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

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.

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.

Safety profile of intravenous digoxin in Chinese patients with acute heart failure with reduced ejection fraction: a small-scale prospective cohort study

Background: Adverse effects of intravenous digoxin vary from patients and disease status, which should be closely monitored. Aims: To explore the safety profile of intravenous digoxin in acute heart failure with reduced ejection fraction (HFrEF) among Chinese patients. Methods: A clinical prospective, single-center, single-arm, open-label exploratory clinical trial was performed in patients with acute HFrEF at Wuhan Asia Heart Hospital. A fixed dose of 0.5 mg digoxin was used intravenously once per day for 3 days. The normalized dosage of digoxin (NDD), toxic serum digoxin concentration (SDC), and adverse reactions of intravenous digoxin were recorded. Results: A total of 40 patients were recruited in the study. The SDC increased from 1.03 ± 0.34 ng/mL to 1.95 ± 0.52 ng/mL during treatment. 50% (20/40) patients reached a toxic SDC of 2.0 ng/mL, and toxic effects were seen in 30% (12/40) patients. Estimated glomerular filtration rate (eGFR) < 60 mL/min [HR: 5.269; 95% CI: 1.905-14.575, p = 0.001], NDD ≥7 μg/kg [HR: 3.028; 95% CI: 1.119-8.194, p = 0.029], and ischemic cardiomyopathy [HR: 2.658; 95% CI: 1.025-6.894, p = 0.044] were independent risk factors for toxic SDC. Toxic SDC was effectively identified [area under the receiver operating characteristic (ROC) curve = 0.85, p < 0.001] using this model, and patients would have a higher risk of toxicity with more risk factors. Conclusion: Intravenous digoxin of 0.5 mg was safe and effective for initial dose but not suitable for maintenance treatment in Chinese patients with acute HFrEF. Patients who had lower eGFR, received higher NDD, and had ischemic cardiomyopathy should be closely monitored to avoid digoxin toxicity.

Incorporating Uremic Solute-mediated Inhibition of OAT1/3 Improves PBPK Prediction of Tenofovir Renal and Systemic Disposition in Patients with Severe Kidney Disease

BACKGROUND

Dose modification of renally secreted drugs in patients with chronic kidney disease (CKD) has relied on serum creatinine concentration as a biomarker to estimate glomerular filtration (GFR) under the assumption that filtration and secretion decline in parallel. A discrepancy between actual renal clearance and predicted renal clearance based on GFR alone is observed in severe CKD patients with tenofovir, a compound secreted by renal OAT1/3. Uremic solutes that inhibit OAT1/3 may play a role in this divergence.

METHODS

To examine the impact of transporter inhibition by uremic solutes on tenofovir renal clearance, we determined the inhibitory potential of uremic solutes hippuric acid, indoxyl sulfate, and p-cresol sulfate. The inhibition parameters (IC50) were incorporated into a previously validated mechanistic kidney model; simulated renal clearance and plasma PK profile were compared to data from clinical studies.

RESULTS

Without the incorporation of uremic solute inhibition, the PBPK model failed to capture the observed data with an absolute average fold error (AAFE) > 2. However, when the inhibition of renal uptake transporters and uptake transporters in the slow distribution tissues were included, the AAFE value was within the pre-defined twofold model acceptance criterion, demonstrating successful model extrapolation to CKD patients.

CONCLUSION

A PBPK model that incorporates inhibition by uremic solutes has potential to better predict renal clearance and systemic disposition of secreted drugs in patients with CKD. Ongoing research is warranted to determine if the model can be expanded to include other OAT1/3 substrate drugs and to evaluate how these findings can be translated to clinical guidance for drug selection and dose optimization in patients with CKD.

Mechanistic Middle-Out Physiologically Based Toxicokinetic Modeling of Transporter-Dependent Disposition of Perfluorooctanoic Acid in Humans

Perfluorooctanoic acid (PFOA) is an environmental toxicant exhibiting a years-long biological half-life (t_1/2) in humans and is linked with adverse health effects. However, limited understanding of its toxicokinetics (TK) has obstructed the necessary risk assessment. Here, we constructed the first middle-out physiologically based toxicokinetic (PBTK) model to mechanistically explain the persistence of PFOA in humans. In vitro transporter kinetics were thoroughly characterized and scaled up to in vivo clearances using quantitative proteomics-based in vitro-to-in vivo extrapolation. These data and physicochemical parameters of PFOA were used to parameterize our model. We uncovered a novel uptake transporter for PFOA, highly likely to be monocarboxylate transporter 1 which is ubiquitously expressed in body tissues and may mediate broad tissue penetration. Our model was able to recapitulate clinical data from a phase I dose-escalation trial and divergent half-lives from clinical trial and biomonitoring studies. Simulations and sensitivity analyses confirmed the importance of renal transporters in driving extensive PFOA reabsorption, reducing its clearance and augmenting its t_1/2. Crucially, the inclusion of a hypothetical, saturable renal basolateral efflux transporter provided the first unified explanation for the divergent t_1/2 of PFOA reported in clinical (116 days) versus biomonitoring studies (1.3-3.9 years). Efforts are underway to build PBTK models for other perfluoroalkyl substances using similar workflows to assess their TK profiles and facilitate risk assessments.

