Facing the Facts of Altered Plasma Protein Binding: Do Current Models Correctly Predict Changes in Fraction Unbound in Special Populations?

Accounting for variability in plasma protein binding of drugs is an essential input to physiologically-based pharmacokinetic (PBPK) models of special populations. Prediction of fraction unbound in plasma (fu) in such populations typically considers changes in plasma protein concentration while assuming that the binding affinity remains unchanged. A good correlation between predicted vs observed fu data reported for various drugs in a given special population is often used as a justification for such predictive methods. However, none of these analyses evaluated the prediction of the fold-change in fu in special populations relative to the reference population. This would be a more appropriate assessment of the predictivity, analogous to drug-drug interactions. In this study, predictive performance of the single protein binding model was assessed by predicting fu for alpha-1-acid glycoprotein and albumin bound drugs in hepatic impairment, renal impairment, paediatric, elderly, patients with inflammatory disease, and in different ethnic groups for a dataset of >200 drugs. For albumin models, the concordance correlation coefficients for predicted fu were >0.90 for 16 out of 17 populations with sub-groups, indicating strong agreement between predicted and observed values. In contrast, concordance correlation coefficients for predicted fold-change in fu for the same dataset were <0.38 for all populations and sub-groups. Trends were similar for alpha-1-acid glycoprotein models. Accordingly, the predictions of fu solely based on changes in protein concentrations in plasma cannot explain the observed values in some special populations. We recommend further consideration of the impact of changes in special populations to endogenous substances that competitively bind to plasma proteins, and changes in albumin structure due to posttranslational modifications. PBPK models of special populations for highly bound drugs should preferably use measured fu data to ensure reliable prediction of drug exposure or compare predicted unbound drug exposure between populations knowing that these will not be sensitive to changes in fu.

Dealing With Variable Drug Exposure Due to Variable Hepatic Metabolism: A Proof-of-Concept Application of Liquid Biopsy in Renal Impairment

Precision dosing strategies require accounting for between-patient variability in pharmacokinetics (PK), affecting drug exposure, and in pharmacodynamics (PD), affecting response achieved at the same drug concentration at the site of action. Although liquid biopsy for assessing different levels of molecular drug targets has yet to be established, individual characterization of drug elimination pathways using liquid biopsy has recently been demonstrated. The feasibility of applying this approach in conjunction with modeling tools to guide individual dosing remains unexplored. In this study, we aimed to individualize physiologically-based pharmacokinetic (PBPK) models based on liquid biopsy measurements in plasma from 25 donors with different grades of renal function who were previously administered oral midazolam as part of a microdose cocktail. Virtual twin models were constructed based on demographics, renal function, and hepatic expression of relevant pharmacokinetic pathways projected from liquid biopsy output. Simulated exposure (AUC) to midazolam was in agreement with observed data (AFE = 1.38, AAFE = 1.78). Simulated AUC variability with three dosing approaches indicated higher variability with uniform dosing (14-fold) and stratified dosing (13-fold) compared with individualized dosing informed by liquid biopsy (fivefold). Further, exosome screening revealed mRNA expression of 532 targets relevant to drug metabolism and disposition (169 enzymes and 361 transporters). Data related to these targets can be used to further individualize PBPK models for pathways relevant to PK of other drugs. This study provides additional verification of liquid biopsy-informed PBPK modeling approaches, necessary to advance strategies that seek to achieve precise dosing from the start of treatment.

In silico modeling and simulation of organ-on-a-chip systems to support data analysis and a priori experimental design

Organ-on-a-chip (OoC) systems are a promising new class of in vitro devices that can combine various tissues, cultured in different compartments, linked by media flow. The properties of these novel in vitro systems linked to increased physiological relevance of culture conditions may lead to more in vivo-relevant cell phenotypes, enabling better in vitro pharmacology and toxicology assessment. Improved cell activities combined with longer lasting cultures offer opportunities to improve the characterization of absorption, distribution, metabolism, and excretion (ADME) processes, potentially leading to more accurate prediction of human pharmacokinetics (PKs). The inclusion of barrier tissue elements and metabolically competent tissue types results in complex concentration-time profiles (in vitro PK) for test drugs and their metabolites that require appropriate mathematical modeling of in vitro data for parameter estimation. In particular, modeling is critical to estimate in vitro ADME parameters when multiple different tissues are combined in a single device. Therefore, sophisticated in silico data analysis and a priori experimental design are highly recommended for OoC experiments in a manner not needed with standard ADME screening. The design of the experiment should be optimized based on an investigation of the structural characteristics of the in vitro system, the ADME features of the test compound and any available knowledge of cell phenotypes. This tutorial aims to provide such a modeling framework to inform experimental design and refine parameter estimation in a Gut-Liver OoC (the most studied multi-organ systems to predict the oral drug PKs) to improve translatability of data generated in such complex cellular systems.

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.

