Use of Developmental Midazolam and 1-Hydroxymidazolam Data with Pediatric Physiologically Based Modeling to Assess Cytochrome P450 3A4 and Uridine Diphosphate Glucuronosyl Transferase 2B4 Ontogeny In Vivo.

Pediatric physiologically based pharmacokinetics modeling in drug development has grown in the past decade but uncertainty remains regarding ontogeny of some drug metabolizing enzymes. In this study, a midazolam and 1-hydroxymidazolam physiologically based pharmacokinetic model (PBPK) model was developed and used to define the ontogeny for hepatic cytochrome P450 (CYP) 3A4 and uridine diphosphate glucuronosyl transferase (UGT) 2B4. Data for model development and pharmacokinetic studies on intravenous midazolam in adults and pediatrics were collated from the literature. The PBPK model was verified in the adult population and then used to compare the performance of two ontogeny profiles for CYP3A4 in terms of parent drug elimination in pediatrics. Four studies also published data on the 1-hydroxymidazolam, and this was used to evaluate the known ontogeny for UGT2B4.For midazolam elimination, the Upreti CYP3A4 ontogeny performed better than Salem; mean error (bias) and mean squared error (precision) were 0.14 and 0.064 compared with 0.69 and 1.21, respectively. For 1-hydroxymidazolam elimination, the Simcyp default ontogeny of UGT2B4 appeared to perform best for studies covering the age range 0.5 to 15.7 years, while for a study in younger ages 0 to 1 years it was the Badee UGT2B4 ontogeny. In preterm neonates, overall expression of UGT appeared to be around 10% of that in adults.Identifying the optimal model of CYP3A4 ontogeny is important for the regulatory use of PBPK. The results for midazolam are conclusive but research about other CYP3A4 metabolized compounds will underpin generalizability of the CYP3A4 ontogeny. UGT2B4 ontogeny is less certain, but this study indicates the most likely scenarios. SIGNIFICANCE STATEMENT: A PBPK model for midazolam and 1-hydroxymidazolam was developed to test various ontogeny scenarios for CYP3A4 and UGT2B4. The CYP3A4 ontogeny of Upreti resulted in more accurate prediction of midazolam CL across nine clinical studies, age range birth to 18 years. 1-Hydroxy midazolam was used as a marker of UGT. The Simcyp default 'no ontogeny' profiles for UGT2B4 performed the best; however, for <1 year of age, there was some evidence of overactivity of this enzyme compared to adults.

Population pharmacokinetics of the MEK inhibitor selumetinib and its active N-desmethyl metabolite: data from 10 phase I trials.

AIMS: The aims of the study were to characterize the pharmacokinetics (PK) of selumetinib (AZD6244; ARRY-142886), a mitogen-activated protein kinase kinase (MEK) 1/2 inhibitor in clinical development for various indications, and its N-desmethyl metabolite in healthy volunteers, and evaluate clinically important covariates. METHODS: A pooled-population PK analysis was performed using a nonlinear mixed-effects approach with plasma concentration data from 346 subjects who received single oral doses of selumetinib 20-75 mg across 10 phase I studies. Absolute bioavailability was determined using intravenous [14 C] selumetinib. RESULTS: A two-compartment linear model with sequential zero-first order absorption and a lag time for the zero-order process was described for selumetinib PK. N-desmethyl metabolite disposition was described by a single compartment with linear elimination, without back transformation. The parent-only and joint models generally described pooled data adequately. For the median subject, not taking interacting drugs, estimates for clearance (CL) and central volume of distribution (V2) for selumetinib in the final joint model were 12.7 l h-1 and 35.6 l, respectively. Food effects, comedication with itraconazole [a cytochrome P450 (CYP) 3A4 inhibitor], fluconazole (a CYP2C19 inhibitor) and rifampicin (a CYP3A4 inducer) and formulation effects were incorporated into the base model a priori. Race and hepatic function were also influential in the PK model. Additional covariates affecting selumetinib disposition identified from covariate analysis were age on V2, bilirubin on CL, and weight on CL and V2. CONCLUSIONS: Analysis confirmed previous clinical pharmacology study findings of drug-drug interactions and food effects, with additional covariates that influence selumetinib and N-desmethyl selumetinib PK identified. Dose modifications based on these additional covariates were not considered necessary.

