Systematic Development and Verification of a Physiologically Based Pharmacokinetic Model of Rivaroxaban

A review of physiologically based pharmacokinetic modeling of renal drug disposition

The human kidney is a critical organ for the elimination of numerous drugs and metabolites. The mechanisms of renal drug handling are manifold including unbound filtration, transporter-mediated active secretion, bidirectional passive diffusion, and occasionally active reabsorption and renal metabolism. These mechanisms collectively dictate the fate of drugs at various spatiotemporal points as drug molecules travel through the renal vasculature, tubules, and cells, posing a significant challenge in accurately describing and predicting renal drug disposition. Toward this end, a physiologically based kidney model serves as a promising tool to combine the anatomical and physiological features of the kidney (eg, tubular flow rate, pH, and transporter expression) with the unique properties of drugs (eg, protein binding, lipophilicity, ionization, and transporter substrate) to capture the dynamic system-drug interactions. Despite the exciting progress over the past several decades, physiologically based pharmacokinetic modeling has overall been predominantly used to predict intestinal absorption and hepatic drug-drug interaction. In comparison, pharmacokinetic modeling of renal drug handling has been underappreciated. In this review, we first provide an overview of kidney function and physiology, renal clearance mechanisms, and the evolutionary history of the physiologically based mechanistic kidney model. We then summarize the recent efforts spent in different areas of kidney model application, particularly: (1) renal transporter-mediated drug-drug interaction, (2) disease effect from both renal and hepatic impairment, and (3) model applications across the lifespan (eg, pediatrics and geriatrics). Finally, we identify remaining knowledge gaps, future directions, and potential model utilities. SIGNIFICANCE STATEMENT: This review summarizes pharmacokinetic model case studies that are related to renal drug disposition, illustrating the current framework of modeling renal drug handling, highlighting knowledge gaps in predicting renal transporter-mediated drug-drug interactions, and modeling the effects of disease and age on renal drug handling. A discussion on robust model validation and areas for future directions is also provided.

Evaluation of Drug-Drug Interactions Between Clarithromycin and Direct Oral Anticoagulants Using Physiologically Based Pharmacokinetic Models

Objective: This study assessed the pharmacokinetic (PK) interactions between clarithromycin (a P-glycoprotein [P-gp] inhibitor) and four direct oral anticoagulants (DOACs) (P-gp substrates) using physiologically based PK (PBPK) models to elucidate the influence of P-gp in the interaction between them. Methods: PBPK models for clarithromycin, DABE-dabigatran (DAB), rivaroxaban, apixaban, and edoxaban were constructed using GastroPlus™ (version 9.9), based on physicochemical data and PK parameters from the literature. The models were optimized and validated in healthy subjects. We evaluated the predictive performance of the established model and further assessed the impact of P-gp on the PK of the four DOACs. Successfully validated models were then used to evaluate potential drug-drug interactions (DDIs) between clarithromycin and the DOACs. Results: The established PBPK models accurately described the PK of clarithromycin, DABE-DAB, rivaroxaban, apixaban, and edoxaban. The predicted PK parameters (Cmax, Tmax, AUC0-t) were within 0.5-2 times the observed values. A sensitivity analysis of P-gp parameters indicated that an increase in P-gp expression was reduced by in vivo exposure to DOACs. The models demonstrated good predictive ability for DDIs between clarithromycin and the anticoagulants, and the ratio of the predicted values to the observed values of Cmax and the area under the curve (AUC) in the DDI state was within the range of 0.5-2. Conclusions: Comprehensive PBPK models for clarithromycin, DABE-DAB, rivaroxaban, apixaban, and edoxaban were developed, which can effectively predict DDIs mediated by P-gp's function. These models provide theoretical support for clinical dose adjustments and serve as a foundation for future PBPK model development for DOACs under specific pathological conditions.

Drug Interactions between Androgen Receptor Axis-Targeted Therapies and Antithrombotic Therapies in Prostate Cancer: Delphi Consensus

Background/Objectives: Abiraterone acetate, apalutamide, darolutamide, and enzalutamide, which make up the androgen receptor axis-targeted therapies (ARATs) drug class, are commonly used in the management of prostate cancer. Many patients on ARATs also receive oral antithrombotic therapy (i.e., anticoagulants or antiplatelets). The concomitant use of ARATs and antithrombotic therapies creates the potential for clinically relevant drug-drug interactions, but the literature regarding the actual consequences of these interactions, and guidance for co-prescribing, is limited. We assembled a multidisciplinary panel of experts and provided them with clinical information derived from a comprehensive literature review regarding the drug-drug interactions between ARATs and antithrombotic therapies. Methods: A three-stage modified electronic Delphi process was used to gather and consolidate opinions from the panel. Each stage consisted of up to three rounds of voting to achieve consensus on which ARAT/antithrombotic therapy drug pairs warrant attention, the possible clinical consequences of drug-drug interactions, and suggested actions for management. Results: The panel achieved consensus to avoid 11 ARAT/antithrombotic therapy drug pairs and modify therapy for eight pairs. Assessments relied heavily on pharmacokinetic data and extrapolation from drug-drug interaction studies of similarly metabolized drugs. Conclusions: This e-Delphi process highlights the need for further research into the clinical impact of ARAT/antithrombotic drug interactions. Nonetheless, the suggested actions aim to provide clinicians with a practical framework for therapeutic decision making.