Use of In Vivo Imaging and Physiologically-Based Kinetic Modelling to Predict Hepatic Transporter Mediated Drug-Drug Interactions in Rats

Gadoxetate, a magnetic resonance imaging (MRI) contrast agent, is a substrate of organic-anion-transporting polypeptide 1B1 and multidrug resistance-associated protein 2. Six drugs, with varying degrees of transporter inhibition, were used to assess gadoxetate dynamic contrast enhanced MRI biomarkers for transporter inhibition in rats. Prospective prediction of changes in gadoxetate systemic and liver AUC (AUCR), resulting from transporter modulation, were performed by physiologically-based pharmacokinetic (PBPK) modelling. A tracer-kinetic model was used to estimate rate constants for hepatic uptake (khe), and biliary excretion (kbh). The observed median fold-decreases in gadoxetate liver AUC were 3.8- and 1.5-fold for ciclosporin and rifampicin, respectively. Ketoconazole unexpectedly decreased systemic and liver gadoxetate AUCs; the remaining drugs investigated (asunaprevir, bosentan, and pioglitazone) caused marginal changes. Ciclosporin decreased gadoxetate khe and kbh by 3.78 and 0.09 mL/min/mL, while decreases for rifampicin were 7.20 and 0.07 mL/min/mL, respectively. The relative decrease in khe (e.g., 96% for ciclosporin) was similar to PBPK-predicted inhibition of uptake (97-98%). PBPK modelling correctly predicted changes in gadoxetate systemic AUCR, whereas underprediction of decreases in liver AUCs was evident. The current study illustrates the modelling framework and integration of liver imaging data, PBPK, and tracer-kinetic models for prospective quantification of hepatic transporter-mediated DDI in humans.

Kidney Drug Transporters in Pharmacotherapy

The kidney functions not only as a metabolite elimination organ but also plays an important role in pharmacotherapy. The kidney tubule epithelia cells express membrane carriers and transporters, which play an important role in drug elimination, and can determine drug nephrotoxicity and drug-drug interactions, as well as constituting direct drug targets. The above aspects of kidney transport proteins are discussed in the review.

Comparison of creatinine-based equations for estimating renal function for digoxin dose adjustment in patients with atrial fibrillation and heart failure

The aim of this study was to determine an appropriate equation for estimating renal function to dose regulate the serum digoxin trough concentration to a target of <0.9 ng/ml in patients with atrial fibrillation (AF) and heart failure (HF). All patients received 0.125 mg oral digoxin daily. The estimated glomerular filtration rate by the Modification of Diet in Renal Disease (eGFRMDRD ) equation deindexed based on body surface area had the highest correlation with digoxin trough concentrations (r = -0.450) compared to the Cockcroft-Gault equation (r = -0.415) or deindexed eGFR based on the Chronic Kidney Disease Epidemiology Collaboration (eGFRCKD-EPI ) equation (r = -0.416). The median digoxin trough concentrations were 0.60, 0.77, 0.97 and 1.30 ng/ml in patients with a deindexed eGFRMDRD  ≥ 60, 45-59, 30-44 and < 30 ml/min, respectively. The deindexed eGFRMDRD is an appropriate equation for digoxin dose adjustment in patients with AF and HF.

Assessment of Aging-Related Function Variations of P-gp Transporter in Old-Elderly Chinese CHF Patients Based on Modeling and Simulation

BACKGROUND AND OBJECTIVES

P-glycoprotein (P-gp) is one of the most intensely studied transporters owing to its broad tissue distribution and substrate specificity. Existing research suggests that the risk of systemic exposure to dabigatran etexilate (DABE) and digoxin, two P-gp probe substrates in vivo, has significantly increased in elderly patients. We applied a model-based quantitative pharmacological approach to assess aging-related P-gp changes in the Chinese old-elderly population.

METHODS

Population pharmacokinetic (PopPK) modeling was first performed using clinical pharmacokinetic data to explore the effect of age on the pharmacokinetic characteristics of dabigatran (DAB, the active principle of DABE) and digoxin in elderly Chinese patients. Corresponding physiologically based pharmacokinetic (PBPK) models were established to further explain the elevated systemic exposure to these two drugs. Eventually, standard dosing regimens of DABE and digoxin were assessed in Chinese old-elderly patients with chronic heart failure (CHF) with different stages of renal impairment.

RESULTS

PopPK analysis suggested that age as a covariate had an additional effect on the apparent clearance of these two drugs after correcting for creatinine clearance. PBPK simulation results suggested that disease-specific pathophysiological changes could explain DAB exposure in the young elderly. In the elderly population, 17.1% of elevated DAB exposure remained unexplained, and 25.5% of the reduced P-gp function associated with aging was ultimately obtained using sensitivity analysis. This value was further validated using digoxin data obtained by PBPK modeling. The simulation results suggest that CHF patients with advanced age and moderate-to-severe renal impairment require heightened vigilance for elevated exposure risk during the use of DABE and digoxin.

