Highly Differentiated Human Primary Proximal Tubule MPS Model (aProximate MPS Flow)

The kidney proximal tubule (PT) mediates renal drug elimination in vivo and is a major site of drug-induced toxicity. To reliably assess drug efficacy, it is crucial to construct a model in which PT functions are replicated. Current animal studies have proven poorly predictive of human outcome. To address this, we developed a physiologically relevant micro-physiological system (MPS) model of the human PT, the aProximate MPS Flow platform (Patent No: G001336.GB). In this model, primary human PT cells (hPTCs) are subjected to fluidic media flow and a shear stress of 0.01-0.2 Pa. We observe that these cells replicate the polarity of hPTCs and exhibit a higher expression of all the key transporters of SLC22A6 (OAT1), SLC22A8 (OAT3), SLC22A2 (OCT2), SLC47A1 (MATE1), SLC22A12 (URAT1), SLC2A9 (GLUT9), ABCB1 (MDR1), ABCC2 (MRP2), LRP2 (megalin), CUBN (cubilin), compared with cells grown under static conditions. Immunofluorescence microscopy confirmed an increase in OAT1, OAT3, and cilia protein expression. Increased sensitivity to nephrotoxic protein cisplatin was observed; creatinine and FITC-albumin uptake was significantly increased under fluidic shear stress conditions. Taken together, these data suggest that growing human PT cells under media flow significantly improves the phenotype and function of hPTC monolayers and has benefits to the utility and near-physiology of the model.

Physiologically based pharmacokinetic model combined with reverse dose method to study the nephrotoxic tolerance dose of tacrolimus

Nephrotoxicity is the most common side effect that severely limits the clinical application of tacrolimus (TAC), an immunosuppressive agent used in kidney transplant patients. This study aimed to explore the tolerated dose of nephrotoxicity of TAC in individuals with different CYP3A5 genotypes and liver conditions. We established a human whole-body physiological pharmacokinetic (WB-PBPK) model and validated it using data from previous clinical studies. Following the injection of 1 mg/kg TAC into the tail veins of male rats, we developed a rat PBPK model utilizing the drug concentration-time curve obtained by LC-MS/MS. Next, we converted the established rat PBPK model into the human kidney PBPK model. To establish renal concentrations, the BMCL5 of the in vitro CCK-8 toxicity response curve (drug concentration range: 2-80 mol/L) was extrapolated. To further investigate the acceptable levels of nephrotoxicity for several distinct CYP3A5 genotypes and varied hepatic function populations, oral dosing regimens were extrapolated utilizing in vitro-in vivo extrapolation (IVIVE). The PBPK model indicated the tolerated doses of nephrotoxicity were 0.14-0.185 mg/kg (CYP3A5 expressors) and 0.13-0.155 mg/kg (CYP3A5 non-expressors) in normal healthy subjects and 0.07-0.09 mg/kg (CYP3A5 expressors) and 0.06-0.08 mg/kg (CYP3A5 non-expressors) in patients with mild hepatic insufficiency. Further, patients with moderate hepatic insufficiency tolerated doses of 0.045-0.06 mg/kg (CYP3A5 expressors) and 0.04-0.05 mg/kg (CYP3A5 non-expressors), while in patients with moderate hepatic insufficiency, doses of 0.028-0.04 mg/kg (CYP3A5 expressors) and 0.022-0.03 mg/kg (CYP3A5 non-expressors) were tolerated. Overall, our study highlights the combined usage of the PBPK model and the IVIVE approach as a valuable tool for predicting toxicity tolerated doses of a drug in a specific group.

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.

Change of metformin concentrations in the liver as a pharmacological target site of metformin after long-term combined treatment with ginseng berry extract