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

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

Effects of tyrosine kinase inhibitors used for the treatment of non-small cell lung carcinoma on cytochrome P450 2J2 activities

Cytochrome P450 (CYP) 2J2 is responsible for the epoxidation of arachidonic acid, producing epoxyeicosatrienoic acids (EETs) that are known to enhance tumorigenesis. CYP2J2 is prominently expressed in the heart and also found in the lungs. Furthermore, the expression level of CYP2J2 in tumour tissues is higher than that in adjacent normal tissues. Non-small cell lung carcinoma is a common cancer, and tyrosine kinase inhibitors (TKIs) are powerful tools for its treatment. This study aimed to elucidate the inhibitory effects of 17 TKIs on CYP2J2 activity using LC-MS/MS.Seventeen TKIs exhibited different inhibitory effects on CYP2J2-catalysed astemizole O-demethylation in recombinant CYP2J2. Pralsetinib and selpercatinib showed strong competitive inhibition, with inhibition constant values of 0.48 and 1.1 µM, respectively. They also inhibited other CYP2J2 activities, including arachidonic acid epoxidation, hydroxyebastine carboxylation, and rivaroxaban hydroxylation.In conclusion, we showed that pralsetinib and selpercatinib strongly inhibit CYP2J2 activity. Inhibition of 14,15-EET production by these TKIs may be a novel mechanism for suppressing tumour growth and proliferation. Additionally, when these TKIs are co-administered with a CYP2J2 substrate, we may consider the possibility of drug-drug interactions via CYP2J2 inhibition.

Time Course of the Interaction Between Oral Short-Term Ritonavir Therapy with Three Factor Xa Inhibitors and the Activity of CYP2D6, CYP2C19, and CYP3A4 in Healthy Volunteers

BACKGROUND

We investigated the effect of a 5-day low-dose ritonavir therapy, as it is used in the treatment of COVID-19 with nirmatrelvir/ritonavir, on the pharmacokinetics of three factor Xa inhibitors (FXaI). Concurrently, the time course of the activities of the cytochromes P450 (CYP) 3A4, 2C19, and 2D6 was assessed.

METHODS

In an open-label, fixed sequence clinical trial, the effect and duration of a 5-day oral ritonavir (100 mg twice daily) treatment on the pharmacokinetics of three oral microdosed FXaI (rivaroxaban 25 µg, apixaban 25 µg, and edoxaban 50 µg) and microdosed probe drugs (midazolam 25 µg, yohimbine 50 µg, and omeprazole 100 µg) was evaluated in eight healthy volunteers. The plasma concentrations of all drugs were quantified using validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods and pharmacokinetics were analysed using non-compartmental analyses.

RESULTS

Ritonavir increased the exposure of apixaban, edoxaban, and rivaroxaban, but to a different extent the observed area under the plasma concentration-time curve (geometric mean ratio 1.29, 1.46, and 1.87, respectively). A strong CYP3A4 inhibition (geometric mean ratio > 10), a moderate CYP2C19 induction 2 days after ritonavir (0.64), and no alteration of CYP2D6 were observed. A CYP3A4 recovery half-life of 2.3 days was determined.

CONCLUSION

This trial with three microdosed FXaI suggests that at most the rivaroxaban dose should be reduced during short-term ritonavir, and only in patients receiving high maintenance doses. Thorough time series analyses demonstrated differential effects on three different drug-metabolising enzymes over time with immediate profound inhibition of CYP3A4 and only slow recovery after discontinuation.

CLINICAL TRIAL REGISTRATION

EudraCT number: 2021-006643-39.

Investigating the association between CYP2J2 inhibitors and QT prolongation: a literature review

Drug withdrawal post-marketing due to cardiotoxicity is a major concern for drug developers, regulatory agencies, and patients. One common mechanism of cardiotoxicity is through inhibition of cardiac ion channels, leading to prolongation of the QT interval and sometimes fatal arrythmias. Recently, oxylipin signaling compounds have been shown to bind to and alter ion channel function, and disruption in their cardiac levels may contribute to QT prolongation. Cytochrome P450 2J2 (CYP2J2) is the predominant CYP isoform expressed in cardiomyocytes, where it oxidizes arachidonic acid to cardioprotective epoxyeicosatrienoic acids (EETs). In addition to roles in vasodilation and angiogenesis, EETs bind to and activate various ion channels. CYP2J2 inhibition can lower EET levels and decrease their ability to preserve cardiac rhythm. In this review, we investigated the ability of known CYP inhibitors to cause QT prolongation using Certara's Drug Interaction Database. We discovered that among the multiple CYP isozymes, CYP2J2 inhibitors were more likely to also be QT-prolonging drugs (by approximately 2-fold). We explored potential binding interactions between these inhibitors and CYP2J2 using molecular docking and identified four amino acid residues (Phe61, Ala223, Asn231, and Leu402) predicted to interact with QT-prolonging drugs. The four residues are located near the opening of egress channel 2, highlighting the potential importance of this channel in CYP2J2 binding and inhibition. These findings suggest that if a drug inhibits CYP2J2 and interacts with one of these four residues, then it may have a higher risk of QT prolongation and more preclinical studies are warranted to assess cardiovascular safety.