CONCLUSIONS

Aging might be a significant risk factor for elevated systemic exposure to DAB and digoxin by reducing P-gp-mediated efflux in the Chinese old elderly population.

Quantitative Proteomics in Translational Absorption, Distribution, Metabolism, and Excretion and Precision Medicine

A reliable translation of in vitro and preclinical data on drug absorption, distribution, metabolism, and excretion (ADME) to humans is important for safe and effective drug development. Precision medicine that is expected to provide the right clinical dose for the right patient at the right time requires a comprehensive understanding of population factors affecting drug disposition and response. Characterization of drug-metabolizing enzymes and transporters for the protein abundance and their interindividual as well as differential tissue and cross-species variabilities is important for translational ADME and precision medicine. This review first provides a brief overview of quantitative proteomics principles including liquid chromatography-tandem mass spectrometry tools, data acquisition approaches, proteomics sample preparation techniques, and quality controls for ensuring rigor and reproducibility in protein quantification data. Then, potential applications of quantitative proteomics in the translation of in vitro and preclinical data as well as prediction of interindividual variability are discussed in detail with tabulated examples. The applications of quantitative proteomics data in physiologically based pharmacokinetic modeling for ADME prediction are discussed with representative case examples. Finally, various considerations for reliable quantitative proteomics analysis for translational ADME and precision medicine and the future directions are discussed. SIGNIFICANCE STATEMENT: Quantitative proteomics analysis of drug-metabolizing enzymes and transporters in humans and preclinical species provides key physiological information that assists in the translation of in vitro and preclinical data to humans. This review provides the principles and applications of quantitative proteomics in characterizing in vitro, ex vivo, and preclinical models for translational research and interindividual variability prediction. Integration of these data into physiologically based pharmacokinetic modeling is proving to be critical for safe, effective, timely, and cost-effective drug development.

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.

Clinical Implications of Altered Drug Transporter Abundance/Function and PBPK Modeling in Specific Populations: An ITC Perspective

The role of membrane transporters on pharmacokinetics (PKs), drug-drug interactions (DDIs), pharmacodynamics (PDs), and toxicity of drugs has been broadly recognized. However, our knowledge of modulation of transporter expression and/or function in the diseased patient population or specific populations, such as pediatrics or pregnancy, is still emerging. This white paper highlights recent advances in studying the changes in transporter expression and activity in various diseases (i.e., renal and hepatic impairment and cancer) and some specific populations (i.e., pediatrics and pregnancy) with the focus on clinical implications. Proposed alterations in transporter abundance and/or activity in diseased and specific populations are based on (i) quantitative transporter proteomic data and relative abundance in specific populations vs. healthy adults, (ii) clinical PKs, and emerging transporter biomarker and/or pharmacogenomic data, and (iii) physiologically-based pharmacokinetic modeling and simulation. The potential for altered PK, PD, and toxicity in these populations needs to be considered for drugs and their active metabolites in which transporter-mediated uptake/efflux is a major contributor to their absorption, distribution, and elimination pathways and/or associated DDI risk. In addition to best practices, this white paper discusses current challenges and knowledge gaps to study and quantitatively predict the effects of modulation in transporter activity in these populations, together with the perspectives from the International Transporter Consortium (ITC) on future directions.

Pharmacogenomics Informs Cardiovascular Pharmacotherapy

Precision medicine exemplifies the emergence of personalized treatment options which may benefit specific patient populations based upon their genetic makeup. Application of pharmacogenomics requires an understanding of how genetic variations impact pharmacokinetic and pharmacodynamic properties. This particular approach in pharmacotherapy is helpful because it can assist in and improve clinical decisions. Application of pharmacogenomics to cardiovascular pharmacotherapy provides for the ability of the medical provider to gain critical knowledge on a patient's response to various treatment options and risk of side effects.

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.

Application of a PBPK Model of Rivaroxaban to Prospective Simulations of Drug-Drug-Disease Interactions with Protein Kinase Inhibitors in CA-VTE

BACKGROUND AND PURPOSE

Rivaroxaban is a viable anticoagulant for the management of cancer associated venous thromboembolism (CA-VTE). A previously verified physiologically-based pharmacokinetic (PBPK) model of rivaroxaban established how its multiple pathways of elimination via both CYP3A4/2J2-mediated hepatic metabolism and organic anion transporter 3 (OAT3)/P-glycoprotein-mediated renal secretion predisposes rivaroxaban to drug-drug-disease interactions (DDDIs) with clinically relevant protein kinase inhibitors (PKIs). We proposed the application of PBPK modelling to prospectively interrogate clinically significant DDIs between rivaroxaban and PKIs (erlotinib and nilotinib) for dose adjustments in CA-VTE.

