Key to Opening Kidney for In Vitro-In Vivo Extrapolation Entrance in Health and Disease: Part II: Mechanistic Models and In Vitro-In Vivo Extrapolation

Albumin-Mediated Drug Uptake by Organic Anion Transporter 1/3 Is Real: Implications for the Prediction of Active Renal Secretion Clearance

Modulation of the transport-mediated active uptake by human serum albumin (HSA) for highly protein-bound substrates has been reported and improved the in vitro-to-in vivo extrapolation (IVIVE) of hepatic clearance. However, evidence for the relevance of such a phenomenon in the case of renal transporters is sparse. In this study, transport of renal organic anion transporter 1 or 3 (OAT1/3) substrates into conditionally immortalized proximal tubular epithelial cells transduced with OAT1/3 was measured in the presence and absence of 1 and 4% HSA while keeping the unbound substrate concentration constant (based on measured fraction unbound, fu,inc). In the presence of 4% HSA, the unbound intrinsic active uptake clearance (CLint,u,active) of six highly protein-bound substrates increased substantially relative to the HSA-free control (3.5- to 122-fold for the OAT1 CLint,u,active, and up to 28-fold for the OAT3 CLint,u,active). The albumin-mediated uptake effect (fold increase in CLint,u,active) was more pronounced with highly bound substrates compared to no effect seen for weakly protein-bound substrates adefovir (OAT1-specific) and oseltamivir carboxylate (OAT3-specific). The relationship between OAT1/3 CLint,u,active and fu,inc agreed with the facilitated-dissociation model; a relationship was established between the albumin-mediated fold change in CLint,u,active and fu,inc for both the OAT1 and OAT3, with implications for IVIVE modeling. The relative activity factor and the relative expression factor based on global proteomic quantification of in vitro OAT1/3 expression were applied for IVIVE of renal clearance. The inclusion of HSA improved the bottom-up prediction of the level of OAT1/3-mediated secretion and renal clearance (CLsec and CLr), in contrast to the underprediction observed with the control (HSA-free) scenario. For the first time, this study confirmed the presence of the albumin-mediated uptake effect with renal OAT1/3 transporters; the extent of the effect was more pronounced for highly protein-bound substrates. We recommend the inclusion of HSA in routine in vitro OAT1/3 assays due to considerable improvements in the IVIVE of CLsec and CLr.

Assessment of osteopontin as an early nephrotoxicity indicator in human renal proximal tubule cells and its application in evaluating lanthanum-induced nephrotoxicity

Nephrotoxicity is a common adverse effect induced by various chemicals, necessitating the development of reliable toxicity screening models for nephrotoxicity assessment. In this study, we assessed a group of nephrotoxicity indicators derived from different toxicity pathways, including conventional endpoints and kidney tubular injury biomarkers such as clusterin (CLU), kidney injury molecule-I (KIM-1), osteopontin (OPN), and neutrophil gelatinase-associated lipocalin (NGAL), using HK-2 and induced pluripotent stem cells (iPSCs)-derived renal proximal tubular epithelial-like cells (PTLs). Among the biomarkers tested, OPN emerged as the most discerning and precise marker. The predictive potential of OPN was tested using a panel of 10 nephrotoxic and 5 non-nephrotoxic compounds. The results demonstrated that combining OPN with the half-maximal inhibitory concentration (IC50) enhanced the diagnostic accuracy in both cellular models. Additionally, PTLs cells showed superior predictive efficacy for nephrotoxicity compared to HK-2 cells in this investigation. The two cellular models were utilized to evaluate the nephrotoxicity of lanthanum. The findings indicated that lanthanum possesses nephrotoxic properties; however, the degree of nephrotoxicity was relatively low, consistent with the outcomes of in vivo experiments.