An extension of biorelevant fed-state dissolution tests to clinical pharmacokinetics - A study on gastrointestinal factors influencing rivaroxaban exposure and efficacy in atrial fibrillation patients

A direct oral anticoagulant rivaroxaban fails to prevent stroke and systemic embolism in one-to-several percent of patients with nonvalvular atrial fibrillation (NVAF), but the reasons are unknown. The study used semi-mechanistic in vitro-in vivo prediction (IVIVP) modeling to explore the reasons for ineffective thrombosis prevention in NVAF patients. Steady-state drug concentrations in plasma were measured at 0 h (Ctrough), 3 h (C3h), and 12 h post-dosing in thirty-four patients treated with 20 mg rivaroxaban daily. The clinical data were compared against "virtual twins" generated with a novel IVIVP model that combined drug dissolution modeling, mechanistic description of gastric drug transit, and population pharmacokinetics defining the variability of drug disposition. The nonresponders had significantly lower C3h and Ctrough than the responders (p < 0.001) and the covariates included in the population pharmacokinetic submodel did not fully explain this difference. Simulations involving varied gastrointestinal parameters in the "virtual twins" revealed that lower small intestinal effective permeability (Peff), rather than a slower stomach emptying rate, could explain low rivaroxaban exposure in the nonresponders. IVIVP modeling was effectively used for exploring pharmacotherapy failure. Low Peff, found as a major determinant of ineffective rivaroxaban treatment, encourages further research to find (pato)physiological factors influencing suboptimal absorption.

Chronic kidney disease and physiologically based pharmacokinetic modeling: a critical review of existing models

INTRODUCTION

Physiologically based pharmacokinetic (PBPK) modeling is a paradigm shift in this era for determining the exposure of drugs in pediatrics, geriatrics, and patients with chronic diseases where clinical trials are difficult to conduct.

AREAS COVERED

This review has collated data regarding published PBPK models on chronic kidney disease (CKD), including the drug and system-specific input model parameters and model evaluation criteria. Four databases were used from 13th June 2023 to 10th July 2023 for identifying the relevant studies that met the inclusion/exclusion criteria. Alterations in plasma protein (albumin/alpha-1 acid glycoprotein), gastric emptying time, hematocrit, small intestinal transit time, the abundance of cytochrome (CYP) 450 enzymes, glomerular filtration rate, and physicochemical parameters for different drugs were explicitly elaborated from earlier reported studies. Moreover, model evaluation depicted that models in CKD for most of the included drugs were within the allowed two-fold error range.

EXPERT OPINION

This review will provide insights for researchers on applying PBPK models in managing patients with different levels of CKD to prevent undesirable side effects and increase the effectiveness of drug therapy.

Apixaban and rivaroxaban's physiologically-based pharmacokinetic model validation in hospitalized patients: A first step for larger use of a priori modeling approach at bed side

When used in real-world conditions, substantial interindividual variations in direct oral anticoagulant (DOAC) plasma concentrations are observed for a given dose, leading to a risk of over- or under-exposure and clinically significant adverse events. Physiologically-based pharmacokinetic (PBPK) models could help physicians to tailor DOAC prescriptions in vulnerable patient populations, such as those in the hospital setting. The present study aims to validate prospectively PBPK models for rivaroxaban and apixaban in a large cohort of elderly, polymorbid, and hospitalized patients. In using a model of geriatric population integrating appropriate physiological parameters into models first optimized with healthy volunteer data, observed plasma concentration collected in hospitalized patients on apixaban (n = 100) and rivaroxaban (n = 100) were adequately predicted (ratio predicted/observed area under the concentration curve for a dosing interval [AUCtau ] = 0.97 [0.96-0.99] geometric mean, 90% confidence interval, ratio predicted/observed AUCtau  = 1.03 [1.02-1.05]) for apixaban and rivaroxaban, respectively. Validation of the present PBPK models for rivaroxaban and apixaban in in-patients represent an additional step toward the feasibility of bedside use.

Simvastatin, but Not Atorvastatin, Is Associated with Higher Peak Rivaroxaban Serum Levels and Bleeding: an Asian Cohort Study from Singapore

AIMS

This study attempts to identify predictors associated with bleeding and stroke and systemic embolism (SSE) in Singaporean Asians taking rivaroxaban and apixaban.