Evaluating drug-drug interaction risk associated with peptide analogues using advanced in vitro systems

Drug-drug interaction (DDI) assessment of therapeutic peptides is an evolving area. The industry generally follows DDI guidelines for small molecules, but the translation of data generated with commonly used in vitro systems to in vivo is sparse. In the current study, we investigated the ability of advanced human hepatocyte in vitro systems namely HepatoPac, spheroids, and Liver-on-a-chip to assess potential changes in regulation of CYP1A2, CYP2B6, CYP3A4, SLCO1B1 and ABCC2 in the presence of selected therapeutic peptides, proteins, and small molecules. The peptide NN1177, a glucagon and GLP-1 receptor co-agonist, did not suppress mRNA expression or activity of CYP1A2, CYP2B6, and CYP3A4 in HepatoPac, spheroids, or Liver-on-a-chip; these findings were in contrast to the data obtained in sandwich cultured hepatocytes. No effect of NN1177 on SLCO1B1 and ABCC2 mRNA was observed in any of the complex systems. The induction magnitude differed across the systems (e.g., rifampicin induction of CYP3A4 mRNA ranged from 2.8-fold in spheroids to 81.2-fold in Liver-on-a-chip). Small molecules, obeticholic acid and abemaciclib, showed varying responses in HepatoPac, spheroids and Liver-on-a-chip, indicating a need for EC50 determinations to fully assess translatability data. HepatoPac, the most extensively investigated in this study (3 donors), showed high potential to investigate DDIs associated with CYP regulation by therapeutic peptides. Spheroids and Liver-on-a-chip were only assessed in one hepatocyte donor and further evaluations are required to confirm their potential. This study establishes an excellent foundation towards the establishment of more clinically-relevant in vitro tools for evaluation of potential DDIs with therapeutic peptides. Significance Statement At present, there are no guidelines for drug-drug interaction (DDI) assessment of therapeutic peptides. Existing in vitro methods recommended for assessing small molecule DDIs do not appear to translate well for peptide drugs, complicating drug development for these moieties. Here, we establish evidence that complex cellular systems have potential to be used as more clinically-relevant tools for the in vitro DDI evaluation of therapeutic peptides.

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.

Challenges and Opportunities for In Vitro-In Vivo Extrapolation of Aldehyde Oxidase-Mediated Clearance: Toward a Roadmap for Quantitative Translation

Underestimation of aldehyde oxidase (AO)-mediated clearance by current in vitro assays leads to uncertainty in human dose projections, thereby reducing the likelihood of success in drug development. In the present study we first evaluated the current drug development practices for AO substrates. Next, the overall predictive performance of in vitro-in vivo extrapolation of unbound hepatic intrinsic clearance (CLint,u) and unbound hepatic intrinsic clearance by AO (CLint,u,AO) was assessed using a comprehensive literature database of in vitro (human cytosol/S9/hepatocytes) and in vivo (intravenous/oral) data collated for 22 AO substrates (total of 100 datapoints from multiple studies). Correction for unbound fraction in the incubation was done by experimental data or in silico predictions. The fraction metabolized by AO (fmAO) determined via in vitro/in vivo approaches was found to be highly variable. The geometric mean fold errors (gmfe) for scaled CLint,u (mL/min/kg) were 10.4 for human hepatocytes, 5.6 for human liver cytosols, and 5.0 for human liver S9, respectively. Application of these gmfe's as empirical scaling factors improved predictions (45%-57% within twofold of observed) compared with no correction (11%-27% within twofold), with the scaling factors qualified by leave-one-out cross-validation. A road map for quantitative translation was then proposed following a critical evaluation on the in vitro and clinical methodology to estimate in vivo fmAO In conclusion, the study provides the most robust system-specific empirical scaling factors to date as a pragmatic approach for the prediction of in vivo CLint,u,AO in the early stages of drug development. SIGNIFICANCE STATEMENT: Confidence remains low when predicting in vivo clearance of AO substrates using in vitro systems, leading to de-prioritization of AO substrates from the drug development pipeline to mitigate risk of unexpected and costly in vivo impact. The current study establishes a set of empirical scaling factors as a pragmatic tool to improve predictability of in vivo AO clearance. Developing clinical pharmacology strategies for AO substrates by utilizing mass balance/clinical drug-drug interaction data will help build confidence in fmAO.

Estimation of FMO3 Ontogeny by Mechanistic Population Pharmacokinetic Modelling of Risdiplam and Its Impact on Drug-Drug Interactions in Children

BACKGROUND AND OBJECTIVE

Spinal muscular atrophy (SMA) is a progressive neuromuscular disease caused by insufficient levels of survival motor neuron (SMN) protein. Risdiplam (EvrysdiTM) increases SMN protein and is approved for the treatment of SMA. Risdiplam has high oral bioavailability and is primarily eliminated through hepatic metabolism by flavin-containing monooxygenase3 (FMO3) and cytochrome P450 (CYP) 3A, by 75% and 20%, respectively. While the FMO3 ontogeny is critical input data for the prediction of risdiplam pharmacokinetics (PK) in children, it was mostly studied in vitro, and robust in vivo FMO3 ontogeny is currently lacking. We derived in vivo FMO3 ontogeny by mechanistic population PK modelling of risdiplam and investigated its impact on drug-drug interactions in children.