Metformin as an oral glucose-lowering drug is used to treat type 2 diabetic mellitus. Considering the relatively high incidence of cardiovascular complications and other metabolic diseases in diabetic mellitus patients, a combination of metformin plus herbal supplements is a preferrable way to improve the therapeutic outcomes of metformin. Ginseng berry, the fruit of Panax ginseng Meyer, has investigated as a candidate in metformin combination mainly due to its anti-hyperglycemic, anti-hyperlipidemic, anti-obesity, anti-hepatic steatosis and anti-inflammatory effects. Moreover, the pharmacokinetic interaction of metformin via OCTs and MATEs leads to changes in the efficacy and/or toxicity of metformin. Thus, we assessed how ginseng berry extract (GB) affects metformin pharmacokinetics in mice, specially focusing on the effect of the treatment period (i.e., 1-day and 28-day) of GB on metformin pharmacokinetics. In 1-day and 28-day co-treatment of metformin and GB, GB did not affect renal excretion as a main elimination route of metformin and GB therefore did not change the systemic exposure of metformin. Interestingly, 28-day co-treatment of GB increased metformin concentration in the livers (i.e., 37.3, 59.3% and 60.9% increases versus 1-day metformin, 1-day metformin plus GB and 28-day metformin groups, respectively). This was probably due to the increased metformin uptake via OCT1 and decreased metformin biliary excretion via MATE1 in the livers. These results suggest that co-treatment of GB for 28 days (i.e., long-term combined treatment of GB) enhanced metformin concentration in the liver as a pharmacological target tissue of metformin. However, GB showed a negligible impact on the systemic exposure of metformin in relation to its toxicity (i.e., renal and plasma concentrations of metformin).

Novel method for kinetic analysis applied to transport by the uniporter OCT2

The kinetics of solute transport shed light on the roles these processes play in cellular physiology, and the absolute values of the kinetic parameters that quantitatively describe transport are increasingly used to model its impact on drug clearance. However, accurate assessment of transport kinetics is challenging. Although most carrier-mediated transport is adequately described by the Michaelis-Menten equation, its use presupposes that the rates of uptake used in the analysis of maximal rates of transport (Jmax) and half-saturation constants (Kt) reflect true unidirectional rates of influx from known concentrations of substrate. Most experimental protocols estimate the initial rate of transport from net substrate accumulation determined at a single time point (typically between 0.5 and 5 min) and assume it reflects unidirectional influx. However, this approach generally results in systematic underestimates of Jmax and overestimates of Kt; the former primarily due to the unaccounted impact of efflux of accumulated substrate, and the latter due to the influence of unstirred water layers. Here, we describe the bases of these time-dependent effects and introduce a computational model that analyzes the time course of net substrate uptake at several concentrations to calculate Jmax and Kt for unidirectional influx, taking into account the influence of unstirred water layers and mediated efflux. This method was then applied to calculate the kinetics of transport of 1-methyl-4-phenylpryridinium and metformin by renal organic cation transporter 2 as expressed in cultured Chinese hamster ovary cells.NEW & NOTEWORTHY Here, we describe a mathematical model that uses the time course of net substrate uptake into cells from several increasing concentrations to calculate unique kinetic parameters [maximal rates of transport (Jmax) and half-saturation constants (Kt)] of the process. The method is the first to take into consideration the common complicating factors of unstirred layers and carrier-mediated efflux in the experimental determination of transport kinetics.

Exposure-response analyses for the MET inhibitor tepotinib including patients in the pivotal VISION trial: support for dosage recommendations

Purpose

Tepotinib is a highly selective MET inhibitor approved for treatment of non-small cell lung cancer (NSCLC) harboring METex14 skipping alterations. Analyses presented herein evaluated the relationship between tepotinib exposure, and efficacy and safety outcomes.

Methods

Exposure–efficacy analyses included data from an ongoing phase 2 study (VISION) investigating 500 mg/day tepotinib in NSCLC harboring METex14 skipping alterations. Efficacy endpoints included objective response, duration of response, and progression-free survival. Exposure–safety analyses included data from VISION, plus four completed studies in advanced solid tumors/hepatocellular carcinoma (30–1400 mg). Safety endpoints included edema, serum albumin, creatinine, amylase, lipase, alanine aminotransferase, aspartate aminotransferase, and QT interval corrected using Fridericia’s method (QTcF).

Results

Tepotinib exhibited flat exposure–efficacy relationships for all endpoints within the exposure range observed with 500 mg/day. Tepotinib also exhibited flat exposure–safety relationships for all endpoints within the exposure range observed with 30–1400 mg doses. Edema is the most frequently reported adverse event and the most frequent cause of tepotinib dose reductions and interruptions; however, the effect plateaued at low exposures. Concentration-QTc analyses using data from 30 to 1400 mg tepotinib resulted in the upper bounds of the 90% confidence interval being less than 10 ms for the mean exposures at the therapeutic (500 mg) and supratherapeutic (1000 mg) doses.