METHODS

A total of 134 Singaporean patients on either rivaroxaban or apixaban for non-valvular atrial fibrillation were included for this study. Baseline characteristics were recorded at recruitment while bleeding and SSE events were recorded during a 1-year follow-up. Peak and trough drug plasma concentrations were collected based on the dosing interval and pharmacokinetics of the drugs and quantified using high performance liquid chromatography. Characteristics of patients with or without bleeds were compared using relevant statistical tests. Multivariable regression that included covariates with p < 0.1 from an initial univariable regression was performed to analyse predictors that resulted in higher risk of bleeding in patients.

RESULTS

Median creatinine clearance (CrCl) was significantly lower in patients on rivaroxaban who experienced bleeds as compared to patients who did not experience bleeds (61.5 vs 70.8 mL/min, p = 0.047), while concomitant simvastatin use was found to be independently associated with a sixfold increased risk of bleeding (adjusted OR = 6.14 (95% CI: 1.18-31.97), p = 0.031) for rivaroxaban after controlling for body mass index, CrCl and having experienced a previous SSE.

CONCLUSION

Our findings suggest that concomitant use of simvastatin with rivaroxaban may be associated with bleeding events in an Asian cohort. Further studies using physiologically based pharmacokinetic modelling are required to investigate the drug-drug interactions between these drugs.

Physiologically-based pharmacokinetic pharmacodynamic parent-metabolite model of edoxaban to predict drug-drug-disease interactions: M4 contribution

This study aimed to develop a physiologically-based pharmacokinetic pharmacodynamic (PBPK/PD) parent-metabolite model of edoxaban, an oral anticoagulant with a narrow therapeutic index, and to predict pharmacokinetic (PK)/PD profiles and potential drug-drug-disease interactions (DDDIs) in patients with renal impairment. A whole-body PBPK model with a linear additive PD model of edoxaban and its active metabolite M4 was developed and validated in SimCYP for healthy adults with or without interacting drugs. The model was extrapolated to situations including renal impairment and drug-drug interactions (DDIs). Observed PK and PD data in adults were compared with predicted data. The effect of several model parameters on the PK/PD response of edoxaban and M4 was investigated in sensitivity analysis. The PBPK/PD model successfully predicted PK profiles of edoxaban and M4 as well as anticoagulation PD responses with or without the influence of interacting drugs. For patients with renal impairment, the PBPK model successfully predicted the fold change in each impairment group. Inhibitory DDI and renal impairment had a synergistic effect on the increased exposure of edoxaban and M4, and their downstream anticoagulation PD effect. Sensitivity analysis and DDDI simulation show that renal clearance, intestinal P-glycoprotein activity, and hepatic OATP1B1 activity are the major factors affecting edoxaban-M4 PK profiles and PD responses. Anticoagulation effect induced by M4 cannot be ignored when OATP1B1 is inhibited or downregulated. Our study provides a reasonable approach to adjust the dose of edoxaban in several complicated scenarios especially when M4 cannot be ignored due to decreased OATP1B1 activity.

Physiologically-based pharmacokinetic modeling to predict drug-drug interactions of dabigatran etexilate and rivaroxaban in the Chinese older adults

INTRODUCTION

Drug-drug interaction (DDI) is one of the major concerns for the clinical use of NOACs in the older adults considering that coexistence of multiple diseases and comorbidity were common. Current guidelines on the DDI management were established based on clinical studies conducted in healthy adults and mainly focus on the Caucasians, whereas systemic and ethnic differences may lead to distinct management in the Chinese older adults.

OBJECTIVES

To investigate the impact of aging on the DDI magnitude between P-gp and/or CYP3A4 inhibitors with dabigatran etexilate and rivaroxaban in older adults, providing additional information for the use in clinical practice.

RESULTS

Compared with the simulated adult, the AUC of the simulated older adults increased by 42-88% (DABE) and 21-60% (rivaroxaban), respectively, during NOACs monotherapy. Simulation on DDIs predicted that verapamil and clarithromycin further increase the exposure of dabigatran by 29-72% and 40-47%, whereas clarithromycin, fluconazole, and ketoconazole increase the exposure of rivaroxaban by 21-30%, 16-24%, and 194-247% in the older adults. Overall, our simulation result demonstrated that aging and DDIs both increased the exposure of NOACs. However, aging does not have a drastic impact on the extent of DDIs. The DDI ratios of young and old older adults were similar to the adults and were also similar between Caucasians and Chinese.

DISCUSSION

We further simulated the interactions under steady-state based on the EHRA guideline (2021). Our simulation results revealed that recommended reduced dosing regimen of dabigatran etexilate during comedication with verapamil and clarithromycin (110 and 75 mg BID for Chinese young and old older adults) will result in exposure (trough concentration) that was either slightly higher or similar to the trough concentration of patients with any bleeding events. Routine monitoring of bleeding risk is encouraged. Further studies on the use of rivaroxaban in Chinese older adults are warranted.

CONCLUSION

Aging and DDI increases exposure of drug in Chinese older adults. However, aging does not have a drastic impact on the extent of DDIs. Clinical management of DDIs in Chinese older adults in the absence of complex polypharmacy can a priori be similar to the EHRA guideline but routine monitoring of bleeding risk is encouraged when dabigatran etexilate given with verapamil and clarithromycin.