EXPERIMENTAL APPROACH

The inhibitory potencies of the PKIs on CYP3A4/2J2-mediated metabolism of rivaroxaban were characterized. Using prototypical OAT3 inhibitor ketoconazole, in vitro OAT3 inhibition assays were optimized to ascertain the in vivo relevance of derived transport inhibitory constants (K_i ). Untested DDDIs between rivaroxaban and erlotinib or nilotinib were simulated.

KEY RESULTS

Mechanism-based inactivation (MBI) of CYP3A4-mediated rivaroxaban metabolism by both PKIs and MBI of CYP2J2 by erlotinib were established. The importance of substrate specificity and nonspecific binding to derive OAT3-inhibitory K_i values of ketoconazole and nilotinib for the accurate prediction of interactions was illustrated. When simulated rivaroxaban exposure variations with concomitant erlotinib and nilotinib therapy were evaluated using published dose-exposure equivalence metrics and bleeding risk analyses, dose reductions from 20 mg to 15 mg and 10 mg in normal and mild renal dysfunction, respectively, were warranted.

CONCLUSION AND IMPLICATIONS

We established a PBPK-DDDI model to prospectively evaluate clinically relevant interactions between rivaroxaban and PKIs for the safe and efficacious management of CA-VTE.

Quantitative Proteomic Map of Enzymes and Transporters in the Human Kidney: Stepping Closer to Mechanistic Kidney Models to Define Local Kinetics

The applications of translational modeling of local drug concentrations in various organs had a sharp increase over the last decade. These are part of the model-informed drug development initiative, adopted by the pharmaceutical industry and promoted by drug regulatory agencies. With respect to the kidney, the models serve as a bridge for understanding animal vs. human observations related to renal drug disposition and any consequential adverse effects. However, quantitative data on key drug-metabolizing enzymes and transporters relevant for predicting renal drug disposition are limited. Using targeted and global quantitative proteomics, we determined the abundance of multiple enzymes and transporters in 20 human kidney cortex samples. Nine enzymes and 22 transporters were quantified (8 for the first time in the kidneys). In addition, > 4,000 proteins were identified and used to form an open database. CYP2B6, CYP3A5, and CYP4F2 showed comparable, but generally low expression, whereas UGT1A9 and UGT2B7 levels were the highest. Significant correlation between abundance and activity (measured by mycophenolic acid clearance) was observed for UGT1A9 (Rs = 0.65, P = 0.004) and UGT2B7 (Rs = 0.70, P = 0.023). Expression of P-gp ≈ MATE-1 and OATP4C1 transporters were high. Strong intercorrelations were observed between several transporters (P-gp/MRP4, MRP2/OAT3, and OAT3/OAT4); no correlation in expression was apparent for functionally related transporters (OCT2/MATEs). This study extends our knowledge of pharmacologically relevant proteins in the kidney cortex, with implications on more prudent use of mechanistic kidney models under the general framework of quantitative systems pharmacology and toxicology.

Reduced physiologically-based pharmacokinetic model of dabigatran etexilate-dabigatran and its application for prediction of intestinal P-gp-mediated drug-drug interactions

BACKGROUND

Dabigatran etexilate (DABE) has been suggested as a clinical probe for intestinal P-glycoprotein (P-gp)-mediated drug-drug interaction (DDI) studies and, as an alternative to digoxin. Clinical DDI data with various P-gp inhibitors demonstrated a dose-dependent inhibition of P-gp with DABE. The aims of this study were to develop a joint DABE (prodrug)-dabigatran reduced physiologically-based-pharmacokinetic (PBPK) model and to evaluate its ability to predict differences in P-gp DDI magnitude between a microdose and a therapeutic dose of DABE.

METHODS

A joint DABE-dabigatran PBPK model was developed with a mechanistic intestinal model accounting for the regional P-gp distribution in the gastrointestinal tract. Model input parameters were estimated using DABE and dabigatran pharmacokinetic (PK) clinical data obtained after administration of DABE alone or with a strong P-gp inhibitor, itraconazole, and over a wide range of DABE doses (from 375 µg to 400 mg). Subsequently, the model was used to predict extent of DDI with additional P-gp inhibitors and with different DABE doses.

RESULTS

The reduced DABE-dabigatran PBPK model successfully described plasma concentrations of both prodrug and metabolite following administration of DABE at different dose levels and when co-administered with itraconazole. The model was able to capture the dose dependency in P-gp mediated DDI. Predicted magnitude of itraconazole P-gp DDI was higher at the microdose (predicted vs. observed median fold-increase in AUC_+inh/AUC_control (min-max) = 5.88 (4.29-7.93) vs. 6.92 (4.96-9.66) ) compared to the therapeutic dose (predicted median fold-increase in AUC_+inh/AUC_control = 3.48 (2.37-4.84) ). In addition, the reduced DABE-dabigatran PBPK model predicted successfully the extent of DDI with verapamil and clarithromycin as P-gp inhibitors. Model-based simulations of dose staggering predicted the maximum inhibition of P-gp when DABE microdose was concomitantly administered with itraconazole solution; simulations also highlighted dosing intervals required to minimise the DDI risk depending on the DABE dose administered (microdose vs. therapeutic).