Conclusions

These analyses provide important quantitative pharmacologic support for benefit/risk assessment of the 500 mg/day dosage of tepotinib as being appropriate for the treatment of NSCLC harboring METex14 skipping alterations.

Registration Numbers

NCT01014936, NCT01832506, NCT01988493, NCT02115373, NCT02864992.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00280-022-04441-3.

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.

Effect of Chronic Kidney Disease on the Renal Secretion via Organic Anion Transporters 1/3: Implications for Physiologically-Based Pharmacokinetic Modeling and Dose Adjustment

There is growing evidence that active tubular secretory clearance (CL_s) may not decline proportionally with the glomerular filtration rate (GFR) in chronic kidney disease (CKD), leading to the overestimation of renal clearance (CL_r) when using solely GFR to approximate disease effect on renal elimination. The clinical pharmacokinetic data of 33 renally secreted OAT1/3 substrates were collated to investigate the impact of mild, moderate, and severe CKD on CL_r, tubular secretion and protein binding (f_u,p). The f_u,p of the collated substrates ranged from 0.0026 to 1.0 in healthy populations; observed CKD‐related increase in the f_u,p (up to 2.7‐fold) of 8 highly bound substrates (f_u,p ≤ 0.2) was accounted for in the analysis. Use of prediction equation based on disease‐related changes in albumin resulted in underprediction of the CKD‐related increase in f_u,p of highly bound substrates, highlighting the necessity to measure protein binding in severe CKD. The critical analysis of clinical data for 33 OAT1/3 probes established that decrease in OAT1/3 activity proportional to the changes in GFR was insufficient to recapitulate effects of severe CKD on unbound tubular secretion clearance. OAT1/3‐mediated CL_s was estimated to decline by an additional 50% relative to the GFR decline in severe CKD, whereas change in active secretion in mild and moderate CKD was proportional to GFR. Consideration of this additional 50% decline in OAT1/3‐mediated CL_s is recommended for physiologically‐based pharmacokinetic models and dose adjustment of OAT1/3 substrates in severe CKD, especially for substrates with high contribution of the active secretion to CL_r.

PBPK Simulation-Based Evaluation of Ganciclovir Crystalluria Risk Factors: Effect of Renal Impairment, Old Age, and Low Fluid Intake

Dosing guidance is often lacking for chronic kidney disease (CKD) due to exclusion of such patients from pivotal clinical trials. Physiologically based pharmacokinetic (PBPK) modelling supports model-informed dosing when clinical data are lacking, but application of these approaches to patients with impaired renal function is not yet at full maturity. In the current study, a ganciclovir PBPK model was developed for patients with normal renal function and extended to CKD population. CKD-related changes in tubular secretion were explored in the mechanistic kidney model and implemented either as proportional or non-proportional decline relative to GFR. Crystalluria risk was evaluated in different clinical settings (old age, severe CKD and low fluid intake) by simulating ganciclovir medullary collecting duct (MCD) concentrations. The ganciclovir PBPK model captured observed changes in systemic pharmacokinetic endpoints in mild-to-severe CKD; these trends were evident irrespective of assumed pathophysiological mechanism of altered active tubular secretion in the model. Minimal difference in simulated ganciclovir MCD concentrations was noted between young adult and geriatric populations with normal renal function and urine flow (1 mL/min), with lower concentrations predicted for severe CKD patients. High crystalluria risk was identified at reduced urine flow (0.1 mL/min) as simulated ganciclovir MCD concentrations exceeded its solubility (2.6–6 mg/mL), irrespective of underlying renal function. The analysis highlighted the importance of appropriate distribution of virtual subjects’ systems data in CKD populations. The ganciclovir PBPK model illustrates the ability of this translational tool to explore individual and combined effects of age, urine flow, and renal impairment on local drug renal exposure.

