Creation of Novel Sensitive Probe Substrate and Moderate Inhibitor Models for a Comprehensive Prediction of CYP2C8 Interactions for Tucatinib.

A physiologically-based pharmacokinetic (PBPK) model was developed to simulate plasma concentrations of tucatinib (TUKYSA®) after single-dose or multiple-dose administration of 300 mg b.i.d. orally. This PBPK model was subsequently applied to support evaluation of drug-drug interaction (DDI) risk as a perpetrator resulting from tucatinib inhibition of CYP3A4, CYP2C8, CYP2C9, P-gp, or MATE1/2-K. The PBPK model was also applied to support evaluation of DDI risk as a victim resulting from co-administration with CYP3A4 or CYP2C8 inhibitors, or a CYP3A4 inducer. After refinement with clinical DDI data, the final PBPK model was able to recover the clinically observed single and multiple-dose plasma concentrations for tucatinib when tucatinib was administered as a single agent in healthy subjects. In addition, the final model was able to recover clinically observed plasma concentrations of tucatinib when administered in combination with itraconazole, rifampin, or gemfibrozil as well as clinically observed plasma concentrations of probe substrates of CYP3A4, CYP2C8, CYP2C9, P-gp, or MATE1/2-K. The PBPK model was then applied to prospectively predict the potential perpetrator or victim DDIs with other substrates, inducers, or inhibitors. To simulate a potential interaction with a moderate CYP2C8 inhibitor, two novel PBPK models representing a moderate CYP2C8 inhibitor and a sensitive CYP2C8 substrate were developed based on the existing PBPK models for gemfibrozil and rosiglitazone, respectively. The simulated population geometric mean area under the curve ratio of tucatinib with a moderate CYP2C8 inhibitor ranged from 1.98- to 3.08-fold, and based on these results, no dose modifications were proposed for moderate CYP2C8 inhibitors for the tucatinib label.

Real-world application of PBPK in drug discovery.

The utility of PBPK models in support of drug development has been well documented. During the discovery stage, PBPK has increasingly been applied for early risk assessment, prediction of human dose, toxicokinetic dose projection and early formulation assessment. Previous review articles have proposed model building and application strategies for PBPK-based first in human predictions with comprehensive descriptions of the individual components of PBPK models. This includes the generation of decision trees, based on comprehensive literature reviews, to guide the application of PBPK in the discovery setting. The goal of this mini review is to provide additional guidance on the real-world application of PBPK, in support of the discovery stage of drug development. In this mini review, our goal is to provide guidance on the typical steps involved in the development and application of a PBPK model during drug discovery to assist in decision making. We have illustrated our recommended approach through description of case examples, where PBPK has been successfully applied to aid in human PK projection, candidate selection and prediction of drug interaction liability for parent and metabolite. Through these case studies, we have highlighted fundamental issues, including pre-verification in preclinical species, the application of empirical scalars in the prediction of in vivo clearance from in vitro systems, in silico prediction of permeability and the exploration of aqueous and biorelevant solubility data to predict dissolution. In addition, current knowledge gaps have been highlighted and future directions proposed. Significance Statement Through description of three case studies, we have highlighted the fundamental principles of PBPK application during drug discovery. These include pre-verification of the model in preclinical species, application of empirical scalars where necessary in the prediction of clearance, in silico prediction of permeability, and the exploration of aqueous and biorelevant solubility data to predict dissolution. In addition, current knowledge gaps have been highlighted and future directions proposed.

Physiologically Based Pharmacokinetic Modeling and Simulation of Mavacamten Exposure with Drug-Drug Interactions from CYP Inducers and Inhibitors by CYP2C19 Phenotype.

Mavacamten is a first-in-class, oral, selective, allosteric, reversible cardiac myosin inhibitor approved by the US Food and Drug Administration for the treatment of adults with symptomatic New York Heart Association functional class II-III obstructive hypertrophic cardiomyopathy. Mavacamten is metabolized in the liver, predominantly via cytochrome P450 (CYP) enzymes CYP2C19 (74%), CYP3A4 (18%), and CYP2C9 (8%). A physiologically-based pharmacokinetic (PBPK) model was developed using Simcyp version 19 (Certara, Princeton, NJ). Following model verification, the PBPK model was used to explore the effects of strong CYP3A4 and CYP2C19 inducers, and strong, moderate, and weak CYP2C19 and CYP3A4 inhibitors on mavacamten pharmacokinetics (PK) in a healthy population, with the effect of CYP2C19 phenotype predicted for poor, intermediate, normal, and ultrarapid metabolizers. The PBPK model met the acceptance criteria for all verification simulations (> 80% of model-predicted PK parameters within 2-fold of those observed clinically). A weak induction effect was predicted when mavacamten was administered with a strong CYP3A4 inducer in poor metabolizers. Moderate reductions in mavacamten exposure were predicted with a strong CYP2C19/CYP3A4 inducer in all CYP2C19 phenotypes. Except for the effect of strong CYP2C19 inhibitors on ultrarapid metabolizers, steady-state area under plasma concentration-time curve and maximum plasma concentration values were weakly affected (< 2-fold) or not affected (< 1.25-fold), regardless of CYP2C19 phenotype. In conclusion, a fit-for-purpose PBPK model was developed and verified, which accurately predicted the available clinical data and was used to simulate the potential impact of CYP induction and inhibition on mavacamten PKs, stratified by CYP2C19 phenotype.