CONCLUSIONS

This study provides a modelling framework for the evaluation of P-gp inhibitory potential of new molecular entities using DABE as a clinical probe. Simulations of dose staggering and regional differences in the extent of intestinal P-gp inhibition for DABE microdose and therapeutic dose provide model-based guidance for design of prospective clinical P-gp DDI studies.

Dosage Adjustment for Ceftazidime in Pediatric Patients With Renal Impairment Using Physiologically Based Pharmacokinetic Modeling

Physiologically based pharmacokinetic (PBPK) modeling has unique advantages in investigating the pharmacokinetics of drugs in special populations. Our aim is to design optimized dosing regimens for ceftazidime in renally-impaired pediatric patients using PBPK modeling. Models for healthy and renally-impaired adults were developed, verified, and adapted for children to predict ceftazidime exposure in pediatric patients with varying degrees of renal impairment, capturing age- and weight-related pharmacokinetic changes. We derived a dosage-adjusted regimen for renally-impaired children based on pharmacokinetic data and evaluated the pharmacodynamics of ceftazidime. The PBPK models adequately predicted ceftazidime exposures in populations after single- and multi-dose administrations, with fold error values within 1.1 between simulated and observed data. In moderate, severe, and end-stage renally-impaired pediatric patients, the areas under the plasma concentration-time curves (AUCs) were 1.87-fold, 3.56-fold, and 6.19-fold higher, respectively, than in healthy children when treated with the same dose of 50 mg/kg. Pharmacodynamic verification indicated that the recommended doses of 28, 15, and 8 mg/kg administered three times daily (every 8 h) to pediatric patients with moderate, severe, and end-stage renal disease, respectively, were sufficient to attain the target of maintaining the free plasma concentration at or above minimum inhibitory concentration (MIC) during 70% of the dosing interval (70% fT > MIC: nearly 100% target attainment for susceptible MIC of 4 mg/L and >70% for intermediate MIC of 8 mg/L). Our PBPK model can be an effective tool to support dosing recommendations in pediatric patients with different degrees of renal impairment.

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.

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.

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.

Combinations of common SNPs of the transporter gene ABCB1 influence apparent bioavailability, but not renal elimination of oral digoxin

Effects of different genotypes on the pharmacokinetics of probe substrates may support their use as phenotyping agents for the activity of the respective enzyme or transporter. Digoxin is recommended as a probe substrate to assess the activity of the transporter P-glycoprotein (P-gp) in humans. Current studies on the individual effects of three commonly investigated single nucleotide polymorphisms (SNPs) of the ABCB1 gene encoding P-gp (C1236T, G2677T/A, and C3435T) on digoxin pharmacokinetics are inconclusive. Since SNPs are in incomplete linkage disequilibrium, considering combinations of these SNPs might be necessary to assess the role of polymorphisms in digoxin pharmacokinetics accurately. In this study, the relationship between SNP combinations and digoxin pharmacokinetics was explored via a population pharmacokinetic approach in 40 volunteers who received oral doses of 0.5 mg digoxin. Concerning the SNPs 1236/2677/3435, the following combinations were evaluated: CGC, CGT, and TTT. Carriers of CGC/CGT and TTT/TTT had 35% higher apparent bioavailability compared to the reference group CGC/CGC, while no difference was seen in CGC/TTT carriers. No significant effect on renal clearance was observed. The population pharmacokinetic model supports the use of oral digoxin as a phenotyping substrate of intestinal P-gp, but not to assess renal P-gp activity.

Assessing Potential Drug-Drug Interactions Between Dabigatran Etexilate and a P-Glycoprotein Inhibitor in Renal Impairment Populations Using Physiologically Based Pharmacokinetic Modeling

Plasma concentrations of dabigatran, an active principle of prodrug dabigatran etexilate (DABE), are increased by renal impairment (RI) or coadministration of a P‐glycoprotein inhibitor. Because the combined effects of drug–drug interactions and RI have not been evaluated by means of clinical studies, the decision of DABE dosing for RI patients receiving P‐glycoprotein inhibitors is empirical at its best. We conducted virtual drug–drug interactions studies between DABE and the P‐glycoprotein inhibitor verapamil in RI populations using physiologically based pharmacokinetic modeling. The developed physiologically based pharmacokinetic model for DABE and dabigatran was used to predict trough dabigatran concentrations in the presence and absence of verapamil in virtual RI populations. The population‐based physiologically based pharmacokinetic model provided the most appropriate dosing regimen of DABE for likely clinical scenarios, such as drug–drug interactions in this RI population based on available knowledge of the systems changes and in the absence of actual clinical studies.

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.

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.

Using PBPK Modeling to Predict Drug Exposure and Support Dosage Adjustments in Patients With Renal Impairment: An Example with Lamivudine

BACKGROUND

Lamivudine is a nucleoside reverse transcriptase inhibitor used to treat HIV and hepatitis B. It is primarily cleared by the kidney with renal secretion mediated by OCT2 and MATE.