METHODS

Population and physiologically based PK (PPK and PBPK) modelling conducted during the development of risdiplam were integrated into a mechanistic PPK (Mech-PPK) model to estimate in vivo FMO3 ontogeny. A total of 10,205 risdiplam plasma concentration-time data from 525 subjects aged 2 months-61 years were included. Six different structural models were examined to describe the in vivo FMO3 ontogeny. Impact of the newly estimated FMO3 ontogeny on predictions of drug-drug interaction (DDI) in children was investigated by simulations for dual CYP3A-FMO3 substrates including risdiplam and theoretical substrates covering a range of metabolic fractions (fm) of CYP3A and FMO3 (fmCYP3A:fmFMO3 = 10%:90%, 50%:50%, 90%:10%).

RESULTS

All six models consistently predicted higher FMO3 expression/activity in children, reaching a maximum at the age of 2 years with an approximately threefold difference compared with adults. Different trajectories of FMO3 ontogeny in infants < 4 months of age were predicted by the six models, likely due to limited observations for this age range. Use of this  in vivo FMO3 ontogeny function improved prediction of risdiplam PK in children compared to in vitro FMO3 ontogeny functions. The simulations of theoretical dual CYP3A-FMO3 substrates predicted comparable or decreased CYP3A-victim DDI propensity in children compared to adults across the range of fm values. Refinement of FMO3 ontogeny in the risdiplam model had no impact on the previously predicted low CYP3A-victim or -perpetrator DDI risk of risdiplam in children.

CONCLUSION

Mech-PPK modelling successfully estimated in vivo FMO3 ontogeny from risdiplam data collected from 525 subjects aged 2 months-61 years. To our knowledge, this is the first investigation of in vivo FMO3 ontogeny by population approach using comprehensive data covering a wide age range. Derivation of a robust in vivo FMO3 ontogeny function has significant implications on the prospective prediction of PK and DDI in children for other FMO3 substrates in the future, as illustrated in the current study for FMO3 and/or dual CYP3A-FMO3 substrates.

CLINICAL TRIAL REGISTRY NUMBERS

NCT02633709, NCT03032172, NCT02908685, NCT02913482, NCT03988907.

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.

Application of a gut-liver-on-a-chip device and mechanistic modelling to the quantitative in vitro pharmacokinetic study of mycophenolate mofetil

Microphysiological systems (MPS) consisting of multiple linked organ-on-a-chip (OoC) components are highly promising tools with potential to provide more relevant in vitro to in vivo translation of drug disposition, efficacy and toxicity. A gut-liver OoC system was employed with Caco2 cells in co-culture with HT29 cells in the intestinal compartment and single donor primary hepatocytes in the hepatic compartment for the investigation of intestinal permeability, metabolism (intestinal and hepatic) and potential interplay of those processes. The prodrug mycophenolate mofetil was tested for quantitative evaluation of the gut-liver OoC due to the contribution of both gut and liver in its metabolism. Conversion of mycophenolate mofetil to active drug mycophenolic acid and further metabolism to a glucuronide metabolite was assessed over time in the gut apical, gut basolateral and liver compartments. Mechanistic modelling of experimental data was performed to estimate clearance and permeability parameters for the prodrug, active drug and glucuronide metabolite. Integration of gut-liver OoC data with in silico modelling allowed investigation of the complex combination of intestinal and hepatic processes, which is not possible with standard single tissue in vitro systems. A comprehensive evaluation of the mechanistic model, including structural model and parameter identifiability and global sensitivity analysis, enabled a robust experimental design and estimation of in vitro pharmacokinetic parameters. We propose that similar methodologies may be applied to other multi-organ microphysiological systems used for drug metabolism studies or wherever quantitative knowledge of changing drug concentration with time enables better understanding of biological effect.

Coproporphyrin I as an Endogenous Biomarker to Detect Reduced OATP1B Activity and Shift in Elimination Route in Chronic Kidney Disease

Coproporphyrin I (CPI) is an endogenous biomarker of organic anion transporting polypeptide 1B transporter (OATP1B). CPI plasma baseline was reported to increase with severity of chronic kidney disease (CKD). Further, ratio of CPI area under the plasma concentration-time curve (AUCR) in the presence/absence of OATP1B inhibitor rifampin was higher in patients with CKD compared with healthy participants, in contrast to pitavastatin (a clinical OATP1B probe). This study investigated mechanism(s) contributing to altered CPI baseline in patients with CKD by extending a previously developed physiologically-based pharmacokinetic (PBPK) model to this patient population. CKD-related covariates were evaluated in a stepwise manner on CPI fraction unbound in plasma (f_u,p ), OATP1B-mediated hepatic uptake clearance (CL_active ), renal clearance (CL_R ), and endogenous synthesis (k_syn ). The CPI model successfully recovered increased baseline and rifampin-mediated AUCR in patients with CKD by accounting for the following disease-related changes: 13% increase in f_u,p , 29% and 39% decrease in CL_active in mild and moderate to severe CKD, respectively, decrease in CL_R proportional to decline in glomerular filtration rate, and 27% decrease in k_syn in severe CKD. Almost complete decline in CPI renal elimination in severe CKD increased its fraction transported by OATP1B, rationalizing differences in the CPI-rifampin interaction observed between healthy participants and patients with CKD. In conclusion, mechanistic modeling performed here supports CKD-related decrease in OATP1B function to inform prospective PBPK modeling of OATP1B-mediated drug-drug interaction in these patients. Monitoring of CPI allows detection of CKD-drug interaction risk for OATP1B drugs with combined hepatic and renal elimination which may be underestimated by extrapolating the interaction risk based on pitavastatin data in healthy participants.