Incubation Time Influences Organic Anion Transporter 1 Kinetics and Renal Clearance Predictions

Accurate predictions of drug uptake transporter involvement in renal excretion of xenobiotics require determination of in vitro transport kinetic parameters under initial-rate conditions. The purpose of the present study was to determine how changing the incubation time from initial rate to steady state influences ligand interactions with the renal organic anion transporter 1 (OAT1), and the impact of the different experimental conditions on pharmacokinetic predictions. Transport studies were performed with Chinese hamster ovary cells expressing OAT1 (CHO-OAT1) and the Simcyp Simulator was used for physiological-based pharmacokinetic predictions. Maximal transport rate and intrinsic uptake clearance (CL_int) for PAH decreased with increasing incubation time. The CL_int values ranged 11-fold with incubation times spanning from 15 s (CL_int,15s, initial rate) to 45 min (CL_int,45min, steady state). The Michaelis constant (K_m) was also influenced by the incubation time with an apparent increase in the Km value at longer incubation times. Inhibition potency of five drugs against PAH transport was tested using incubation times of either 15 s or 10 min. There was no effect of time on inhibition potency for omeprazole or furosemide, whereas indomethacin was less potent, and probenecid (~2-fold) and telmisartan (~7-fold) more potent with the longer incubation time. Notably, the inhibitory effect of telmisartan was reversible, albeit slowly. A pharmacokinetic model was developed for PAH using the CL_int,15s value. The simulated plasma concentration-time profile, renal clearance, and cumulative urinary excretion-time profile of PAH agreed well with reported clinical data, and the PK parameters were sensitive to the time-associated CL_int value used in the model.

Physiologically Based Pharmacokinetic Modelling to Predict Pharmacokinetics of Enavogliflozin, a Sodium-Dependent Glucose Transporter 2 Inhibitor, in Humans

Enavogliflozin is a sodium-dependent glucose cotransporter 2 (SGLT2) inhibitor approved for clinical use in South Korea. As SGLT2 inhibitors are a treatment option for patients with diabetes, enavogliflozin is expected to be prescribed in various populations. Physiologically based pharmacokinetic (PBPK) modelling can rationally predict the concentration–time profiles under altered physiological conditions. In previous studies, one of the metabolites (M1) appeared to have a metabolic ratio between 0.20 and 0.25. In this study, PBPK models for enavogliflozin and M1 were developed using published clinical trial data. The PBPK model for enavogliflozin incorporated a non-linear urinary excretion in a mechanistically arranged kidney model and a non-linear formation of M1 in the liver. The PBPK model was evaluated, and the simulated pharmacokinetic characteristics were in a two-fold range from those of the observations. The pharmacokinetic parameters of enavogliflozin were predicted using the PBPK model under pathophysiological conditions. PBPK models for enavogliflozin and M1 were developed and validated, and they seemed useful for logical prediction.

Nephrotoxicity induced by natural compounds from herbal medicines - a challenge for clinical application

Herbal medicines (HMs) have long been considered safe and effective without serious toxic and side effects. With the continuous use of HMs, more and more attention has been paid to adverse reactions and toxic events, especially the nephrotoxicity caused by natural compounds in HMs. The composition of HMs is complex and various, especially the mechanism of toxic components has been a difficult and hot topic. This review comprehensively summarizes the kidney toxicity characterization and mechanism of nephrotoxic natural compounds (organic acids, alkaloids, glycosides, terpenoids, phenylpropanoids, flavonoids, anthraquinones, cytotoxic proteins, and minerals) from different sources. Recommendations for the prevention and treatment of HMs-induced kidney injury were provided. In vitro and in vivo models for evaluating nephrotoxicity and the latest biomarkers are also included in this investigation. More broadly, this review may provide theoretical basis for safety evaluation and further comprehensive development and utilization of HMs in the future.

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.

IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making

During the past few decades, the science of toxicology has been undergoing a transformation from observational to predictive science. New approach methodologies (NAMs), including in vitro assays, in silico models, read-across, and in vitro to in vivo extrapolation (IVIVE), are being developed to reduce, refine, or replace whole animal testing, encouraging the judicious use of time and resources. Some of these methods have advanced past the exploratory research stage and are beginning to gain acceptance for the risk assessment of chemicals. A review of the recent literature reveals a burst of IVIVE publications over the past decade. In this review, we propose operational definitions for IVIVE, present literature examples for several common toxicity endpoints, and highlight their implications in decision-making processes across various federal agencies, as well as international organizations, including those in the European Union (EU). The current challenges and future needs are also summarized for IVIVE. In addition to refining and reducing the number of animals in traditional toxicity testing protocols and being used for prioritizing chemical testing, the goal to use IVIVE to facilitate the replacement of animal models can be achieved through their continued evolution and development, including a strategic plan to qualify IVIVE methods for regulatory acceptance.