Evaluation of the Potential for Drug-Drug Interactions with Inhaled Itraconazole Using Physiologically Based Pharmacokinetic Modelling, Based on Phase 1 Clinical Data.

Itraconazole is a potent inhibitor of cytochrome P450 3A4 (CYP3A4), associated with numerous drug-drug interactions (DDI). PUR1900, a dry powder formulation of itraconazole for oral inhalation, results in high lung and low systemic exposure. This project used physiologically based pharmacokinetic (PBPK) modeling to assess the DDI potential of inhaled PUR1900, using midazolam as a "victim drug." The basic and mechanistic static models evaluated the DDI potential of PUR1900, assuming 5 mg of midazolam coadministration at steady-state itraconazole exposure. Subsequently, Simcyp® PBPK simulation software and pharmacokinetic data from a Phase 1 clinical trial with PUR1900 (NCT03479411) were used to optimize an existing itraconazole PBPK model. The model was applied to investigate the potential for CYP3A4 DDI when 5 mg of midazolam is co-administered with inhaled PUR1900 at a steady state in a virtual healthy population at PUR1900 doses up to 40 mg per day. The basic static and mechanistic static models suggested a strong likelihood for DDI with inhaled PUR1900. The PBPK model was consistent with PUR1900 Phase 1 trial data. The geometric mean Cmax and AUC ratios of midazolam at a maximum dose of 40 mg PUR1900 were 1.14 and 1.26, respectively, indicating a minimal likelihood of DDI with inhaled PUR1900. The low systemic exposure of itraconazole when administered as PUR1900 results in minimal to no CYP3A4 inhibition, reducing the concern of drug-drug interactions. As the risk of CYP3A4 DDI is predicted to be significantly lower when itraconazole is administered via oral inhalation as PUR1900, it is likely that PUR1900 can be safely used for the treatment of pulmonary fungal infections in patients taking pharmaceuticals currently contraindicated with oral itraconazole.

Physiologically Based Pharmacokinetic Model Development and Verification for Bioequivalence Testing of Bempedoic Acid Oral Suspension and Reference Tablet Formulation.

The bioequivalence of bempedoic acid oral suspension and commercial immediate release (IR) tablet formulations were assessed using a physiologically based pharmacokinetic (PBPK) model. The mechanistic model, developed from clinical mass balance results and in vitro intrinsic solubility, permeability, and dissolution data, was verified against observed clinical pharmacokinetics (PK) results. Model inputs included a fraction of a dose in solution (0.01%), viscosity (118.8 cps), and median particle diameter (50 µm) for the suspension and particle diameter (36.4 µm) for IR tablets. Dissolution was determined in the relevant media (pH 1.2-6.8) in vitro. Model simulations of bioequivalence predicted oral suspension (test) to IR tablet (reference) geometric mean ratio estimates of 96.9% (90% confidence interval [CI]: 92.6-101) for maximum concentration and 98.2% (90% CI: 87.3-111) for the area under the concentration-time curve. Sensitivity analyses showed gastric transit time had a minor impact on model predictions. Oral suspension biopharmaceutical safe space was defined by extremes of particle size and the percent of bempedoic acid in solution. PBPK model simulations predicted that the rate and extent of bempedoic acid absorption are unlikely to exhibit clinically meaningful differences when dosed as an oral suspension compared with an IR tablet without requiring a clinical bioequivalence study in adults.

Pediatric Dose Selection and Utility of PBPK in Determining Dose.