OBJECTIVE

To use PBPK modeling to assess the impact of renal impairment on lamivudine pharmacokinetics using the Simcyp® Simulator.

METHODS

The model incorporated the Simcyp® Mechanistic Kidney Model option to predict renal disposition. The model was initially verified using the Simcyp® Healthy Volunteer population. Two discrete patient populations were then created for moderate (GFR 10-40 mL/min) and severe (GFR < 10 mL/min) renal failure (RF), and model simulations were compared to published data. The developed model was then utilized in a clinical study evaluating the clinical experience and plasma exposure of lamivudine when administered at higher than recommended doses to HIV-infected patients with varying degrees of renal impairment.

RESULTS

Predicted systemic exposure metrics (Cmax, AUC) compared favorably to published clinical data for each population, with the following fold errors (FE, ratio of predicted and observed data) for Cmax/AUC: Healthy Volunteers 1.04/1.04, Moderate RF 1.03/0.78, Severe RF 0.89/0.79. The model captured lamivudine plasma concentrations measured pre- and post-dose (0.5-1.5hr) in study participants (n = 34). Model simulations demonstrated comparable systemic profiles across patient cohorts, supporting the proposed dosage adjustment scheme.

CONCLUSION

This study illustrates how PBPK modeling can help verify dosing guidelines for patients with varying levels of renal impairment. This approach may also be useful for predicting potential changes in exposure during renal insufficiency for compounds undergoing clinical development.

Individualized medication of digoxin based on the serum drug concentration and blood biochemical indexes

Aim: The dose of digoxin is often difficult to be determined precisely. The aim of this study was to retrospectively investigate the effect of blood biochemical indexes on the serum concentration of digoxin. Materials & methods: We collected the data of hospitalized patients treated orally with digoxin in Nanjing Drum Tower Hospital (Nanjing, China) from 2016 to 2018. Descriptive statistics was used to analyze the patients' comprehensive condition. Results: A total of 425 patients were included in the study. Through analysis, nine factors were included in the regression model of the serum concentration of digoxin, and this regression model showed good predictive performance (r² = 0.83138; p < 0.001). Conclusion: The regression model for the prediction of serum concentration of digoxin has clinical significance, and can provide research basis for individualized medication of digoxin.

Quantitative Translation of Microfluidic Transporter in Vitro Data to in Vivo Reveals Impaired Albumin-Facilitated Indoxyl Sulfate Secretion in Chronic Kidney Disease

Indoxyl sulfate (IxS), a highly albumin-bound uremic solute, accumulates in chronic kidney disease (CKD) due to reduced renal clearance. This study was designed to specifically investigate the role of human serum albumin (HSA) in IxS renal secretion via organic anion transporter 1 (OAT1) in a microfluidic system and subsequently apply quantitative translation of in vitro data to predict extent of change in IxS renal clearance in CKD stage IV relative to healthy. Conditionally immortalized human proximal tubule epithelial cells overexpressing OAT1 were incubated with IxS (5-200 μM) in the HSA-free medium or in the presence of either HSA or CKD-modified HSA. IxS uptake in the presence of HSA resulted in more than 20-fold decrease in OAT1 affinity (K_m,u) and 37-fold greater in vitro unbound intrinsic clearance (CL_int,u) versus albumin-free condition. In the presence of CKD-modified albumin, K_m,u increased four-fold and IxS CL_int,u decreased almost seven-fold relative to HSA. Fold-change in parameters exceeded differences in IxS binding between albumin conditions, indicating additional mechanism and facilitating role of albumin in IxS OAT1-mediated uptake. Quantitative translation of IxS in vitro OAT1-mediated CL_int,u predicted a 60% decrease in IxS renal elimination as a result of CKD, in agreement with the observed data (80%). The findings of the current study emphasize the role of albumin in IxS transport via OAT1 and explored the impact of modifications in albumin on renal excretion via active secretion in CKD. For the first time, this study performed quantitative translation of transporter kinetic data generated in a novel microfluidic in vitro system to a clinically relevant setting. Knowledge gaps and future directions in quantitative translation of renal drug disposition from microphysiological systems are discussed.

Impact of reduced P-glycoprotein function on digoxin concentrations in patients with dementia

AIMS

Patients with Alzheimer's disease (AD), the most common form of dementia, have reduced P-glycoprotein (P-gp) function at the blood-brain barrier. However, the effect of AD on P-gp function in peripheral organs, and the impact on medication efficacy and toxicity is unknown. In this study, clinical chart review and physiologically based pharmacokinetic (PBPK) modelling were employed to determine whether disease-associated changes in P-gp could be assessed from clinically measured digoxin concentrations in patients without and with dementia.

METHODS

A retrospective chart review was conducted to compare digoxin dose and concentrations between cohorts. A PBPK model was developed to simulate changes in digoxin concentrations at single and multiple 62.5 and 125 μg/d doses due to reduced P-gp function in peripheral organs.