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 model of renally cleared antibacterial drugs in Chinese renal impairment patients

To preliminarily develop physiologically based population models for Chinese renal impairment patients and to evaluate the prediction performance of new population models by renally cleared antibacterial drugs. First, demographic data and physiological parameters of Chinese renal impairment patients were collected, and then the coefficients of the relative demographic and physiological equation were recalibrated to construct the new population models. Second, drug‐independent parameters of ceftazidime, cefodizime, vancomycin, and cefuroxime were collected and verified by Chinese healthy volunteers, Caucasian healthy volunteers, and Caucasian renal impairment population models built in Simcyp. Finally, the newly developed population models were applied to predict the plasma concentration of four antibacterial drugs in Chinese renal impairment patients. The new physiologically based pharmacokinetic (PBPK) population models can predict the main pharmacokinetic parameters, including area under the plasma concentration–time curve extrapolated to infinity (AUC_inf), renal clearance (CL_r), and peak concentration (C_max), of ceftazidime, cefodizime, vancomycin, and cefuroxime following intravenous administrations with less than twofold error in mild, moderate, and severe Chinese renal impairment patients. The accuracy and precision of the predictions were improved compared with the Chinese healthy volunteers and Caucasian renal impairment population models. The PBPK population models were preliminarily developed and the first‐step validation results of four antibacterial drugs following intravenous administration showed acceptable accuracy and precision. The population models still need more systematic validation by using more drugs and scenarios in future studies to support their applications on dosage recommendation for Chinese renal impairment patients.

Prediction of Drug Clearance from Enzyme and Transporter Kinetics

Accurate estimation of in vivo clearance in human is pivotal to determine the dose and dosing regimen for drug development. In vitro-in vivo extrapolation (IVIVE) has been performed to predict drug clearance using empirical and physiological scalars. Multiple in vitro systems and mathematical modeling techniques have been employed to estimate in vivo clearance. The models for predicting clearance have significantly improved and have evolved to become more complex by integrating multiple processes such as drug metabolism and transport as well as passive diffusion. This chapter covers the use of conventional as well as recently developed methods to predict metabolic and transporter-mediated clearance along with the advantages and disadvantages of using these methods and the associated experimental considerations. The general approaches to improve IVIVE by use of appropriate scalars, incorporation of extrahepatic metabolism and transport and application of physiologically based pharmacokinetic (PBPK) models with proteomics data are also discussed. The chapter also provides an overview of the advantages of using such dynamic mechanistic models over static models for clearance predictions to improve IVIVE.

Dose Optimization in Kidney Disease: Opportunities for PBPK Modeling and Simulation

Kidney disease affects pharmacokinetic (PK) profiles of not only renally cleared drugs but also nonrenally cleared drugs. The impact of kidney disease on drug disposition has not been fully elucidated, but describing the extent of such impact is essential for conducting dose optimization in kidney disease. Accurate evaluation of kidney function has been a clinical interest for dose optimization, and more scientists pay attention and conduct research for clarifying the role of drug transporters, metabolic enzymes, and their interplay in drug disposition as kidney disease progresses. Physiologically based pharmacokinetic (PBPK) modeling and simulation can provide valuable insights for dose optimization in kidney disease. It is a powerful tool to integrate discrete knowledge from preclinical and clinical research and mechanistically investigate system- and drug-dependent factors that may contribute to the changes in PK profiles. PBPK-based prediction of drug exposures may be used a priori to adjust dosing regimens and thereby minimize the likelihood of drug-related toxicity. With real-time clinical studies, parameter estimation may be performed with PBPK approaches that can facilitate identification of sources of interindividual variability. PBPK modeling may also facilitate biomarker research that aids dose optimization in kidney disease. U.S. Food and Drug Administration guidances related to conduction of PK studies in kidney impairment and PBPK documentation provide the foundation for facilitating model-based dose-finding research in kidney disease.