Development and application of a PBPK modeling strategy to support antimalarial drug development.

As part of a collaboration between Medicines for Malaria Venture (MMV), Certara UK and Monash University, physiologically-based pharmacokinetic (PBPK) models were developed for 20 antimalarials, using data obtained from standardized in vitro assays and clinical studies within the literature. The models have been applied within antimalarial drug development at MMV for more than 5 years. During this time, a strategy for their impactful use has evolved. All models are described in the supplementary material and are available to researchers. Case studies are also presented, demonstrating real-world development and clinical applications, including the assessment of the drug-drug interaction liability between combination partners or with co-administered drugs. This work emphasizes the benefit of PBPK modeling for antimalarial drug development and decision making, and presents a strategy to integrate it into the research and development process. It also provides a repository of shared information to benefit the global health research community.

Sources of interindividual variability in IVIVE of clearance: an investigation into the prediction of benzodiazepine clearance using a mechanistic population-based pharmacokinetic model.

Prediction of metabolic clearance in extreme individuals rather than the 'average human' is becoming an attractive tool within the pharmaceutical industry. The current study involved prediction of variability in metabolic clearance for alprazolam, triazolam and midazolam with emphasis on the following factors: first, evaluation of clearance prediction accuracy using intrinsic clearance (CL(int)) data from in vitro metabolic data and back-calculation from in vivo clearance data. Second, the sensitivity of predicted in vivo variability to changes in variability for physiological parameters (e.g. liver weight, haematocrit, CYP3A abundance). Finally, reported estimates of variability in hepatic CYP3A4 abundance (coefficient of variation (CV) 95%) were refined by separating experimental from interindividual variability using a repeat measurement protocol in 52 human liver samples. Using in vitro metabolic data, predicted clearances were within 2-fold of observed for triazolam and midazolam. Clearance of alprazolam was overpredicted by 2.0- to 3.7-fold. Use of in vivo CL(int) values improved prediction of intravenous clearance to within 2-fold of observed for all drugs. Initially, the variability in clearance was overestimated for all drugs (by 1.8- to 3.6-fold). Use of a reduced hepatic CYP3A4 CV of 41%, representative of interindividual variability alone improved predictions of variability in clearance for all drugs to within 2-fold of observed.

Evaluation of Drug-Drug Interaction Liability for Buprenorphine Extended-Release Monthly Injection Administered by Subcutaneous Route.

Buprenorphine extended-release (BUP-XR) formulation is a once-monthly subcutaneous injection for the treatment of opioid use disorder (OUD). Buprenorphine undergoes extensive cytochrome P450 (CYP) 3A4 metabolism, leading to potential drug-drug interactions (DDIs) as reported for sublingual buprenorphine. Sublingual buprenorphine is subject to first-pass extraction, as a significant proportion of the dose is swallowed. Because subcutaneous administration avoids first-pass extraction, the DDI with CYP3A4 inhibitors is expected to be less than the 2-fold increase reported for the sublingual route. The objective of this analysis was to predict the magnitude of DDI following coadministration of BUP-XR with a strong CYP3A4 inhibitor or inducer using physiologically based pharmacokinetic (PBPK) modeling. Models were developed and verified by comparing predicted and observed data for buprenorphine following intravenous and sublingual dosing. Comparison of predicted and observed pharmacokinetic (PK) profiles and PK parameters demonstrated acceptable predictive performance of the models (within 1.5-fold). Buprenorphine plasma concentrations following administration of a single dose of BUP-XR (300 mg) were simulated using a series of intravenous infusions. Daily coadministration of strong CYP3A4 inhibitors with BUP-XR predicted mild increases in buprenorphine exposures (AUC, 33%-44%; Cmax , 17-28%). Daily coadministration of a strong CYP3A4 inducer was also associated with mild decreases in buprenorphine AUC (28%) and Cmax (22%). In addition, the model predicted minimal increases in buprenorphine AUC (8%-11%) under clinical conditions of 2 weeks' treatment with CYP3A4 inhibitors administered after initiation of BUP-XR. In conclusion, the PBPK predictions indicate that coadministration of BUP-XR with strong CYP3A4 inhibitors or inducers would not result in clinically meaningful interactions.