[Effects of multiple-trough sampling design and algorithm on the estimation of population and individual pharmacokinetic parameters].

The purpose of this study is to investigate the effects of multiple-trough sampling design and nonlinear mixed effect modeling (NONMEM) algorithm on the estimation of population and individual pharmacokinetic parameters. Oxcarbazepine and tacrolimus were used as one-compartment and two-compartment model drugs, respectively. Seven sampling designs were investigated using various number of trough concentrations per individual ranging from 1-4. Monte Carlo simulations were performed to produce state-steady trough concentrations. One-compartment model was used to fit simulated data from oxcarbazepine and tacrolimus. The accuracy and precision of the estimated parameters were evaluated using the median prediction error (PE), the median absolute PE and boxplot. The results indicated that trough concentrations could yield reliable estimates of apparent clearance (CL/F). For oxcarbazepine, as the number of trough concentrations per subject increased, the accuracy and precision of CL/F, between-subject variability (BSV) of CL/F and residual variability (RUV) tended to be improved. For tacrolimus, however, although no improvement were observed in the accuracy of CL/F and BSV of CL/F, the PE distribution ranges were significantly narrowed and the RUV estimates were less bias and imprecise. In terms of algorithm, Monte Carlo importance sampling (IMP) and IMP assisted by mode a posteriori estimation (IMPMAP) were consistently better than other methods. Additionally, the sampling design had no significant effects on the individual parameter estimates, which were only depended on the interaction between BSV and RUV in various algorithms. Decreased in BSV and RUV levels can improve the accuracy and precision of the estimation for both population and individual pharmacokinetic parameter estimates.

CBD and THC in Special Populations: Pharmacokinetics and Drug-Drug Interactions.

Cannabinoid use has surged in the past decade, with a growing interest in expanding cannabidiol (CBD) and delta-9-tetrahydrocannabinol (THC) applications into special populations. Consequently, the increased use of CBD and THC raises the risk of drug-drug interactions (DDIs). Nevertheless, DDIs for cannabinoids, especially in special populations, remain inadequately investigated. While some clinical trials have explored DDIs between therapeutic drugs like antiepileptic drugs and CBD/THC, more potential interactions remain to be examined. This review summarizes the published studies on CBD and THC-drug interactions, outlines the mechanisms involved, discusses the physiological considerations in pharmacokinetics (PK) and DDI studies in special populations (including pregnant and lactating women, pediatrics, older adults, patients with hepatic or renal impairments, and others), and presents modeling approaches that can describe the DDIs associated with CBD and THC in special populations. The PK of CBD and THC in special populations remain poorly characterized, with limited studies investigating DDIs involving CBD/THC in these populations. Therefore, it is critical to evaluate potential DDIs between CBD/THC and medications that are commonly used in special populations. Modeling approaches can aid in understanding these interactions.

Population pharmacokinetics of FCN-159, a MEK1/2 inhibitor, in adult patients with advanced melanoma and neurofibromatosis type 1 (NF1) and model informed dosing recommendations for NF1 pediatrics.

Objective: FCN-159 is a highly active mitogen-activated extracellular signal-regulated kinase 1/2 (MEK1/2) inhibitor in patients with advanced melanoma and neurofibromatosis type 1 (NF1). We report a population pharmacokinetic (PopPK) model-based analysis of FCN-159 and its application to inform dose selection for NF1 pediatric trials. Methods: PK data collected from patients with advanced melanoma and NF1 in two clinical studies (NCT03932253 and NCT04954001) were analyzed using a non-linear mixed effects model. The adult model was adapted by incorporating allometric scaling for PK projection in 2-17 years old children. Pediatric exposure in different body surface area (BSA) bins was simulated to identify nominal doses (i.e., dose amounts given as integers) and BSA bin cutoffs to achieve exposure comparable to adults' optimal exposure across the entire pediatric BSA range. Results: The final dataset consisted of 45 subjects with a total of 1030 PK samples. The PK of FCN-159 was well-described by a 2-compartment model with first-order linear elimination and delayed first-order absorption. Covariates, including BSA, age, sex, albumin, total protein, and cancer type, were identified as statistically significant predictors of FCN-159 disposition. Simulations based on the final model projected daily doses of 4 mg/m2 QD with optimized BSA bin cutoffs would allow fixed nominal doses within each bin and result in steady state exposure approximating the adult exposure observed at the recommended phase 2 dose (RP2D) in NF1, which is 8 mg QD. Conclusion: The developed population PK model adequately described the PK profile of FCN-159, which was adapted using allometric scaling to inform dose selection for NF1 pediatric trials.

Effect of Meal Timings and Meal Content on the AUC0-12h of Mycophenolic Acid: A Simulation Study.

Meal timings and content related to gallbladder emptying in the enterohepatic circulation are important for explaining the high variability in mycophenolic acid exposure. The limited sampling strategy (LSS) was established to estimate the area under the plasma concentration-time curve from time 0 to 12 hours (AUC0-12h ) of mycophenolic acid in therapeutic drug monitoring. The aim of this study is to investigate the effect of meal timings and content on the AUC0-12h of mycophenolic acid and to assess the influence of meals on LSS. A mycophenolic acid pharmacokinetic model with a mechanism-based enterohepatic circulation process was employed to perform simulations under various assumed meal scenarios. The simulations were compared to evaluate the effect of meal timings and meal content on mycophenolic acid AUC0-12h . Monte Carlo simulations were performed using the meal parameter with the greatest impact on mycophenolic acid AUC0-12h as a variable. The corresponding LSS equations were established, and the predictive performance was assessed. Both the meal timings and meal content affected the mycophenolic acid AUC0-12h , and the postdose fasting period had the greatest impact. The predictive performance of the LSS is sensitive to the postdose fasting period. Therefore, meal timings may improve the estimation of mycophenolic acid AUC0-12h and the efficacy of therapeutic drug monitoring.

Lower clearance of sodium tanshinone IIA sulfonate in coronary heart disease patients and the effect of total bilirubin: a population pharmacokinetics analysis.

This study developed a population pharmacokinetic model for sodium tanshinone IIA sulfonate (STS) in healthy volunteers and coronary heart disease (CHD) patients in order to identify significant covariates for the pharmacokinetics of STS. Blood samples were obtained by intense sampling approach from 10 healthy volunteers and sparse sampling from 25 CHD patients, and a population pharmacokinetic analysis was performed by nonlinear mixed-effect modeling. The final model was evaluated by bootstrap and visual predictive check. A total of 230 plasma concentrations were included, 137 from healthy volunteers and 93 from CHD patients. It was a two-compartment model with first-order elimination. The typical value of the apparent clearance (CL) of STS in CHD patients with total bilirubin (TBIL) level of 10 µmol(L-1 was 48.7 L(h-1 with inter individual variability of 27.4%, whereas that in healthy volunteers with the same TBIL level was 63.1 L(h-1. Residual variability was described by a proportional error model and estimated at 5.2%. The CL of STS in CHD patients was lower than that in healthy volunteers and decreased when TBIL levels increased. The bootstrap and visual predictive check confirmed the stability and validity of the final model. These results suggested that STS dosage adjustment might be considered based on TBIL levels in CHD patients.