Application of Physiologically Based Pharmacokinetic Modeling to Predict Pharmacokinetics in Healthy Japanese Subjects

Development and Verification of a Japanese Pediatric Physiologically Based Pharmacokinetic Model with Emphasis on Drugs Eliminated by Cytochrome P450 or Renal Excretion

Physiologically based pharmacokinetic (PBPK) models are useful in bridging drug exposure in different ethnic groups, and there is increasing regulatory application of this approach in adults. Reported pediatric PBPK models tend to focus on the North European population, with few examples in other ethnic groups. This study describes the development and verification of a Japanese pediatric PBPK population. The development of the model was based on the existing North European pediatric population. Japanese systems and clinical data were collated from public databases and the literature, and the underlying demographics and equations were optimized so that physiological outputs represented the Japanese pediatric population. The model was tested using 14 different small molecule drugs, eliminated by a variety of pathways, including cytochrome P450 3A4 (CYP3A4) metabolism and renal excretion. Given the limitations of the clinical data, the overall performance of the model was good, with 44/62 predictions for PK parameters (area under the plasma drug concentration-time curve, AUC; maximum serum concentration, Cmax ; clearance, CL) being within 0.8- to 1.25-fold, 56/62 within 0.67- to 1.5-fold, and 61/62 within 0.5- to 2.0-fold of the observed values. Specific results for the 5 CYP3A4 substrates showed 20/31 cases were predicted within 0.8- to 1.25-fold, 27/31 within 0.67- to 1.5-fold, and all were within 0.5- to 2.0-fold of the observed values. Given the increased regulatory use of pediatric PBPK in drug development, expanding these models to other ethnic groups are important. Considering qualifying these models based on the context of use, there is a need to expand on the current research to include a larger range of drugs with different elimination pathways. Collaboration among academic, industry, model providers, and regulators will facilitate further development.

Physiologically-based pharmacokinetic modeling for optimal dosage prediction of olaparib when co-administered with CYP3A4 modulators and in patients with hepatic/renal impairment

This study aimed to develop a physiologically-based pharmacokinetic (PBPK) model to predict the maximum plasma concentration (Cmax) and trough concentration (Ctrough) at steady-state of olaparib (OLA) in Caucasian, Japanese and Chinese. Furthermore, the PBPK model was combined with mean and 95% confidence interval to predict optimal dosing regimens of OLA when co-administered with CYP3A4 modulators and administered to patients with hepatic/renal impairment. The dosing regimens were determined based on safety and efficacy PK threshold Cmax (< 12,500 ng/mL) and Ctrough (772-2500 ng/mL). The population PBPK model for OLA was successfully developed and validated, demonstrating good consistency with clinically observed data. The ratios of predicted to observed values for Cmax and Ctrough fell within the range of 0.5 to 2.0. When OLA was co-administered with a strong or moderate CYP3A4 inhibitor, the recommended dosing regimens should be reduced to 100 mg BID and 150 mg BID, respectively. Additionally, the PBPK model also suggested that OLA could be not recommended with a strong or moderate CYP3A4 inducer. For patients with moderate hepatic and renal impairment, the dosing regimens of OLA were recommended to be reduced to 200 mg BID and 150 mg BID, respectively. In cases of severe hepatic and renal impairment, the PBPK model suggested a dosing regimen of 100 mg BID for OLA. Overall, this present PBPK model can determine the optimal dosing regimens for various clinical scenarios involving OLA.

Asia-Inclusive Clinical Research and Development Enabled by Translational Science and Quantitative Clinical Pharmacology: Toward a Culture That Challenges the Status Quo

Access lag to innovative therapies in Asian populations continues to present a challenge to global health. Recent progressive changes in the global regulatory landscape, including newer guidelines, are enabling simultaneous global drug development and near-simultaneous global drug registration. The International Conference on Harmonization (ICH) E17 guideline outlines general principles for the design and analysis of multiregional clinical trials (MRCTs). We posit that translational research and quantitative clinical pharmacology tools are core enablers for Asia-inclusive global drug development aligned with ICH E17 principles. Assessment of ethnic sensitivity should be initiated early in the development lifecycle to inform the need for, and extent of, Asian phase I ethno-bridging data. Relevant ethno-bridging data may be generated as standalone Asian phase I trials, as part of Western First-In-Human trials, or under accelerated development settings as a lead-in phase in an MRCT. Quantitative understanding of human clearance mechanisms and pharmacogenetic factors is vital to forecasting ethnic sensitivity in drug exposure using physiologically-based pharmacokinetic models. Stratification factors to control heterogeneity in MRCTs can be identified by reverse translational research incorporating pharmacometric disease models and model-based meta-analyses. Because epidemiological variations can extend to the molecular level, quantitative systems pharmacology models may be useful in forecasting how molecular variation in therapeutic targets or pathway proteins across populations might impact treatment outcomes. Through prospective evaluation of conservation in drug- and disease-related intrinsic and extrinsic factors, a pooled East Asian region can be implemented in Asia-inclusive MRCTs to maximize efficiency in substantiating evidence of benefit-risk for the region at-large with a Totality of Evidence approach.