Interest in determining safe and efficacious doses for drug administration in pediatric patients has increased dramatically in recent years. However, published pediatric clinical studies have failed to increase proportionally with adult clinical study publications. In order to assess the current state of pediatric dose determination and the supporting role of physiologically based pharmacokinetic modeling and simulation in determining pediatric dose, the pediatric clinical literature (2006-2016) and case examples of pediatric PBPK modeling efforts were reviewed. The objective of this assessment was to investigate the contribution of PBPK to our understanding of the differences between children and adults, which lead to differences in drug dose. Pediatric and adult dose data were available for 31 small molecule drugs. In general, pediatric dose was well-correlated with adult data, with an apparent tendency for higher body weight- or body surface area-normalized pediatric dose. Overall performance of pediatric PBPK modeling approaches was considered to adequately predict observed data. However, model performance was dependent upon age group simulated, with approximately half of neonatal predictions falling outside of 1.5-fold of observed. In conclusion, there is a clear need for further refinement of starting dose in pediatric phase 1 studies, and utilization of PBPK could lead to reduced numbers of patients required to establish safe and efficacious doses in the pediatric population.

MEK inhibitors beyond monotherapy: current and future development.

The development of MEK inhibitors has led to improved progression-free survival in patients with mutant BRAF(V600) cancers when used in combination with BRAF inhibitors. However, resistance to combination therapy remains an issue. This review summarizes our current understanding of the role of MEK in cancer cell proliferation and the mechanisms which lead to resistance in patients. Specific adverse events, which have been linked to the MEK inhibitor class, have been described. Future combinations of MEK inhibitors with other cancer therapy options, currently under investigation in clinical trials, are also discussed.

Predictive utility of in vitro rifampin induction data generated in fresh and cryopreserved human hepatocytes, Fa2N-4, and HepaRG cells.

Rifampin is a potent inducer of CYP3A4 in vitro and precipitates numerous drug-drug interactions (DDIs) when coadministered with CYP3A4 substrates. In the current study, we have critically assessed reported rifampin in vitro CYP3A4 induction data in Fa2N-4, HepaRG, and cryopreserved or primary human hepatocytes, using either CYP3A4 mRNA or probe substrate metabolism as induction endpoints. An in vivo data base of intravenously administered victim drugs (assuming hepatic induction only) was collated (n = 18) to assess the predictive utility of these in vitro systems and to optimize rifampin in vivo E(max). In addition, the effect of substrate hepatic extraction ratio on prediction accuracy was investigated using prediction boundaries proposed recently (Drug Metab Dispos 39:170-173). Incorporation of hepatic extraction ratio in the prediction model resulted in accurate prediction of 89% of intravenous induction DDIs (n = 18), regardless of the in vitro system or induction endpoint (mRNA or CYP3A4 activity). Effects of in vitro parameters from different cellular systems, and optimized in vivo E(max), on the prediction of 21 oral DDIs were assessed. Use of mRNA data resulted in pronounced overprediction across all systems, with 86 to 100% of DDIs outside the acceptable prediction limits; in contrast, CYP3A4 activity predicted up to 62% of the oral DDIs within limits. Although prediction accuracy of oral DDIs was improved when using intravenous optimized rifampin E(max), >35% of DDIs were incorrectly assigned, suggesting potential differential E(max) between intestine and liver. Implications of the findings and recommendations for prediction of rifampin DDIs are discussed.

Pharmacokinetics of valerenic acid after administration of valerian in healthy subjects.

OBJECTIVES: To describe the pharmacokinetics of valerenic acid in a group of healthy adults after a single oral dose of valerian using a newly developed sensitive assay for serum concentrations of valerenic acid, a commonly used marker for qualitative and quantitative analysis of valerian root and valerian products. STUDY DESIGN: Six healthy adults (22-61 years, five men, one female) received a single 600 mg dose of valerian at 08:00. Blood samples were collected for 8 h after administration. Valerenic acid was extracted from serum and measured using a LC/MS/MS method developed in our laboratory. RESULTS: The maximum serum concentration of valerenic acid for five of the six subjects occurred between 1 and 2 h ranging from 0.9 to 2.3 ng/mL. Valerenic acid serum concentrations were measurable for at least 5 h after the valerian dose. One subject showed a peak plasma value at 1 h and a second peak at 5 h. The elimination half-life (T(1/2)) for valerenic acid was 1.1 +/- 0.6 h. The area under the concentration time curve (AUC) as a measure of valerenic acid exposure was variable (4.80 +/- 2.96 microg/mL. h) and not correlated with subject's age or weight. CONCLUSIONS: Assuming that valerenic acid serum concentrations correlate with the pharmacological activity of valerian, the timing of the valerenic acid peak concentration is consistent with the standard dosage recommendation to take valerian 30 min to 2 h before bedtime. Ongoing studies are evaluating the relationship between valerenic acid serum concentrations and objective measures of sleep in patients.