RESULTS

Digoxin concentrations were similar between the nondementia (n = 75) and dementia (n = 72) cohorts (mean ± standard deviation; 0.64 ± 0.31 and 0.60 ± 0.34 ng/mL, respectively; -0.06 to 0.15, 95% confidence interval of difference). PBPK simulations showed that reduced P-gp function resulted in a significant increase in digoxin exposure (AUC), but not in C_max . For example, when a 2-fold reduction in P-gp function was simulated in older people following multiple 125 μg/d digoxin doses, the AUC over the last dosing interval was increased compared to baseline (24.29 ± 3.94 vs 17.04 ± 3.46 ng/mL*h; 4.52 to 9.98); however, C_max was similar (1.38 ± 0.20 vs 0.99 ± 0.18 ng/mL; -2.33 to 3.13).

CONCLUSION

Clinically measured digoxin concentrations were not statistically different in patients with dementia. Based on PBPK simulations, digoxin AUC may need to be evaluated to adequately assess the impact of reduced P-gp function in peripheral organs.

Evaluation of a Potential Clinical Significant Drug-Drug Interaction between Digoxin and Bupropion in Cynomolgus Monkeys

PURPOSE

A three-period digoxin-bupropion drug-drug interaction study was performed in cynomolgus monkeys to assess the effect of bupropion and its metabolites on digoxin disposition.

METHODS

Monkeys were administered either an i.v. infusion (0.1 mg/kg) or an oral dose of digoxin (0.2 mg/kg) as control. In single-dosing period, monkeys received an i.v. infusion of bupropion at 1.5 mg/kg together with an infusion or oral dosing of digoxin, respectively. During multiple-dosing period, bupropion was orally administered q.d. at 7.72 mg/kg for 12-day. Then it was co-administered with an i.v. infusion or oral dosing of digoxin, respectively. Renal expression of OATP4C1 and P-gp was examined.

RESULTS

Bupropion significantly increased i.v. digoxin CL_renal0-48h by 1 fold in single-dosing period. But it had no effect on the systemic disposition of digoxin. In multiple-dosing period, bupropion significantly increased oral digoxin CL_renal0-48h, CL_total0-48h, CL_{non-renal0-48h} and decreased its plasma exposure. Bupropion and its metabolites did not alter creatinine clearance. OATP4C1 was located at the basolateral membrane of proximal tubule cells, while P-gp was on the apical membrane.

CONCLUSIONS

The effect of multiple dosing with bupropion on the pharmacokinetics of digoxin is more pronounced. The magnitude of increase in digoxin CL_renal0-48h contributed to the decrease in AUC of digoxin in some extent, but certainly is not the major driving force. The lack of systemic exposure after a single dose but a significant decrease in exposure mediated by an increase in the digoxin CL_{non-renal0-48h} with repeated dosing is likely to be the more clinically relevant.

Advancing Predictions of Tissue and Intracellular Drug Concentrations Using In Vitro, Imaging and Physiologically Based Pharmacokinetic Modeling Approaches

This white paper examines recent progress, applications, and challenges in predicting unbound and total tissue and intra/subcellular drug concentrations using in vitro and preclinical models, imaging techniques, and physiologically based pharmacokinetic (PBPK) modeling. Published examples, regulatory submissions, and case studies illustrate the application of different types of data in drug development to support modeling and decision making for compounds with transporter-mediated disposition, and likely disconnects between tissue and systemic drug exposure. The goals of this article are to illustrate current best practices and outline practical strategies for selecting appropriate in vitro and in vivo experimental methods to estimate or predict tissue and plasma concentrations, and to use these data in the application of PBPK modeling for human pharmacokinetic (PK), efficacy, and safety assessment in drug development.

Physiologically Based Pharmacokinetic Modeling in Regulatory Science: An Update From the U.S. Food and Drug Administration's Office of Clinical Pharmacology

This commentary provides an update on the status of physiologically based pharmacokinetic modeling and simulation at the U.S. Food and Drug Administration's Office of Clinical Pharmacology. Limitations and knowledge gaps in integration of physiologically based pharmacokinetic approach to inform regulatory decision making, as well as the importance of scientific engagement with drug developers who intend to use this approach, are highlighted.

Use of Physiologically Based Pharmacokinetic Modeling to Evaluate the Effect of Chronic Kidney Disease on the Disposition of Hepatic CYP2C8 and OATP1B Drug Substrates

Chronic kidney disease (CKD) differentially affects the pharmacokinetics (PK) of nonrenally cleared drugs via certain pathways (e.g., cytochrome P450 (CYP)2D6); however, the effect on CYP2C8‐mediated clearance is not well understood because of overlapping substrate specificity with hepatic organic anion‐transporting polypeptides (OATPs). This study used physiologically based pharmacokinetic (PBPK) modeling to delineate potential changes in CYP2C8 or OATP1B activity in patients with CKD. Drugs analyzed are predominantly substrates of CYP2C8 (rosiglitazone and pioglitazone), OATP1B (pitavastatin), or both (repaglinide). Following initial model verification, pharmacokinetics (PK) of these drugs were simulated in patients with severe CKD considering changes in glomerular filtration rate (GFR), plasma protein binding, and activity of either CYP2C8 and/or OATP1B in a stepwise manner. The PBPK analysis suggests that OATP1B activity could be decreased up to 60% in severe CKD, whereas changes to CYP2C8 are negligible. This improved understanding of CKD effect on clearance pathways could be important to inform the optimal use of nonrenally eliminated drugs in patients with CKD.

