Pharmacokinetic design optimization in children and estimation of maturation parameters: example of cytochrome P450 3A4.

The aim of this work was to determine whether optimizing the study design in terms of ages and sampling times for a drug eliminated solely via cytochrome P450 3A4 (CYP3A4) would allow us to accurately estimate the pharmacokinetic parameters throughout the entire childhood timespan, while taking into account age- and weight-related changes. A linear monocompartmental model with first-order absorption was used successively with three different residual error models and previously published pharmacokinetic parameters ("true values"). The optimal ages were established by D-optimization using the CYP3A4 maturation function to create "optimized demographic databases." The post-dose times for each previously selected age were determined by D-optimization using the pharmacokinetic model to create "optimized sparse sampling databases." We simulated concentrations by applying the population pharmacokinetic model to the optimized sparse sampling databases to create optimized concentration databases. The latter were modeled to estimate population pharmacokinetic parameters. We then compared true and estimated parameter values. The established optimal design comprised four age ranges: 0.008 years old (i.e., around 3 days), 0.192 years old (i.e., around 2 months), 1.325 years old, and adults, with the same number of subjects per group and three or four samples per subject, in accordance with the error model. The population pharmacokinetic parameters that we estimated with this design were precise and unbiased (root mean square error [RMSE] and mean prediction error [MPE] less than 11% for clearance and distribution volume and less than 18% for k(a)), whereas the maturation parameters were unbiased but less precise (MPE < 6% and RMSE < 37%). Based on our results, taking growth and maturation into account a priori in a pediatric pharmacokinetic study is theoretically feasible. However, it requires that very early ages be included in studies, which may present an obstacle to the use of this approach. First-pass effects, alternative elimination routes, and combined elimination pathways should also be investigated.

Model-Based Meta-Analysis Compares DAS28 Rheumatoid Arthritis Treatment Effects and Suggests an Expedited Trial Design for Early Clinical Development.

A nonlinear mixed effects modeling approach was used to conduct a model-based meta-analysis (MBMA) of longitudinal, summary-level, baseline-corrected 28-joint Disease Activity Score (ΔDAS28) clinical trial data from seven approved rheumatoid arthritis (RA) drugs (abatacept, adalimumab, certolizumab, etanercept, rituximab, tocilizumab, and tofacitinib), representing 130 randomized clinical trials in 27,355 patients. All of the drugs except tocilizumab were found to have relatively similar ΔDAS28 time courses and efficacy (baseline-corrected and placebo-corrected) at 24 weeks and beyond of approximately 0.87-1.3 units in the typical RA patient population. Tocilizumab was estimated to have a differentially greater response of 1.99 at 24 weeks, likely due to its disproportionate effect on the acute-phase cytokine interleukin-6. Baseline DAS28, disease duration, percentage of male participants, and the year of conduct of the trial were found to have statistically significant effects on the timing and/or magnitude of ΔDAS28 in the control arms. Clinical trial simulations using the present MBMA indicated that abatacept, certolizumab, etanercept, tocilizumab, and tofacitinib would be expected to have a greater than 70% probability of showing a statistically significant difference vs. control at Week 6 with a sample size of ~ 30 patients per arm. In future RA clinical trials, an interim analysis conducted as early as 6 weeks after treatment initiation, with relatively small sample sizes, should be sufficient to detect the ΔDAS28 treatment effect vs. placebo.

A population analysis of weight-related differences in lopinavir pharmacokinetics and possible consequences for protease inhibitor-naive and -experienced patients.

BACKGROUND: Lopinavir is a potent protease inhibitor (PI) used for the treatment of HIV infection. Different lopinavir target trough concentrations (C(troughs)) were previously determined according to patient treatment histories: 1 mg/l for PI-naive patients, and 4 and 5.7 mg/l for PI-experienced patients. However, the probability to achieve these target C(troughs) with the current 400 mg twice-daily or 800 mg once-daily doses of the new tablet form, and the influence of body weight on this probability are unknown. METHODS: A population pharmacokinetic model for lopinavir was developed using data from 424 HIV type-1-infected patients, and the final model was used to estimate the probability to achieve target C(troughs) via Monte Carlo simulations. RESULTS: A one-compartment model adequately described the data. Mean population estimates (percentage interindividual variability) were 4.61 l/h (36%) for apparent clearance (CL/F) and 63.2 l (70%) for apparent distribution volume. Body weight was found to explain the interindividual variability of lopinavir CL/F. Probability to achieve the 1 mg/l target C(trough) was >96% for the twice-daily dose and comprised between 80% and 90% for the once-daily dose. The probability to achieve the 4 and 5.7 mg/l target C(troughs) with the twice-daily dose significantly decreased when body weight increased (from 76% to 61% and from 56% to 37% respectively, for body weights increasing from 50 to 90 kg). CONCLUSIONS: These results support lopinavir therapeutic drug monitoring and the use of higher lopinavir doses for PI-pretreated patients.