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

Creatinine is the most common clinical biomarker of renal function. As a substrate for renal transporters, its secretion is susceptible to inhibition by drugs, resulting in transient increase in serum creatinine and false impression of damage to kidney. Novel physiologically based models for creatinine were developed here and (dis)qualified in a stepwise manner until consistency with clinical data. Data from a matrix of studies were integrated, including systems data (common to all models), proteomics-informed in vitro-in vivo extrapolation of all relevant transporter clearances, exogenous administration of creatinine (to estimate endogenous synthesis rate), and inhibition of different renal transporters (11 perpetrator drugs considered for qualification during creatinine model development and verification on independent data sets). The proteomics-informed bottom-up approach resulted in the underprediction of creatinine renal secretion. Subsequently, creatinine-trimethoprim clinical data were used to inform key model parameters in a reverse translation manner, highlighting best practices and challenges for middle-out optimization of mechanistic models.

Predicting tubular reabsorption with a human kidney proximal tubule tissue-on-a-chip and physiologically-based modeling

Kidney is a major route of xenobiotic excretion, but the accuracy of preclinical data for predicting in vivo clearance is limited by species differences and non-physiologic 2D culture conditions. Microphysiological systems can potentially increase predictive accuracy due to their more realistic 3D environment and incorporation of dynamic flow. We used a renal proximal tubule microphysiological device to predict renal reabsorption of five compounds: creatinine (negative control), perfluorooctanoic acid (positive control), cisplatin, gentamicin, and cadmium. We perfused compound-containing media to determine renal uptake/reabsorption, adjusted for non-specific binding. A physiologically-based parallel tube model was used to model reabsorption kinetics and make predictions of overall in vivo renal clearance. For all compounds tested, the kidney tubule chip combined with physiologically-based modeling reproduces qualitatively and quantitatively in vivo tubular reabsorption and clearance. However, because the in vitro device lacks filtration and tubular secretion components, additional information on protein binding and the importance of secretory transport is needed in order to make accurate predictions. These and other limitations, such as the presence of non-physiological compounds such as antibiotics and bovine serum albumin in media and the need to better characterize degree of expression of important transporters, highlight some of the challenges with using microphysiological devices to predict in vivo pharmacokinetics.

Molecular and cellular physiology of organic cation transporter 2

Organic cation transporters play a critical role in mediating the distribution of cationic pharmaceuticals. Indeed, organic cation transporter (OCT)2 is the initial step in the renal secretion of organic cations and consequently plays a defining role in establishing the pharmacokinetics of many cationic drugs. Although a hallmark of OCTs is their broad selectivity, this characteristic also makes them targets for unwanted, adverse drug-drug interactions (DDIs), making them a focus for efforts to develop models of ligand interaction that could predict and preempt these adverse interactions. This review discusses the molecular characteristics of these transporters as well as the evidence that established the OCTs as key players in the distribution of organic cations. However, the primary focus is the present understanding of the complexity of ligand interaction with OCTs, particularly OCT2, including evidence for the presence of multiple ligand-binding sites and the influence of substrate structure on the affinity of the transporter for inhibitory ligands. This leads to a discussion of the complexities associated with the development of protocols for assessing the inhibitory potential of new molecular entities to perpetrate unwanted DDIs, the criteria that should be considered in the interpretation of the results of such protocols, and the challenges associated with development of models capable of predicting unwanted DDIs.

Challenges in working towards an internal threshold of toxicological concern (iTTC) for use in the safety assessment of cosmetics: Discussions from the Cosmetics Europe iTTC Working Group workshop

The Threshold of Toxicological Concern (TTC) is an important risk assessment tool which establishes acceptable low-level exposure values to be applied to chemicals with limited toxicological data. One of the logical next steps in the continued evolution of TTC is to develop this concept further so that it is representative of internal exposures (TTC based on plasma concentration). An internal TTC (iTTC) would provide threshold values that could be utilized in exposure-based safety assessments. As part of a Cosmetics Europe (CosEu) research program, CosEu has initiated a project that is working towards the development of iTTCs that can be used for the human safety assessment. Knowing that the development of an iTTC is an ambitious and broad-spanning topic, CosEu organized a Working Group comprised a balance of multiple stakeholders (cosmetics and chemical industries, the EPA and JRC and academia) with relevant experience and expertise and workshop to critically evaluate the requirements to establish an iTTC. Outcomes from the workshop included an evaluation on the current state of the science for iTTC, the overall iTTC strategy, selection of chemical databases, capture and curation of chemical information, ADME and repeat dose data, expected challenges, as well as next steps and ongoing work.