Predicting transporter mediated drug-drug interactions via static and dynamic physiologically based pharmacokinetic modeling: A comprehensive insight on where we are now and the way forward

The greater utilization and acceptance of physiologically-based pharmacokinetic (PBPK) modeling to evaluate the potential metabolic drug-drug interactions is evident by the plethora of literature, guidance's, and regulatory dossiers available in the literature. In contrast, it is not widely used to predict transporter-mediated DDI (tDDI). This is attributed to the unavailability of accurate transporter tissue expression levels, the absence of accurate in vitro to in vivo extrapolations (IVIVE), enzyme-transporter interplay, and a lack of specific probe substrates. Additionally, poor understanding of the inhibition/induction mechanisms coupled with the inability to determine unbound concentrations at the interaction site made tDDI assessment challenging. Despite these challenges, continuous improvements in IVIVE approaches enabled accurate tDDI predictions. Furthermore, the necessity of extrapolating tDDI's to special (pediatrics, pregnant, geriatrics) and diseased (renal, hepatic impaired) populations is gaining impetus and is encouraged by regulatory authorities. This review aims to visit the current state-of-the-art and summarizes contemporary knowledge on tDDI predictions. The current understanding and ability of static and dynamic PBPK models to predict tDDI are portrayed in detail. Peer-reviewed transporter abundance data in special and diseased populations from recent publications were compiled, enabling direct input into modeling tools for accurate tDDI predictions. A compilation of regulatory guidance's for tDDI's assessment and success stories from regulatory submissions are presented. Future perspectives and challenges of predicting tDDI in terms of in vitro system considerations, endogenous biomarkers, the use of empirical scaling factors, enzyme-transporter interplay, and acceptance criteria for model validation to meet the regulatory expectations were discussed.

Inhibition of Cytochrome P450 2J2-Mediated Metabolism of Rivaroxaban and Arachidonic Acid by Ibrutinib and Osimertinib

Covalent tyrosine kinase inhibitors (TKIs) ibrutinib and osimertinib are associated with cardiac arrhythmia. The interactions between these TKIs with CYP2J2 that is highly expressed in the human heart are unknown. In vitro metabolism experiments were performed to characterize CYP2J2-mediated metabolism of ibrutinib and osimertinib. Unbound distribution coefficient (Kpuu) for both TKIs was determined in AC16 cardiomyocytes. In vitro reversible and time-dependent CYP2J2 inhibition experiments were conducted with exogenous and endogenous substrates, namely rivaroxaban and arachidonic acid (AA), respectively, where kinetic parameters were estimated via one-site and multisite kinetic modeling. Ibrutinib was efficiently metabolized by CYP2J2 to a hydroxylated metabolite, M35, following substrate inhibition kinetics. Osimertinib is not a substrate of CYP2J2. Both TKIs depicted Kpuu values above 1 and equipotently inhibited CYP2J2-mediated hydroxylation of rivaroxaban in a concentration-dependent manner without time-dependency. The mode of reversible inhibition of CYP2J2-mediated metabolism of rivaroxaban and AA by osimertinib was described by Michaelis-Menten kinetics, whereas a two-site kinetic model recapitulated the atypical inhibitory kinetics of ibrutinib, assuming multiple substrate-binding domains within the CYP2J2 active site. The inhibition of ibrutinib and osimertinib on cardiac AA metabolism could be clinically significant considering the preferable distribution of both TKIs to cardiomyocytes with R cut-off values of 1.160 and 1.026, respectively. The dysregulation of CYP2J2-mediated metabolism of AA to cardioprotective epoxyeicosatrienoic acids by ibrutinib and osimertinib serves as a novel mechanism for TKI-induced cardiac arrhythmia. Mechanistic characterization of CYP2J2-mediated typical and atypical enzyme kinetics further illuminates the unique catalytic properties of CYP2J2. SIGNIFICANCE STATEMENT: We reported for the first time that ibrutinib is efficiently metabolized by CYP2J2. By using rivaroxaban and arachidonic acid (AA) as substrates, we characterized the typical and atypical inhibition kinetics of CYP2J2 by ibrutinib and osimertinib. The inhibition of both drugs on cardiac AA metabolism could be clinically significant considering their preferable distribution to cardiomyocytes. Our findings serve as a novel mechanism for drug-induced cardiac arrhythmia and shed insights into the multisite interactions between CYP2J2 and ligands.