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.

Exploration and application of a liver-on-a-chip device in combination with modelling and simulation for quantitative drug metabolism studies

Microphysiological systems (MPS) are complex and more physiologically realistic cellular in vitro tools that aim to provide more relevant human in vitro data for quantitative prediction of clinical pharmacokinetics while also reducing the need for animal testing. The PhysioMimix liver-on-a-chip integrates medium flow with hepatocyte culture and has the potential to be adopted for in vitro studies investigating the hepatic disposition characteristics of drug candidates. The current study focusses on liver-on-a-chip system exploration for multiple drug metabolism applications. Characterization of cytochrome P450 (CYP), UDP-glucuronosyl transferase (UGT) and aldehyde oxidase (AO) activities was performed using 15 drugs and in vitro to in vivo extrapolation (IVIVE) was assessed for 12 of them. Next, the utility of the liver-on-a-chip for estimation of the fraction metabolized (f_m) via specific biotransformation pathways of quinidine and diclofenac was established. Finally, the metabolite identification opportunities were also explored using efavirenz as an example drug with complex primary and secondary metabolism involving a combination of CYP, UGT and sulfotransferase enzymes. A key aspect of these investigations was the application of mathematical modelling for improved parameter calculation. Such approaches will be required for quantitative assessment of metabolism and/or transporter processes in systems where medium flow and system compartments result in non-homogeneous drug concentrations. In particular, modelling was used to explore the effect of evaporation from the medium and it was found that the intrinsic clearance (CL_int) might be underestimated by up to 40% for low clearance compounds if evaporation is not accounted for. Modelling of liver-on-a-chip in vitro data also enhanced the approach to f_m estimation allowing objective assessment of metabolism models of different complexity. The resultant diclofenac f_m,UGT of 0.64 was highly comparable with values reported previously in the literature. The current study demonstrates the integration of mathematical modelling with experimental liver-on-a-chip studies and illustrates how this approach supports generation of high quality of data from complex in vitro cellular systems.

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.

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.

Model-Based Drug-Drug Interaction Extrapolation Strategy From Adults to Children: Risdiplam in Pediatric Patients With Spinal Muscular Atrophy

Risdiplam (Evrysdi) improves motor neuron function in patients with spinal muscular atrophy (SMA) and has been approved for the treatment of patients ≥2 months old. Risdiplam exhibits time‐dependent inhibition of cytochrome P450 (CYP) 3A in vitro. While many pediatric patients receive risdiplam, a drug–drug interaction (DDI) study in pediatric patients with SMA was not feasible. Therefore, a novel physiologically‐based pharmacokinetic (PBPK) model‐based strategy was proposed to extrapolate DDI risk from healthy adults to children with SMA in an iterative manner. A clinical DDI study was performed in healthy adults at relevant risdiplam exposures observed in children. Risdiplam caused an 1.11‐fold increase in the ratio of midazolam area under the curve with and without risdiplam (AUCR)), suggesting an 18‐fold lower in vivo CYP3A inactivation constant compared with the in vitro value. A pediatric PBPK model for risdiplam was validated with independent data and combined with a validated midazolam pediatric PBPK model to extrapolate DDI from adults to pediatric patients with SMA. The impact of selected intestinal and hepatic CYP3A ontogenies on the DDI susceptibility in children relative to adults was investigated. The PBPK analysis suggests that primary CYP3A inhibition by risdiplam occurs in the intestine rather than the liver. The PBPK‐predicted risdiplam CYP3A inhibition risk in pediatric patients with SMA aged 2 months–18 years was negligible (midazolam AUCR of 1.09–1.18) and included in the US prescribing information of risdiplam. Comprehensive evaluation of the sensitivity of predicted CYP3A DDI on selected intestinal and hepatic CYP3A ontogeny functions, together with PBPK model‐based strategy proposed here, aim to guide and facilitate DDI extrapolations in pediatric populations.

Physiologically Based Pharmacokinetic Modeling of Transporter-Mediated Hepatic Disposition of Imaging Biomarker Gadoxetate in Rats