Population analysis of the pregnancy-related modifications in lopinavir pharmacokinetics and their possible consequences for dose adjustment.

OBJECTIVES: To investigate the possible necessity of an increase in lopinavir dose during pregnancy in order to achieve the concentrations previously defined as predictive of virological efficacy. PATIENTS AND METHODS: Lopinavir pharmacokinetics were investigated by a population approach performed on 145 HIV-infected women, including 74 pregnant women. The final model was used to determine the probability of achievement of the target trough concentrations by Monte Carlo simulations. RESULTS: The typical population estimates (inter-individual variability %) of apparent clearance (CL/F) and volume of distribution were 4.38 L/h (24%) and 58.4 L (59%), respectively. Pregnancy associated with a gestational age >15 weeks and delivery were found to increase lopinavir CL/F by 39% and 58%, respectively. With the standard 400 mg twice-a-day regimen, the probability of reaching the 1 mg/L target trough concentration for protease inhibitor (PI)-naive patients was 99% and 96% for non-pregnant and pregnant women, respectively. An important decrease in the probability of achieving the 5.7 mg/L target trough concentration for salvage therapy was observed for non-pregnant women (55%), this decrease being even greater for pregnant women (21%). Raising the lopinavir dose to 600 mg twice daily increased these probabilities to 87% and 53% for non-pregnant and pregnant women, respectively. CONCLUSIONS: Modification of the lopinavir dose is unlikely to be required for PI-naive pregnant women; however, in pregnant women who have previously received a PI, therapeutic drug monitoring and/or empirical increasing of the dose should be considered.

Translational Model-Based Strategy to Guide the Choice of Clinical Doses for Antibody-Drug Conjugates.

This work proposes a model-based approach to help select the phase 1 dosing regimen for the antibody-drug conjugate (ADC) SAR408701 leveraging the available data for 2 other ADCs of the same construct: SAR3419 and SAR566658. First, monkey and human pharmacokinetic (PK) data of SAR566658 and SAR3419 were used to establish the appropriate allometric approach to be applied to SAR408701 monkey PK data. Second, a population pharmacokinetics-pharmacodynamics (PK-PD) model was developed to describe tumor volume evolution following SAR408701 injection in mice. Third, allometric approaches identified for SAR566658 and SAR3419 were applied to SAR408701 monkey PK data to predict the human PK profile. Both SAR566658 and SAR3419 human and monkey PK were best described by a 2-compartment linear model. The relative difference was less than 10% between predicted and observed clearance using allometric exponents of 0.75 and 1, respectively. Tumor volume evolution following SAR408701 injection was best described by a full Simeoni model with a plasma concentration threshold of 4.6 µg/mL for eradication in mice. Both allometric exponents were used to predict SAR408701 PK in human from PK in monkey and to identify the potential effective dosing regimens. This translational strategy may be a valuable tool to design future clinical studies for ADCs, to support selection of the most appropriate dosing regimen, and to estimate the minimal dose required to assure antitumor activity, according to the schedule used.

Topiramate pharmacokinetics in infants and young children: contribution of population analysis.

PURPOSE: To determine the range of topiramate (TPM) concentrations obtained in children under 4 with the recommended dosage regimen (3-9 mg/kg/day) and to compare them to adult target ranges. METHODS: The population pharmacokinetic model developed for TPM, with/without enzyme inducer antiepileptic drugs (EIAEDs) in children was used to determine dosage regimens providing AUC and trough concentrations (C(trough)s) within the adult ranges. RESULTS: TPM pharmacokinetics was described by a one-compartment model. EIAEDs increased the apparent clearance (CL/F) and age and body weight increased the apparent distribution volume (Vd/F). Mean population estimates (% CV interindividual variability) were 0.608/1.15 L/h (13%) for CL/F without/with EIAEDs, 28.6L (0.2%) for Vd/F and 1.4h(-1) (124%) for the absorption rate constant. Mean AUC(0-12h) reached with a 2mg/kg/day dosing regimen was within described range. A 6-16 mg/kg/day dose depending on age allowed reaching target C(trough) range with the highest probability. Combined EIAEDs led to a 2- and 3-fold decrease in AUC and C(trough), respectively. CONCLUSION: TPM dosage of 2/4 mg/kg/day (without/with EIEADs, respectively) provides the AUC reported in adults. In children under 4, alternative dosing regimen should be considered mainly when associated to EIAED to reach C(trough) comparable to adult values.