Multi-phase multi-layer mechanistic dermal absorption (MPML MechDermA) model to predict local and systemic exposure of drug products applied on skin

Physiologically-based pharmacokinetic models combine knowledge about physiology, drug product properties, such as physicochemical parameters, absorption, distribution, metabolism, excretion characteristics, formulation attributes, and trial design or dosing regimen to mechanistically simulate drug pharmacokinetics (PK). The current work describes the development of a multiphase, multilayer mechanistic dermal absorption (MPML MechDermA) model within the Simcyp Simulator capable of simulating uptake and permeation of drugs through human skin following application of drug products to the skin. The model was designed to account for formulation characteristics as well as body site- and sex- population variability to predict local and systemic bioavailability. The present report outlines the structure and assumptions of the MPML MechDermA model and includes results from simulations comparing absorption at multiple body sites for two compounds, caffeine and benzoic acid, formulated as solutions. Finally, a model of the Feldene (piroxicam) topical gel, 0.5% was developed and assessed for its ability to predict both plasma and local skin concentrations when compared to in vivo PK data.

Assessment of the Utility of Physiologically-based Pharmacokinetic Model for prediction of Pharmacokinetics in Chinese and Japanese Populations

The objective for the present analyses was to evaluate the utility of physiologically-based pharmacokinetic (PBPK) modeling for prediction of the pharmacokinetics (PK) in Chinese and Japanese populations with a panel of Pfizer internal compounds. Twelve compounds from Pfizer internal development pipeline with available Westerner PK data and available PK data in at least one of the subpopulations of Japanese and Chinese populations were identified and included in the current analysis. These selected compounds represent various elimination pathways across different therapeutic areas. The Simcyp® PBPK simulator was used to develop and verify the PBPK models of individual compounds. The developed models for these compounds were verified by using the clinical PK data in Westerners. The verified PBPK models were further used to predict the PK of these compounds in Chinese and Japanese populations and the predicted PK parameters were compared with the observed PK parameters. Ten of the 12 compounds had PK data in Chinese, and all the 12 compounds had PK data in Japanese. In general, the PBPK models performed well in predicting PK in Chinese and Japanese, with 8 of 10 drugs in Chinese and 7 of 12 drugs in Japanese has AAFE values less than 1.25-fold. PBPK-guided predictions of the relative PK difference were successful for 75% and 50%, respectively, between Chinese and Western and between Japanese and Western of the tested drugs using 0.8-1.25 as criteria. In conclusion, well verified PBPK models developed using data from Westerners can be used to predict the PK in Chinese and Japanese populations.

Pharmacokinetics and safety of rilpivirine in healthy Japanese subjects and exploration of ethnic sensitivity of rilpivirine pharmacokinetics with physiologically based pharmacokinetic model approach

Rilpivirine is a non-nucleoside reverse transcriptase inhibitor, used for the treatment of human immunodeficiency virus type-1 infection. An open label study was conducted to investigate the pharmacokinetics (PK) and safety of a single oral dose of rilpivirine 25 mg in Japanese healthy adult subjects. No adverse events were reported. The mean C_max (144.3 ng/mL) and AUC_inf (4542 ng h/mL) in Japanese subjects were approximately 30 % higher than those reported from a similar study in Caucasian healthy subjects, whereas the median t_max and mean t_1/2 values were comparable between studies. A simple physiologically based PK model was developed to characterize the rilpivirine PK profile. The model adequately described rilpivirine PK profiles, and well-predicted drug-drug interactions. With exploration using the model, body size and CYP3A4 abundance were identified as factors which explained the observed inter-ethnic difference in rilpivirine exposure. The inter-ethnic difference in rilpivirine exposure was however considered not clinically relevant, since inter-individual variabilities of those intrinsic factors are larger than inter-ethnic ones; and the observed AUC_inf in Japanese subjects was within the range of AUC_tau associated with efficacy and safety in Phase 3 studies. This study results support the use of rilpivirine without dose modification specific to Japanese patients.