Physiologically based pharmacokinetic (PBPK) models are increasingly used in drug development to simulate changes in both systemic and tissue exposures that arise as a result of changes in enzyme and/or transporter activity. Verification of these model-based simulations of tissue exposure is challenging in the case of transporter-mediated drug–drug interactions (tDDI), in particular as these may lead to differential effects on substrate exposure in plasma and tissues/organs of interest. Gadoxetate, a promising magnetic resonance imaging (MRI) contrast agent, is a substrate of organic-anion-transporting polypeptide 1B1 (OATP1B1) and multidrug resistance-associated protein 2 (MRP2). In this study, we developed a gadoxetate PBPK model and explored the use of liver-imaging data to achieve and refine in vitro–in vivo extrapolation (IVIVE) of gadoxetate hepatic transporter kinetic data. In addition, PBPK modeling was used to investigate gadoxetate hepatic tDDI with rifampicin i.v. 10 mg/kg. In vivo dynamic contrast-enhanced (DCE) MRI data of gadoxetate in rat blood, spleen, and liver were used in this analysis. Gadoxetate in vitro uptake kinetic data were generated in plated rat hepatocytes. Mean (%CV) in vitro hepatocyte uptake unbound Michaelis–Menten constant (K_m,u) of gadoxetate was 106 μM (17%) (n = 4 rats), and active saturable uptake accounted for 94% of total uptake into hepatocytes. PBPK–IVIVE of these data (bottom-up approach) captured reasonably systemic exposure, but underestimated the in vivo gadoxetate DCE–MRI profiles and elimination from the liver. Therefore, in vivo rat DCE–MRI liver data were subsequently used to refine gadoxetate transporter kinetic parameters in the PBPK model (top-down approach). Active uptake into the hepatocytes refined by the liver-imaging data was one order of magnitude higher than the one predicted by the IVIVE approach. Finally, the PBPK model was fitted to the gadoxetate DCE–MRI data (blood, spleen, and liver) obtained with and without coadministered rifampicin. Rifampicin was estimated to inhibit active uptake transport of gadoxetate into the liver by 96%. The current analysis highlighted the importance of gadoxetate liver data for PBPK model refinement, which was not feasible when using the blood data alone, as is common in PBPK modeling applications. The results of our study demonstrate the utility of organ-imaging data in evaluating and refining PBPK transporter IVIVE to support the subsequent model use for quantitative evaluation of hepatic tDDI.

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.

Population pharmacokinetic modeling and simulation to support qualification of pyridoxic acid as endogenous biomarker of OAT1/3 renal transporters

Renal clearance of many drugs is mediated by renal organic anion transporters OAT1/3 and inhibition of these transporters may lead to drug‐drug interactions (DDIs). Pyridoxic acid (PDA) and homovanillic acid (HVA) were indicated as potential biomarkers of OAT1/3. The objective of this study was to develop a population pharmacokinetic model for PDA and HVA to support biomarker qualification. Simultaneous fitting of biomarker plasma and urine data in the presence and absence of potent OAT1/3 inhibitor (probenecid, 500 mg every 6 h) was performed. The impact of study design (multiple vs. single dose of OAT1/3 inhibitor) and ability to detect interactions in the presence of weak/moderate OAT1/3 inhibitors was investigated, together with corresponding power calculations. The population models developed successfully described biomarker baseline and PDA/HVA OAT1/3‐mediated interaction data. No prominent effect of circadian rhythm on PDA and HVA individual baseline levels was evident. Renal elimination contributed greater than 80% to total clearance of both endogenous biomarkers investigated. Estimated probenecid unbound in vivo OAT inhibitory constant was up to 6.4‐fold lower than in vitro values obtained with PDA as a probe. The PDA model was successfully verified against independent literature reported datasets. No significant difference in power of DDI detection was found between multiple and single dose study design when using the same total daily dose of 2000 mg probenecid. Model‐based simulations and power calculations confirmed sensitivity and robustness of plasma PDA data to identify weak, moderate, and strong OAT1/3 inhibitors in an adequately powered clinical study to support optimal design of prospective clinical OAT1/3 interaction studies.

Clinical Investigation on Endogenous Biomarkers to Predict Strong OAT-Mediated Drug-Drug Interactions

BACKGROUND

Endogenous biomarkers are promising tools to assess transporter-mediated drug-drug interactions early in humans.

METHODS

We evaluated on a common and validated in vitro system the selectivity of 4-pyridoxic acid (PDA), homovanillic acid (HVA), glycochenodeoxycholate-3-sulphate (GCDCA-S) and taurine towards different renal transporters, including multidrug resistance-associated protein, and assessed the in vivo biomarker sensitivity towards the strong organic anion transporter (OAT) inhibitor probenecid at 500 mg every 6 h to reach close to complete OAT inhibition.

RESULTS

PDA and HVA were substrates of the OAT1/2/3, OAT4 (PDA only) and multidrug resistance-associated protein 4; GCDCA-S was more selective, having affinity only towards OAT3 and multidrug resistance-associated protein 2. Taurine was not a substrate of any of the investigated transporters under the in vitro conditions tested. Plasma exposure of PDA and HVA significantly increased and the renal clearance of GCDCA-S, PDA and HVA decreased; the magnitude of these changes was comparable to those of known clinical OAT probe substrates. PDA and GCDCA-S were the most promising endogenous biomarkers of the OAT pathway activity: PDA plasma exposure was the most sensitive to probenecid inhibition, and, in contrast, GCDCA-S was the most sensitive OAT biomarker based on renal clearance, with higher selectivity towards the OAT3 transporter.

CONCLUSIONS

The current findings illustrate a clear benefit of measuring PDA plasma exposure during phase I studies when a clinical drug candidate is suspected to be an OAT inhibitor based on in vitro data. Subsequently, combined monitoring of PDA and GCDCA-S in both urine and plasma is recommended to tease out the involvement of OAT1/3 in the inhibition interaction.

CLINICAL TRIAL REGISTRATION

EudraCT number: 2016-003923-49.