Risk assessment and molecular mechanism study of drug-drug interactions between rivaroxaban and tyrosine kinase inhibitors mediated by CYP2J2/3A4 and BCRP/P-gp

Cancer patients generally has a high risk of thrombotic diseases. However, anticoagulant therapy always aggravates bleeding risks. Rivaroxaban is one of the most widely used direct oral anticoagulants, which is used as anticoagulant treatment or prophylaxis in clinical practice. The present study aimed to systemically estimate the combination safety of rivaroxaban with tyrosine kinase inhibitors (TKIs) based on human cytochrome P450 (CYPs) and efflux transporters and to explore the drug–drug interaction (DDI) mechanisms in vivo and in vitro. In vivo pharmacokinetic experiments and in vitro enzyme incubation assays and bidirectional transport studies were conducted. Imatinib significantly increased the rivaroxaban C_max value by 90.43% (p < 0.05) and the area under the curve value by 119.96% (p < 0.01) by inhibiting CYP2J2- and CYP3A4-mediated metabolism and breast cancer resistance protein (BCRP)- and P-glycoprotein (P-gp)-mediated efflux transportation in the absorption phase. In contrast, the combination of sunitinib with rivaroxaban reduced the exposure in vivo by 62.32% (p < 0.05) and the C_max value by 72.56% (p < 0.05). In addition, gefitinib potently inhibited CYP2J2- and CYP3A4-mediated rivaroxaban metabolism with K_i values of 2.99 μΜ and 4.91 μΜ, respectively; however, it almost did not affect the pharmacokinetics of rivaroxaban in vivo. Taken together, clinically significant DDIs were observed in the combinations of rivaroxaban with imatinib and sunitinib. Imatinib increased the bleeding risks of rivaroxaban, while sunitinib had a risk of reducing therapy efficiency. Therefore, more attention should be paid to aviod harmful DDIs in the combinations of rivaroxaban with TKIs.

Physiologically Based Pharmacokinetic Modelling-Guided Dose Management of Oral Anticoagulants when Initiating Paxlovid for COVID-19 Treatment

Patients with coronavirus disease 2019 (COVID‐19) with cardiovascular diseases who are at higher risk of progressing to critical illness should be treated with nirmatrelvir/ritonavir (Paxlovid). Ritonavir, the booster in nirmatrelvir/ritonavir, modulates multiple drug metabolizing enzymes and transporters, complicating its use in real‐world clinics. We aimed to apply physiologically‐based pharmacokinetic (PBPK) modeling to simulate the complex drug–drug interactions (DDIs) of ritonavir with two anticoagulants, rivaroxaban and racemic warfarin, to address this important clinical conundrum. Simulations were implemented within Simcyp Simulator. Compound and population models were adopted from Simcyp and our previous studies. Upon verification and validation of the PBPK model of ritonavir, prospective DDI simulations with the anticoagulants were performed in both the general population (20–65 years) and geriatric subjects (65–85 years) with or without moderate renal impairment. Elevated rivaroxaban concentrations were simulated with nirmatrelvir/ritonavir treatment, where the impact was more profound among geriatric subjects with renal impairment. The overexposure of rivaroxaban was restored to normal range on day 4 post‐discontinuation of nirmatrelvir/ritonavir, corroborating with the recovery of enzyme activity. A lower 10 mg daily dose of rivaroxaban could effectively maintain acceptable systemic exposure of rivaroxaban during nirmatrelvir/ritonavir treatment. Treatment of ritonavir marginally declined simulated S‐warfarin concentrations, but substantially elevated that of R‐warfarin, resulting in a decrease in the international normalized ratio (INR). As INR only recovered 2 weeks post‐nirmatrelvir/ritonavir treatment, a longer surveillance INR for warfarin becomes important. Our PBPK‐guided simulations evaluated clinically important yet untested DDIs and supports clinical studies to ensure proper anticoagulation management of patients with COVID‐19 with chronic coagulative abnormalities when initiating nirmatrelvir/ritonavir therapy.

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.

Febuxostat and its Major Acyl Glucuronide Metabolite are Potent Inhibitors of Organic Anion Transporter 3: Implications for Drug-Drug Interactions with Rivaroxaban

Febuxostat is a second-line xanthine oxidase inhibitor that undergoes extensive hepatic metabolism to yield its major acyl-β-D-glucuronide metabolite (febuxostat AG). It was recently reported that febuxostat inhibited organic anion transporter 3 (OAT3)-mediated uptake of enalaprilat. Here, we investigated the inhibition of febuxostat and febuxostat AG on organic anion transporter 3 (OAT3) in transfected human embryonic kidney 293 cells. Our transporter inhibition assays confirmed the potent noncompetitive and competitive inhibition of OAT3-mediated estrone-3-sulfate transport by febuxostat and febuxostat AG with corresponding apparent K_i values of 0.55 μM and 6.11 μM respectively. After accounting for probe substrate-dependency and protein binding effects, mechanistic static modelling with the direct factor Xa anticoagulant rivaroxaban estimated a 1.47-fold increase in its systemic exposure when co-administered with febuxostat based on OAT3 interaction which in turn exacerbates the bleeding risk from baseline for patients with atrial fibrillation by 1.51-fold. Taken together, our results suggested that the concomitant usage of febuxostat with rivaroxaban may potentially culminate in a clinically-significant drug-drug interaction and result in an increased risk of bleeding as a result of its OAT3 inhibition. This article is protected by copyright. All rights reserved.