Physiologically-based pharmacokinetic model predictions of inter-ethnic differences in imatinib pharmacokinetics and dosing regimens

AIMS

This study implements a physiologically-based pharmacokinetic (PBPK) modelling approach to investigate inter-ethnic differences in imatinib pharmacokinetics and dosing regimens.

METHODS

A PBPK model of imatinib was built in the Simcyp Simulator (version 17) integrating in vitro drug metabolism and clinical pharmacokinetic data. The model accounts for ethnic differences in body size and abundance of drug-metabolising enzymes and proteins involved in imatinib disposition. Utility of this model for prediction of imatinib pharmacokinetics was evaluated across different dosing regimens and ethnic groups. The impact of ethnicity on imatinib dosing was then assessed based on the established range of trough concentrations (C_ss,min ).

RESULTS

The PBPK model of imatinib demonstrated excellent predictive performance in describing pharmacokinetics and the attained C_ss,min in patients from different ethnic groups, shown by prediction differences that were within 1.25-fold of the clinically-reported values in published studies. PBPK simulation suggested a similar dose of imatinib (400-600 mg/d) to achieve the desirable range of C_ss,min (1000-3200 ng/mL) in populations of European, Japanese and Chinese ancestry. The simulation indicated that patients of African ancestry may benefit from a higher initial dose (600-800 mg/d) to achieve imatinib target concentrations, due to a higher apparent clearance (CL/F) of imatinib compared to other ethnic groups; however, the clinical data to support this are currently limited.

CONCLUSION

PBPK simulations highlighted a potential ethnic difference in the recommended initial dose of imatinib between populations of European and African ancestry, but not populations of Chinese and Japanese ancestry.

Elucidation of Metabolic and Disposition Pathways for Maribavir in Nonhuman Primates through Mass Balance and Semi-Physiologically Based Modeling Approaches

Maribavir is in phase 3 clinical development for treatment of cytomegalovirus infection/disease in transplant recipients. Previous research conducted using only intact cynomolgus monkeys indicated biliary secretion as the primary elimination pathway for maribavir and that maribavir undergoes enterohepatic recirculation (EHR). To clarify the exact mechanisms of maribavir's EHR behavior, we studied its clearance pathways using intravenously administered ¹⁴C-labeled maribavir in intact and bile duct-cannulated (BDC) monkeys and constructed a semi-physiologically based pharmacokinetic (PBPK) model. Total radioactivity metabolite profiles in plasma and excreta were quantitatively determined along with plasma maribavir concentrations. Intact animals showed significantly lower clearance and longer half-lives in both total radioactivity and parent concentration in plasma than BDC monkeys. The primary in vitro and in vivo metabolic pathway for maribavir in monkey is direct glucuronidation; N-dealkylation and renal clearance are minor pathways. In BDC monkeys, 73% of dose was recovered as maribavir glucuronides in bile, and 3% of dose was recovered as parent in bile and feces; in intact animals' feces, 58% of dose was recovered as parent, and no glucuronides were detected. Therefore, EHR of maribavir occurs through biliary secretion of maribavir glucuronides, and this is followed by hydrolysis of glucuronides in the gut lumen and subsequent reabsorption of parent. A semi-PBPK model constructed from physiologic, in vitro, and in vivo BDC monkey data is capable of projecting maribavir's pharmacokinetic and EHR behavior in intact animals after intravenous or oral dosing and could be applied to modeling other xenobiotics that are subject to similar EHR processes. SIGNIFICANCE STATEMENT: Through both mass balance and semi-physiologically based pharmacokinetic (semi-PBPK) modeling approaches, this study mechanistically and quantitatively elucidates maribavir's enterohepatic recirculation (EHR) behavior in monkeys, which occurs via extensive direct glucuronidation, biliary secretion of these glucuronides, luminal hydrolysis of glucuronides to parent, and subsequent reabsorption of the parent. The study also identifies important drug- and animal-specific parameters that determine the EHR kinetics, and the semi-PBPK model is readily applicable to other drugs that undergo similar metabolic and recirculation mechanisms.