When special populations intersect with drug-drug interactions: Application of physiologically-based pharmacokinetic modeling in pregnant populations

Pregnancy results in significant physiological changes that vary across trimesters and into the postpartum period, and may result in altered disposition of endogenous substances and drug pharmacokinetics. Pregnancy represents a unique special population where physiologically-based pharmacokinetic modeling (PBPK) is well suited to mechanistically explore pharmacokinetics and dosing paradigms without subjecting pregnant women or their fetuses to extensive clinical studies. A critical review of applications of pregnancy PBPK models (pPBPK) was conducted to understand its current status for prediction of drug exposure in pregnant populations and to identify areas of further expansion. Evaluation of existing pPBPK modeling efforts highlighted improved understanding of cytochrome P450 (CYP)-mediated changes during pregnancy and identified knowledge gaps for non-CYP enzymes and the physiological changes of the postpartum period. Examples of the application of pPBPK beyond simple dose regimen recommendations are limited, particularly for prediction of drug-drug interactions (DDI) or differences between genotypes for polymorphic drug metabolizing enzymes. A raltegravir pPBPK model implementing UGT1A1 induction during the second and third trimesters of pregnancy was developed in the current work and verified against clinical data. Subsequently, the model was used to explore UGT1A1-related DDI risk with atazanavir and rifampicin along with the effect of enzyme genotype on raltegravir apparent clearance. Simulations of pregnancy-related induction of UGT1A1 either exacerbated UGT1A1 induction by rifampicin or negated atazanavir UGT1A1 inhibition. This example illustrated the advantages of pPBPK modeling for mechanistic evaluation of complex interplays of pregnancy- and drug-related effects in support of model-informed approaches in drug development.

PBPK Model of Coproporphyrin I: Evaluation of the Impact of SLCO1B1 Genotype, Ethnicity, and Sex on its Inter-Individual Variability

Coproporphyrin I (CPI) is an endogenous biomarker of OATP1B activity and associated drug-drug interactions. In this study, a minimal physiologically-based pharmacokinetic model was developed to investigate the impact of OATP1B1 genotype (c.521T>C), ethnicity, and sex on CPI pharmacokinetics and interindividual variability in its baseline. The model implemented mechanistic descriptions of CPI hepatic transport between liver blood and liver tissue and renal excretion. Key model parameters (e.g., endogenous CPI synthesis rate, and CPI hepatic uptake clearance) were estimated by fitting the model simultaneously to three independent CPI clinical datasets (plasma and urine data) obtained from white (n = 16, men and women) and Asian-Indian (n = 26, all men) subjects, with c.521 variants (TT, TC, and CC). The optimized CPI model successfully described the observed data using c.521T>C genotype, ethnicity, and sex as covariates. CPI hepatic active was 79% lower in 521CC relative to the wild type and 42% lower in Asian-Indians relative to white subjects, whereas CPI synthesis was 23% higher in male relative to female subjects. Parameter sensitivity analysis showed marginal impact of the assumption of CPI synthesis site (blood or liver), resulting in comparable recovery of plasma and urine CPI data. Lower magnitude of CPI-drug interaction was simulated in 521CC subjects, suggesting the risk of underestimation of CPI-drug interaction without prior OATP1B1 genotyping. The CPI model incorporates key covariates contributing to interindividual variability in its baseline and highlights the utility of the CPI modeling to facilitate the design of prospective clinical studies to maximize the sensitivity of this biomarker.

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.

Intestinal P-gp and Putative Hepatic OATP1B Induction: International Transporter Consortium Perspective on Drug Development Implications

There is an increasing interest in transporter induction (i.e., decreased systemic drug exposure due to increased efflux-limited absorption or transporter-mediated clearance) as a mechanism of drug-drug interactions (DDIs), although evidence of clinical relevance is still evolving. Intestinal P-glycoprotein (P-gp) and hepatic organic anion transporting polypeptides 1B (OATP1B) can be important determinants of drug absorption and disposition, as well as targets for DDIs. Current data indicate that intestinal P-gp protein levels can be induced up to threefold to fourfold in humans primarily with pregnane X receptor (PXR) activators, and that this induction can decrease the systemic exposure of drugs with P-gp efflux-limited absorption (e.g., ≤ 67% decrease in the exposure of total dabigatran following rifampin multiple oral dosing). Evaluation of the clinical relevance of P-gp induction as a DDI mechanism must consider the induction potential of the perpetrator drug for P-gp and attenuation of exposure of the victim drug in the context of its therapeutic window. Practical drug development recommendations are provided herein. Reports are contradictory on OATP1B induction by PXR activators in human hepatocytes and liver biopsies. Some clinical investigations demonstrated that rifampin pretreatment decreased exposure of OATP1B substrates, while other studies found no differences, and the potential involvement of other mechanisms in these observed DDIs cannot be definitively ruled out. Thus, further studies are needed to understand hepatic OATP1B induction and potential involvement of other mechanisms contributing to reduced exposure of OATP1B substrates. This review critically summarizes the state-of-the-art on intestinal P-gp and hepatic OATP1B induction, and highlights implications for drug development.