Identification and quantification of blood-brain barrier transporters in isolated rat brain microvessels

The blood-brain barrier (BBB) maintains brain homeostasis by tightly regulating the exchange of molecules with systemic circulation. It consists primarily of microvascular endothelial cells surrounded by astrocytic endfeet, pericytes, and microglia. Understanding the make-up of transporters in rat BBB is essential to the translation of pharmacological and toxicological observations into humans. In this study, experimental workflows are presented in which the optimization of (a) isolation of rat brain microvessels (b) enrichment of endothelial cells, and (c) extraction and digestion of proteins were evaluated, followed by identification and quantification of BBB proteins. Optimization of microvessel isolation was indicated by 15-fold enrichment of endothelial cell marker Glut1 mRNA, whereas markers for other cell types were not enriched. Filter-aided sample preparation was shown to be superior to in-solution sample preparation (10251 peptides vs. 7533 peptides). Label-free proteomics was used to identify nearly 2000 proteins and quantify 1276 proteins in isolated microvessels. A combination of targeted and global proteomics was adopted to measure protein abundance of 6 ATP-binding cassette and 27 solute carrier transporters. Data analysis using proprietary Progenesis and open access MaxQuant software showed overall agreement; however, Abcb9 and Slc22a8 were quantified only by MaxQuant, whereas Abcc9 and Abcd3 were quantified only by Progenesis. Agreement between targeted and untargeted quantification was demonstrated for Abcb1 (19.7 ± 1.4 vs. 17.8 ± 2.3) and Abcc4 (2.2 ± 0.7 vs. 2.1 ± 0.4), respectively. Rigorous quantification of BBB proteins, as reported in this study, should assist with translational modeling efforts involving brain disposition of xenobiotics.

Advances in predictive in vitro models of drug-induced nephrotoxicity

In vitro screens for nephrotoxicity are currently poorly predictive of toxicity in humans. Although the functional proteins that are expressed by nephron tubules and mediate drug susceptibility are well known, current in vitro cellular models poorly replicate both the morphology and the function of kidney tubules and therefore fail to demonstrate injury responses to drugs that would be nephrotoxic in vivo. Advances in protocols to enable the directed differentiation of pluripotent stem cells into multiple renal cell types and the development of microfluidic and 3D culture systems have opened a range of potential new platforms for evaluating drug nephrotoxicity. Many of the new in vitro culture systems have been characterized by the expression and function of transporters, enzymes, and other functional proteins that are expressed by the kidney and have been implicated in drug-induced renal injury. In vitro platforms that express these proteins and exhibit molecular biomarkers that have been used as readouts of injury demonstrate improved functional maturity compared with static 2D cultures and represent an opportunity to model injury to renal cell types that have hitherto received little attention. As nephrotoxicity screening platforms become more physiologically relevant, they will facilitate the development of safer drugs and improved clinical management of nephrotoxicants.

Systems Toxicology: Real World Applications and Opportunities

Systems Toxicology aims to change the basis of how adverse biological effects of xenobiotics are characterized from empirical end points to describing modes of action as adverse outcome pathways and perturbed networks. Toward this aim, Systems Toxicology entails the integration of in vitro and in vivo toxicity data with computational modeling. This evolving approach depends critically on data reliability and relevance, which in turn depends on the quality of experimental models and bioanalysis techniques used to generate toxicological data. Systems Toxicology involves the use of large-scale data streams ("big data"), such as those derived from omics measurements that require computational means for obtaining informative results. Thus, integrative analysis of multiple molecular measurements, particularly acquired by omics strategies, is a key approach in Systems Toxicology. In recent years, there have been significant advances centered on in vitro test systems and bioanalytical strategies, yet a frontier challenge concerns linking observed network perturbations to phenotypes, which will require understanding pathways and networks that give rise to adverse responses. This summary perspective from a 2016 Systems Toxicology meeting, an international conference held in the Alps of Switzerland, describes the limitations and opportunities of selected emerging applications in this rapidly advancing field. Systems Toxicology aims to change the basis of how adverse biological effects of xenobiotics are characterized, from empirical end points to pathways of toxicity. This requires the integration of in vitro and in vivo data with computational modeling. Test systems and bioanalytical technologies have made significant advances, but ensuring data reliability and relevance is an ongoing concern. The major challenge facing the new pathway approach is determining how to link observed network perturbations to phenotypic toxicity.