Physiologically-Based Pharmacokinetic Modelling of Creatinine-Drug Interactions in the Chronic Kidney Disease Population

Elevated serum creatinine (S_Cr ) caused by the inhibition of renal transporter(s) may be misinterpreted as kidney injury. The interpretation is more complicated in patients with chronic kidney disease (CKD) due to altered disposition of creatinine and renal transporter inhibitors. A clinical study was conducted in 17 patients with CKD (estimated glomerular filtration rate 15-59 mL/min/1.73 m² ); changes in S_Cr were monitored during trimethoprim treatment (100-200 mg/day), administered to prevent recurrent urinary infection, relative to the baseline level. Additional S_Cr -interaction data with trimethoprim, cimetidine, and famotidine in patients with CKD were collated from the literature. Our published physiologically-based creatinine model was extended to predict the effect of the CKD on S_Cr and creatinine-drug interaction. The creatinine-CKD model incorporated age/sex-related differences in creatinine synthesis, CKD-related glomerular filtration deterioration; change in transporter activity either proportional or disproportional to glomerular filtration rate (GFR) decline were explored. Optimized models successfully recovered baseline S_Cr from 64 patients with CKD (geometric mean fold-error of 1.1). Combined with pharmacokinetic models of inhibitors, the creatinine model was used to simulate transporter-mediated creatinine-drug interactions. Use of inhibitor unbound plasma concentrations resulted in 66% of simulated S_Cr interaction data within the prediction limits, with cimetidine interaction significantly underestimated. Assuming that transporter activity deteriorates disproportional to GFR decline resulted in higher predicted sensitivity to transporter inhibition in patients with CKD relative to healthy patients, consistent with sparse clinical data. For the first time, this novel modelling approach enables quantitative prediction of S_Cr in CKD and delineation of the effect of disease and renal transporter inhibition in this patient population.

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.

Does "Birth" as an Event Impact Maturation Trajectory of Renal Clearance via Glomerular Filtration? Reexamining Data in Preterm and Full-Term Neonates by Avoiding the Creatinine Bias

Glomerular filtration rate (GFR) is an important measure of renal function. Various models for its maturation have recently been compared; however, these have used markers, which are subject to different renal elimination processes. Inulin clearance data (a purer probe of GFR) collected from the literature were used to determine age‐related changes in GFR aspects of renal drug excretion in pediatrics. An ontogeny model was derived using a best‐fit model with various combinations of covariates such as postnatal age, gestational age at birth, and body weight. The model was applied to the prediction of systemic clearance of amikacin, gentamicin, vancomycin, and gadobutrol. During neonatal life, GFR increased as a function of both gestational age at birth and postnatal age, hence implying an impact of birth and a discrepancy in GFR for neonates with the same postmenstrual age depending on gestational age at birth (ie, neonates who were outside the womb longer had higher GFR, on average). The difference in GFR between pre‐term and full‐term neonates with the same postmenstrual age was negligible from beyond 1.25 years. Considering both postnatal age and gestational age at birth in GFR ontogeny models is important because postmenstrual age alone ignores the impact of birth. Most GFR models use covariates of body size in addition to age. Therefore, prediction from these models will also depend on the change in anthropometric characteristics with age. The latter may not be similar in various ethnic groups, and this makes the head‐to‐head comparison of models very challenging.

Mechanistic Models as Framework for Understanding Biomarker Disposition: Prediction of Creatinine-Drug Interactions

Creatinine is widely used as a biomarker of glomerular filtration, and, hence, renal function. However, transporter-mediated secretion also contributes to its renal clearance, albeit to a lesser degree. Inhibition of these transporters causes transient serum creatinine elevation, which can be mistaken as impaired renal function. The current study developed mechanistic models of creatinine kinetics within physiologically based framework accounting for multiple transporters involved in creatinine renal elimination, assuming either unidirectional or bidirectional-OCT2 transport (driven by electrochemical gradient). Robustness of creatinine models was assessed by predicting creatinine-drug interactions with 10 perpetrators; performance evaluation accounted for 5% intra-individual variability in serum creatinine. Models showed comparable predictive performances of the maximum steady-state effect regardless of OCT2 directionality assumptions. However, only the bidirectional-OCT2 model successfully predicted the minimal effect of ranitidine. The dynamic nature of models provides clear advantage to static approaches and most advanced framework for evaluating interplay between multiple processes in creatinine renal disposition.