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.

Development of a Dynamic Physiologically Based Mechanistic Kidney Model to Predict Renal Clearance

Renal clearance is usually predicted via empirical approaches including quantitative structure activity relationship and allometric scaling. Recently, mechanistic prediction approaches using in silico kidney models have been proposed. However, empirical scaling factors are typically used to adjust for either passive diffusion or active secretion, to acceptably predict renal clearances. The goal of this study was to establish a renal clearance simulation tool that allows prediction of renal clearance (filtration and pH-dependent passive reabsorption) from in vitro permeability data. A 35-compartment physiologically based mechanistic kidney model was developed based on human physiology. The model was verified using 46 test compounds, including neutrals, acids, bases, and zwitterions. The feasibility of incorporating active secretion and pH-dependent bidirectional passive diffusion into the model was demonstrated using para-aminohippuric acid (PAH), cimetidine, memantine, and salicylic acid. The developed model enables simulation of renal clearance from in vitro permeability data, with predicted renal clearance within twofold of observed for 87% of the test drugs.

Transporters in Drug Development: 2018 ITC Recommendations for Transporters of Emerging Clinical Importance

This white paper provides updated International Transporter Consortium (ITC) recommendations on transporters that are important in drug development following the 3^rd ITC workshop. New additions include prospective evaluation of organic cation transporter 1 (OCT1) and retrospective evaluation of organic anion transporting polypeptide (OATP)2B1 because of their important roles in drug absorption, disposition, and effects. For the first time, the ITC underscores the importance of transporters involved in drug-induced vitamin deficiency (THTR2) and those involved in the disposition of biomarkers of organ function (OAT2 and bile acid transporters).

Reverse Translation in PBPK and QSP: Going Backwards in Order to Go Forward With Confidence

Significant events have taken place shaping the recent industrialization of physiologically based pharmacokinetic in vitro-in vivo extrapolation (PBPK-IVIVE) use in drug development. Due to our knowledge gaps about drug-independent systems parameters, there are limitations in the use of purely IVIVE-based (bottom-up) approaches. This has encouraged combining the classical data analysis (top-down) with PBPK-IVIVE-linked models in order to optimize model parameters by taking advantage of observed clinical data. This concept, when initiated after clinical observations, can be viewed as "reverse translation," since it refers back to available systems information preclinical data before trying to describe the observations. This review demonstrates the advantages of such strategies in filling knowledge gaps and discusses the perceived hurdles in widening applications. It is paramount that no clinical data are assessed on their own, but in conjunction with other studies for that drug in different populations and/or other similar drugs in the same population.

Potential Drug Interactions Mediated by Renal Organic Anion Transporter OATP4C1

Organic anion-transporting polypeptide 4C1 (OATP4C1) is an organic anion transporter expressed in the basolateral membrane of the renal proximal tubules. It plays a major role in the urinary excretion of both exogenous drugs and endogenous compounds. Our previous studies have indicated the importance of OATP4C1 in pathologic and physiologic conditions; however, the majority of its pharmacologic characteristics remained unclear. Therefore, to provide essential information for clinical drug therapy decisions and drug development, we clarified drug interactions mediated by OATP4C1. To elucidate potential drug interactions via OATP4C1, we screened 53 representative drugs commonly used in clinical settings. Next, we evaluated the IC₅₀ values of drugs that inhibited OATP4C1 by more than 50%. To apply our results to clinical settings, we calculated the drug-drug interaction (DDI) indices. The screening analysis using an OATP4C1-expressing cell system demonstrated that 22 out of 53 therapeutic drugs inhibited OATP4C1-mediated triiodothyronine transport. In particular, OATP4C1-mediated transport was strongly inhibited by 10 drugs. The IC₅₀ values of 10 drugs-nicardipine, spironolactone, fluvastatin, crizotinib, levofloxacin, clarithromycin, ritonavir, saquinavir, quinidine, and verapamil-obtained in this study were 51, 53, 41, 24, 420, 200, 8.5, 4.3, 100, and 110 µM, respectively. The IC₅₀ values of these drugs were higher than the plasma concentrations obtained in clinical practice. However, ritonavir showed the highest DDI index (1.9) for OATP4C1, suggesting that it may strongly influence this transporter and thus cause drug interactions seen in clinical settings. Our finding gives new insight into the role of OATP4C1 in clinical DDIs.

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.