Physiologically Based Pharmacokinetic Modeling of Drug Transporters to Facilitate Individualized Dose Prediction

Physiologically based pharmacokinetic modeling is a commonly used strategy in the drug development and regulatory submissions. This commentary provides a critical overview of the current status of physiologically based pharmacokinetic methodologies to predict transporter-mediated pharmacokinetics, in addition to the impact of disease and genetics with respect to local and systemic concentration.

Microsomal and Cytosolic Scaling Factors in Dog and Human Kidney Cortex and Application for In Vitro-In Vivo Extrapolation of Renal Metabolic Clearance

In vitro-in vivo extrapolation of drug metabolism data obtained in enriched preparations of subcellular fractions rely on robust estimates of physiologically relevant scaling factors for the prediction of clearance in vivo. The purpose of the current study was to measure the microsomal and cytosolic protein per gram of kidney (MPPGK and CPPGK) in dog and human kidney cortex using appropriate protein recovery marker and evaluate functional activity of human cortex microsomes. Cytochrome P450 (CYP) content and glucose-6-phosphatase (G6Pase) activity were used as microsomal protein markers, whereas glutathione-S-transferase activity was a cytosolic marker. Functional activity of human microsomal samples was assessed by measuring mycophenolic acid glucuronidation. MPPGK was 33.9 and 44.0 mg/g in dog kidney cortex, and 41.1 and 63.6 mg/g in dog liver (n = 17), using P450 content and G6Pase activity, respectively. No trends were noted between kidney, liver, and intestinal scalars from the same animals. Species differences were evident, as human MPPGK and CPPGK were 26.2 and 53.3 mg/g in kidney cortex (n = 38), respectively. MPPGK was 2-fold greater than the commonly used in vitro-in vivo extrapolation scalar; this difference was attributed mainly to tissue source (mixed kidney regions versus cortex). Robust human MPPGK and CPPGK scalars were measured for the first time. The work emphasized the importance of regional differences (cortex versus whole kidney–specific MPPGK, tissue weight, and blood flow) and a need to account for these to improve assessment of renal metabolic clearance and its extrapolation to in vivo.

Delineating the Role of Various Factors in Renal Disposition of Digoxin through Application of Physiologically Based Kidney Model to Renal Impairment Populations

Development of submodels of organs within physiologically-based pharmacokinetic (PBPK) principles and beyond simple perfusion limitations may be challenging because of underdeveloped in vitro-in vivo extrapolation approaches or lack of suitable clinical data for model refinement. However, advantage of such models in predicting clinical observations in divergent patient groups is now commonly acknowledged. Mechanistic understanding of altered renal secretion in renal impairment is one area that may benefit from such models, despite knowledge gaps in renal pathophysiology. In the current study, a PBPK kidney model was developed for digoxin, accounting for the roles of organic anion transporting peptide 4C1 (OATP4C1) and P-glycoprotein (P-gp) in its tubular secretion, with the aim to investigate the impact of age and renal impairment (moderate to severe) on renal drug disposition. Initial PBPK simulations based on changes in glomerular filtration rate (GFR) underestimated the observed reduction in digoxin renal excretion clearance (CL_R) in subjects with moderately impaired renal function relative to healthy. Reduction in either proximal tubule cell number or the OATP4C1 abundance in the mechanistic kidney model successfully predicted 59% decrease in digoxin CL_R, in particular when these changes were proportional to reduction in GFR. In contrast, predicted proximal tubule concentration of digoxin was only sensitive to changes in the transporter expression/ million proximal tubule cells. Based on the mechanistic modeling, reduced proximal tubule cellularity and OATP4C1 abundance, and inhibition of OATP4C1-mediated transport, are proposed as possible causes of reduced digoxin renal secretion in renally impaired patients.