P-Glycoprotein Aggravates Blood Brain Barrier Dysfunction in Experimental Ischemic Stroke by Inhibiting Endothelial Autophagy

P-glycoprotein (P-gp) is expressed on brain microvessel endothelial cells of blood-brain barrier (BBB) and elevated after cerebral ischemia. In this study, we explored the influence and potential mechanisms of P-gp on BBB function in experimental ischemic stroke in vivo and in vitro. Middle cerebral artery occlusion/reperfusion (MCAO/R) was created in mice. Oxygen-glucose deprivation/reoxygenation (OGD/R) was performed in brain microvascular vessel-derived endothelial cells (bEnd.3) to mimic ischemia/reperfusion injury in vitro. P-gp-specific siRNA and pharmacological inhibitor cyclosporine A were used to inhibit P-gp, whereas pcDNA3.1 was utilized to overexpress P-gp. Twenty-four hours after reperfusion, acute ischemic stroke outcome, BBB integrity and permeability, autophagic proteins and relative signaling pathways were evaluated. P-gp levels were markedly elevated in mouse brain and endothelial cells following MCAO/R and OGD/R, respectively. P-gp siRNA silencing or pharmacologically inhibiting (cyclosporine A) reduced infarct volume and brain edema, attenuated brain pathology, and improved neurological behavior in association with attenuated accumulation of neutrophils and macrophages, reduced expression levels of inflammatory cytokines (TNF-α and IL-1β), matrix metalloproteinases (MMP-2 and MMP-9) and adhesion molecules (ICAM-1 and VCAM-1). P-gp silence also counteracted BBB leakage, restored the expressions of tight junction proteins (Claudin-5, Occludin and ZO-1), activated autophagic proteins (upregulated LC3-II/LC3-I and Beclin 1, and downregulated P62), and diminished Akt/mTOR signal activity in mice following MCAO/R. In the endothelial cell OGD/R assay, P-gp silence downregulated the expressions of inflammatory cytokines and adhesion molecules, inhibited leukocytes adhesion and migration, increased tight junction protein levels, and activated autophagy, all were reversible by forceful P-gp expression. Additionally, treatment with an autophagy inhibitor (3-methyladenine) abolished protections against ischemic stroke and tight junction proteins reduction followed by P-gp silence. In conclusion, increased P-gp expression after ischemic injury resulted in BBB dysfunction and hyperpermeability by suppressing Akt/mTOR-induced endothelial autophagy.

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.

Model-Based Risk Prediction of Rivaroxaban with Amiodarone for Moderate Renal Impaired Elderly Population

PURPOSE

Increased bleeding risk was found associated with concurrent prescription of rivaroxaban and amiodarone. We previously recommended dose adjustment for rivaroxaban utilizing a physiologically based pharmacokinetic (PBPK) modeling approach. Our subsequent in vitro studies discovered the pivotal involvement of human renal organic anion transporter 3 (hOAT3) in the renal secretion of rivaroxaban and the inhibitory potency of amiodarone. This study aimed to redefine the disease-drug-drug interactions (DDDI) between rivaroxaban and amiodarone and update the potential risks.

METHODS

Prospective simulations were conducted with updated PBPK models of rivaroxaban and amiodarone incorporating hOAT3-related parameters.

RESULTS

Simulations to recapitulate previously explored DDDI in renal impairment showed a higher bleeding tendency in all simulation scenarios after integrating hOAT3-mediated clearance into PBPK models. Further sensitivity analysis revealed that both hOAT3 dysfunction and age could affect the extent of DDDI, and age was shown to have a more pivotal role on rivaroxaban in vivo exposure. When amiodarone was prescribed along with our recommended dose reduction of rivaroxaban to 10 mg in moderate renal impaired elderly people, it could result in persistently higher rivaroxaban peak concentrations at a steady state. To better manage the increased bleeding risk among such a vulnerable population, a dose reduction of rivaroxaban to 2.5 mg twice daily resulted in its acceptable in vivo exposure.

CONCLUSION

Close monitoring of bleeding tendency is essential for elderly patients with moderate renal impairment receiving co-prescribed rivaroxaban and amiodarone. Further dose reduction is recommended for rivaroxaban to mitigate this specific DDDI risk.

Investigation of the arcane inhibition of human organic anion transporter 3 by benzofuran antiarrhythmic agents