Utilising Magnetically Isolated Lysosomes for Direct Quantification of Intralysosomal Drug Concentrations by LC-MS/MS Analysis: An Investigatory Study With Imipramine

Lysosomes are acidic intracellular organelles that can extensively sequester basic lipophilic drugs due to pH and membrane partitioning, and therefore may significantly influence subcellular drug concentrations. Current in vitro methods for lysosomal drug sequestration evaluation typically lack the ability to accurately and sensitively quantify drug concentrations directly within the lysosome. In the current study, magnetic lysosomal isolation was used in the lysosome rich rat NR8383 cell line and combined with LC-MS/MS analysis to quantify intralysosomal concentrations and lysosomal partitioning (Kp_Lysosome) values of imipramine. The purity of the isolated lysosomes was validated by enzymatic and electron microscopy analysis. Lysosomal imipramine accumulation was explored using 2 methods: addition of imipramine to cells followed by lysosomal isolation (Method 1), and direct addition of imipramine to isolated lysosomes (Method 2). This work highlighted that both experimental buffers and ATP influence intralysosomal drug concentrations, and non-specific drug binding and re-distribution limits the use of Method 1. Method 2 may benefit future lysosomal drug accumulation studies, as imipramine demonstrated high Kp_Lysosome values (3500), comparable to in silico predictions. This study reports a novel method for the direct quantification of intralysosomal drug concentrations that has the ability to be adapted to other cell types.

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.

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.

A population pharmacokinetic model for simvastatin and its metabolites in children and adolescents

Purpose

Poor adherence to dietary/behaviour modifications as interventions for hypercholesterolemia in paediatric patients often necessitates the initiation of statin therapy. The aim of this study was to develop a joint population pharmacokinetic model for simvastatin and four metabolites in children and adolescents to investigate sources of variability in simvastatin acid exposure in this patient population, in addition to SLCO1B1 genotype status.

Methods

Plasma concentrations of simvastatin and its four metabolites, demographic and polymorphism data for OATP1B1 and CYP3A5 were analysed utilising a population pharmacokinetic modelling approach from an existing single oral dose (10 mg < 17 years and 20 mg ≥ 18 years) pharmacokinetic dataset of 32 children and adolescents.

Results

The population PK model included a one compartment disposition model for simvastatin with irregular oral absorption described by two parallel absorption processes each consisting of sequential zero and first-order processes. The data for each metabolite were described by a one-compartment disposition model with the formation and elimination apparent parameters estimated. The model confirmed the statistically significant effect of c.521T>C (rs4149056) on the pharmacokinetics of the active metabolite simvastatin acid in children/adolescents, consistent with adult data. In addition, age was identified as a covariate affecting elimination clearances of 6-hydroxymethyl simvastatin acid and 3, 5 dihydrodiol simvastatin metabolites.

Conclusion

The model developed describes the pharmacokinetics of simvastatin and its metabolites in children/adolescents capturing the effects of both c.521T>C and age on variability in exposure in this patient population. This joint simvastatin metabolite model is envisaged to facilitate optimisation of simvastatin dosing in children/adolescents.

Electronic supplementary material

The online version of this article (10.1007/s00228-019-02697-y) contains supplementary material, which is available to authorized users.

Hepatic Organic Anion Transporting Polypeptide-Mediated Clearance in the Beagle Dog: Assessing In Vitro-In Vivo Relationships and Applying Cross-Species Empirical Scaling Factors to Improve Prediction of Human Clearance

In the present study, the beagle dog was evaluated as a preclinical model to investigate organic anion transporting polypeptide (OATP)-mediated hepatic clearance. In vitro studies were performed with nine OATP substrates in three lots of plated male dog hepatocytes ± OATP inhibitor cocktail to determine total uptake clearance (CL_uptake) and total and unbound cell-to-medium concentration ratio (Kp_uu). In vivo intrinsic hepatic clearances (CL_int,H) were determined following intravenous drug administration (0.1 mg/kg) in male beagle dogs. The in vitro parameters were compared with those previously reported in plated human, monkey, and rat hepatocytes; the ability of cross-species scaling factors to improve prediction of human in vivo clearance was assessed. CL_uptake in dog hepatocytes ranged from 9.4 to 135 µl/min/10⁶ cells for fexofenadine and telmisartan, respectively. Active process contributed >75% to CL_uptake for 5/9 drugs. Rosuvastatin and valsartan showed Kp_uu > 10, whereas cerivastatin, pitavastatin, repaglinide, and telmisartan had Kp_uu < 5. The extent of hepatocellular binding in dog was consistent with other preclinical species and humans. The bias (2.73-fold) obtained from comparison of predicted versus in vivo dog CL_int,H was applied as an average empirical scaling factor (ESF_av) for in vitro-in vivo extrapolation of human CL_int,H The ESF_av based on dog reduced underprediction of human CL_int,H for the same data set (geometric mean fold error = 2.1), highlighting its utility as a preclinical model to investigate OATP-mediated uptake. The ESF_av from all preclinical species resulted in comparable improvement of human clearance prediction, in contrast to drug-specific empirical scalars, rationalized by species differences in expression and/or relative contribution of particular transporters to drug hepatic uptake.

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.