Prediction of Fluoxetine and Norfluoxetine Pharmacokinetic Profiles Using Physiologically Based Pharmacokinetic Modeling

Fluoxetine is a selective serotonin reuptake inhibitor that is metabolized to norfluoxetine by cytochrome P450 (CYP) 2D6, CYP2C19, and CYP3A4. A physiologically based pharmacokinetic model for fluoxetine and norfluoxetine metabolism was developed to predict and investigate changes in concentration-time profiles according to fluoxetine dosage in the Korean population. The model was developed based on the Certara repository model and information gleaned from the literature. Digitally extracted clinical study data were used to develop and verify the model. Simulations for plasma concentrations of fluoxetine and norfluoxetine after a single dose of 60 or 80 mg fluoxetine were made based on 1000 virtual healthy Korean individuals using the SimCYP version 19 simulator. The mean ratios (simulated/observed) after a single administration of 80 mg fluoxetine for maximum plasma concentration, area under the plasma concentration-time curve, and apparent clearance were 1.12, 1.08, and 0.93 for fluoxetine; the ratios of maximum plasma concentration and area under the plasma concentration-time curve were 1.08 and 1.08, respectively, for norfluoxetine, indicating that the simulated concentration-time profiles of fluoxetine and norfluoxetine fitted the observed profiles well. The developed model was used to predict plasma fluoxetine and norfluoxetine concentration-time profiles after repeated administrations of fluoxetine in Korean volunteers. This physiologically based pharmacokinetic model could provide basic understanding of the pharmacokinetic profiles of fluoxetine and its metabolite under various situations.

Physiologically-based pharmacokinetic model for clozapine in Korean patients with schizophrenia

Clozapine has been used as a treatment of schizophrenia. Despite its large interindividual variability, few reports addressed the physiologically-based pharmacokinetic modeling and simulation (PBPK M&S) of clozapine in patients. This study aimed to develop a PBPK M&S of clozapine in Korean patients with schizophrenia. PBPK modeling for clozapine was constructed using a population-based PBPK platform, the SimCYP^® Simulator (V19; Certara, Sheffield, UK). The PBPK model was developed by optimizing the physiological parameters of the built-in population and compound libraries in the SimCYP^® Simulator. The model verification was performed with the predicted/observed ratio for pharmacokinetic parameters and visual predictive checks (VPCs) plot. Simulations were performed to predict toxicities according to dosing regimens. From published data, 230 virtual trials were simulated for each dosing regimen. The predicted/observed ratio for the area under the curve and peak plasma concentration was calculated to be from 0.78 to 1.34. The observation profiles were within the 5th and 95th percentile range with no serious model misspecification through the VPC plot. A significant impact on age and gender was found for clozapine clearance. The simulation results suggested that 150 mg twice a day and 150 mg three times a day of clozapine have toxicity concerns. In conclusion, a PBPK model was developed and reasonable parameters were made from the data of Korean patients with schizophrenia. The provided model might be used to predict the pharmacokinetics of clozapine and assist dose adjustment in clinical settings.

Physiologically based pharmacokinetic (PBPK) modeling of RNAi therapeutics: Opportunities and challenges

Physiologically based pharmacokinetic (PBPK) modeling is a powerful tool with many demonstrated applications in various phases of drug development and regulatory review. RNA interference (RNAi)-based therapeutics are a class of drugs that have unique pharmacokinetic properties and mechanisms of action. With an increasing number of RNAi therapeutics in the pipeline and reaching the market, there is a considerable amount of active research in this area requiring a multidisciplinary approach. The application of PBPK models for RNAi therapeutics is in its infancy and its utility to facilitate the development of this new class of drugs is yet to be fully evaluated. From this perspective, we briefly discuss some of the current computational modeling approaches used in support of efficient development and approval of RNAi therapeutics. Considerations for PBPK model development are highlighted both in a relative context between small molecules and large molecules such as monoclonal antibodies and as it applies to RNAi therapeutics. In addition, the prospects for drawing upon other recognized avenues of PBPK modeling and some of the foreseeable challenges in PBPK model development for these chemical modalities are briefly discussed. Finally, an exploration of the potential application of PBPK model development for RNAi therapeutics is provided. We hope these preliminary thoughts will help initiate a dialogue between scientists in the relevant sectors to examine the value of PBPK modeling for RNAi therapeutics. Such evaluations could help standardize the practice in the future and support appropriate guidance development for strengthening the RNAi therapeutics development program.