The combination of antiarrhythmic agents, amiodarone or dronedarone, with the anticoagulant rivaroxaban is used clinically in the management of atrial fibrillation for rhythm control and secondary stroke prevention respectively. Renal drug-drug interactions (DDIs) between amiodarone or dronedarone and rivaroxaban were previously ascribed to inhibition of rivaroxaban secretion by P-glycoprotein at the apical membrane of renal proximal tubular epithelial cells. Benzbromarone, a known inhibitor of organic anion transporter 3 (OAT3), shares a benzofuran scaffold with amiodarone and dronedarone. However, inhibitory activity of amiodarone and dronedarone against OAT3 remains arcane. Here, we conducted in vitro transporter inhibition assays in OAT3-transfected HEK293 cells which revealed amiodarone, dronedarone and their respective major pharmacologically-active metabolites N-desethylamiodarone and N-desbutyldronedarone possess inhibitory activity against OAT3, with corrected K_i values of 0.042, 0.019, 0.028 and 0.0046 μM respectively. Protein binding effects and probe substrate dependency were accounted for in our assays. Static modelling predicted 1.29-, 1.01-, 1.29- and 1.16-fold increase in rivaroxaban exposure, culminating in a predicted 1.29-, 1.01-, 1.28- and 1.15-fold increase in major bleeding risk respectively, suggesting potential OAT3-mediated DDI between amiodarone and rivaroxaban. Future work involving physiologically-based pharmacokinetic modelling is crucial in holistically predicting the complex DDIs between the benzofuran antiarrhythmic agents and rivaroxaban.

Physiologically-Based Pharmacokinetic Modeling for the Prediction of a Drug-Drug Interaction of Combined Effects on P-glycoprotein and Cytochrome P450 3A

Direct oral anticoagulants, such as apixaban and rivaroxaban, are important for the treatment and prophylaxis of venous thromboembolism and to reduce the risk of stroke and systemic embolism in patients with nonvalvular atrial fibrillation. Because apixaban and rivaroxaban are predominantly eliminated by cytochrome P450 (CYP) 3A and P‐glycoprotein (P‐gp), concomitant use of combined P‐gp and strong CYP3A4 inhibitors and inducers should be avoided. Physiologically‐based pharmacokinetic models for apixaban and rivaroxaban were developed to estimate the net effect of CYP3A induction, P‐gp inhibition, and P‐gp induction by rifampicin. The disposition of rivaroxaban is more complex compared with apixaban because both hepatic and renal P‐gp is considered to contribute to rivaroxaban elimination. Furthermore, organic anion transporter‐3, a renal uptake transporter, may also contribute the elimination of rivaroxaban from systemic circulation. The models were verified with observed clinical drug–drug interactions with CYP3A and P‐gp inhibitors. With the developed models, the predicted area under the concentration time curve and maximum concentration ratios were 0.43 and 0.48, respectively, for apixaban, and 0.50–0.52 and 0.72–0.73, respectively, for rivaroxaban when coadministered with 600 mg multiple doses of rifampicin and that were very close to observed data. The impact of each of the elimination pathways was assessed for rivaroxaban, and inhibition of CYP3A led to a larger impact over intestinal and hepatic P‐gp. Inhibition of renal organic anion transporter‐3 or P‐gp led to an overall modest interaction. The developed apixaban and rivaroxaban models can be further applied to the investigation of interactions with other P‐gp and/or CYP3A4 inhibitors and inducers.

Mechanistic PBPK Modeling of Urine pH Effect on Renal and Systemic Disposition of Methamphetamine and Amphetamine

The effect of urine pH on renal excretion and systemic disposition has been observed for many drugs and metabolites. When urine pH is altered, tubular ionization, passive reabsorption, renal clearance, and systemic exposure of drugs and metabolites may all change dramatically, raising clinically significant concerns. Surprisingly, the urine pH effect on drug disposition is not routinely explored in humans, and regulatory agencies have neither developed guidance on this issue nor required industry to conduct pertinent human trials. In this study, we hypothesized that physiologically based pharmacokinetic (PBPK) modeling could be used as a cost-effective method to examine potential urine pH effect on drug and metabolite disposition. Our previously developed and verified mechanistic kidney model was integrated with a full-body PBPK model to simulate renal clearance and area under the plasma concentration-time curve (AUC) with varying urine pH statuses using methamphetamine and amphetamine as model compounds. We first developed and verified drug models for methamphetamine and amphetamine under normal urine pH condition [absolute average fold error (AAFE) < 1.25 at study level]. Then, acidic and alkaline urine scenarios were simulated. Our simulation results show that the renal excretion and plasma concentration-time profiles for methamphetamine and amphetamine could be recapitulated under different urine pH (AAFE < 2 at individual level). The methamphetamine-amphetamine parent-metabolite full-body PBPK model also successfully simulated amphetamine plasma concentration-time profiles (AAFE < 1.25 at study level) and amphetamine/methamphetamine urinary concentration ratios (AAFE < 2 at individual level) after dosing methamphetamine. This demonstrates that our mechanistic PBPK model can predict urine pH effect on systemic and urinary disposition of drugs and metabolites. SIGNIFICANCE STATEMENT: Our study shows that integrating mechanistic kidney model with full-body physiologically based pharmacokinetic model can predict the magnitude of alteration in renal excretion and area under the plasma concentration-time curve (AUC) of drugs and metabolites when urine pH is changed. This provides a cost-effective method to evaluate the likelihood of renal and systemic disposition changes due to varying urine pH. This is important because multiple drugs and diseases can alter urine pH, leading to quantitatively and clinically significant changes in drug and metabolite disposition that may require adjustment of therapy.