Comprehensive Evaluation of the Utility of 20 Endogenous Molecules as Biomarkers of OATP1B Inhibition Compared with Rosuvastatin and Coproporphyrin I

Endogenous biomarkers can be clinically relevant tools for the assessment of transporter function in vivo and corresponding drug-drug interactions (DDIs). The aim of this study was to perform systematic evaluation of plasma data obtained for 20 endogenous molecules in the same healthy subjects (n = 8-12) in the absence and presence of organic anion transporting polypeptide (OATP) inhibitor rifampicin (600 mg, single dose). The extent of rifampicin DDI magnitude [the ratio of the plasma concentration-time area under the curve (AUCR)], estimated fraction transported (f_T), and baseline variability was compared across the biomarkers and relative to rosuvastatin and coproporphyrin I (CPI). Out of the 20 biomarkers investigated tetradecanedioate (TDA), hexadecanedioate (HDA), glycocholic acid, glycodeoxycholic acid (GDCA), taurodeoxycholic acid (TDCA), and coproporphyrin III (CPIII) showed the high AUCR (2.1-8.5) and f_T (0.5-0.76) values, indicative of substantial OATP1B-mediated transport. A significant positive correlation was observed between the individual GDCA and TDCA AUCRs and the magnitude of rosuvastatin-rifampicin interaction. The CPI and CPIII AUCRs were significantly correlated, but no clear trend was established with the rosuvastatin AUCR. Moderate interindividual variability (15%-62%) in baseline exposure and AUCR was observed for TDA, HDA, and CPIII. In contrast, bile acids demonstrated high interindividual variability (69%-113%) and significant decreases in baseline plasma concentrations during the first 4 hours. This comprehensive analysis in the same individuals confirms that none of the biomarkers supersede CPI in the evaluation of OATP1B-mediated DDI risk. Monitoring of CPI and GDCA/TDCA may be beneficial for dual OATP1B/sodium-taurocholate cotransporting polypeptide inhibitors with consideration of challenges associated with large inter- and intraindividual variability observed for bile acids. Benefit of monitoring combined biomarkers (CPI, one bile acid and one fatty acid) needs to be confirmed with larger data sets and against multiple OATP1B clinical probes and perpetrators.

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.

Influence of Transporter Polymorphisms on Drug Disposition and Response: A Perspective From the International Transporter Consortium

Advances in genomic technologies have led to a wealth of information identifying genetic polymorphisms in membrane transporters, specifically how these polymorphisms affect drug disposition and response. This review describes the current perspective of the International Transporter Consortium (ITC) on clinically important polymorphisms in membrane transporters. ITC suggests that, in addition to previously recommended polymorphisms in ABCG2 (BCRP) and SLCO1B1 (OATP1B1), polymorphisms in the emerging transporter, SLC22A1 (OCT1), be considered during drug development. Collectively, polymorphisms in these transporters are important determinants of interindividual differences in the levels, toxicities, and response to many drugs.

ITC Commentary on Metformin Clinical Drug-Drug Interaction Study Design That Enables an Efficacy- and Safety-Based Dose Adjustment Decision

Metformin drug-drug interaction (DDI) studies are conducted during development of drugs that inhibit organic cation transporters and/or multidrug and toxin extrusion proteins (OCTs/MATEs). Monitoring solely changes in systemic exposure, the typical DDI study endpoint appears inadequate for metformin, which is metabolically stable, has poor passive membrane permeability, and undergoes transporter-mediated tissue distribution and clearance. Evaluation of renal clearance, antihyperglycemic effects, and potentially lactate as an exploratory safety marker, can support rational metformin dose adjustment. The proposed DDI study design aims to adequately inform metformin dosing during comedication.

In Vitro-In Vivo Extrapolation of OATP1B-Mediated Drug-Drug Interactions in Cynomolgus Monkey

Hepatic organic anion-transporting polypeptides (OATP) 1B1 and 1B3 are clinically relevant transporters associated with significant drug-drug interactions (DDIs) and safety concerns. Given that OATP1Bs in cynomolgus monkey share >90% degree of gene and amino acid sequence homology with human orthologs, we evaluated the in vitro-in vivo translation of OATP1B-mediated DDI risk using this preclinical model. In vitro studies using plated cynomolgus monkey hepatocytes showed active uptake K_m values of 2.0 and 3.9 µM for OATP1B probe substrates, pitavastatin and rosuvastatin, respectively. Rifampicin inhibited pitavastatin and rosuvastatin active uptake in monkey hepatocytes with IC₅₀ values of 3.0 and 0.54 µM, respectively, following preincubation with the inhibitor. Intravenous pharmacokinetics of ²H₄-pitavastatin and ²H₆-rosuvastatin (0.2 mg/kg) and the oral pharmacokinetics of cold probes (2 mg/kg) were studied in cynomolgus monkeys (n = 4) without or with coadministration of single oral ascending doses of rifampicin (1, 3, 10, and 30 mg/kg). A rifampicin dose-dependent reduction in i.v. clearance of statins was observed. Additionally, oral pitavastatin and rosuvastatin plasma exposure increased up to 19- and 15-fold at the highest dose of rifampicin, respectively. Use of in vitro IC₅₀ obtained following 1 hour preincubation with rifampicin (0.54 µM) predicted correctly the change in mean i.v. clearance and oral exposure of statins as a function of mean unbound maximum plasma concentration of rifampicin. This study demonstrates quantitative translation of in vitro OATP1B IC₅₀ to predict DDIs using cynomolgus monkey as a preclinical model and provides further confidence in application of in vitro hepatocyte data for the prediction of clinical OATP1B-mediated DDIs.