A population pharmacokinetic model for posaconazole intravenous solution and oral powder for suspension formulations in pediatric patients with neutropenia

The objective of this study was to support posaconazole dose regimens in pediatric patients aged ≥2 years, using a population pharmacokinetic (PK) approach with data from a phase 1b study (NCT02452034). A one-compartment model with first-order absorption was fit to pharmacokinetic data from 144 participants aged 2 to 17 years, who were administered posaconazole as intravenous (IV) and powder for oral suspension (PFS) formulations, or IV only, at dosing regimens of 3.5, 4.5, and 6 mg/kg. The influence of demographic and clinical factors on pharmacokinetic parameters was evaluated using a stepwise forward inclusion/backward exclusion procedure. The final model simulated posaconazole exposure in patients aged 2 to <7 and 7 to 17 years at dosing regimens of 4.5, 6, and 7.5 mg/kg. Plasma concentration data following IV and PFS administration were well-described by a one-compartment model with first-order absorption and estimated bioavailability, where clearance and volume were subject to allometric scaling by body weight. The 6-mg/kg dosing regimen achieved the pharmacokinetic target (90% of the pediatric population having an average steady-state plasma concentration of ≥500 and <2,000 ng/mL) for both age groups, regardless of whether patients received IV and PFS or IV only. In a virtual adolescent population (body weight >40 kg), the 300 mg/day posaconazole tablet was also predicted to achieve the pharmacokinetic target and remain within a safe range of exposure. These data informed a weight-based nomogram for PFS dosing to maximize the number of pediatric patients achieving the pharmacokinetic target across weight bands, while also maintaining a favorable benefit/risk profile.

Population Pharmacokinetic and Exposure-Response Analyses From ALTA-1L: Model-Based Analyses Supporting the Brigatinib Dose in ALK-Positive NSCLC

The ALK in Lung Cancer Trial of brigAtinib in 1st Line (ALTA-1L) compared brigatinib versus crizotinib in ALK inhibitor-naive patients with ALK+ NSCLC. A population pharmacokinetic (PK) model was used to estimate brigatinib exposures for exposure-efficacy and exposure-safety analyses in ALTA-1L. A previously developed population PK model for brigatinib was applied to estimate brigatinib PK parameters. Relationships between static (time-independent) and dynamic (time-varying) exposure metrics and efficacy (progression-free survival [PFS], objective response rate [ORR], and intracranial ORR) and safety outcomes (selected grade ≥ 2 and grade ≥ 3 adverse events) were evaluated using logistic regression and time-to-event analyses. There were no meaningful differences in brigatinib PK in the first-line and second-line settings, supporting use of the previous population PK model for the first-line population. Exposure-response analyses showed no significant effect of time-varying brigatinib exposure on PFS. Brigatinib exposure was not significantly related to ORR, but higher exposure was associated with higher intracranial ORR (odds ratio: 1.13; 95% confidence interval: 1.01-1.28; P = 0.049). Across the observed median exposure (5th-95th percentile) at steady state for 180 mg once daily, the predicted probability of intracranial ORR was 0.83 (0.58-0.99). Adverse events significantly associated with higher exposure were elevated lipase (grade ≥ 3) and amylase (grade ≥ 2). Time to first brigatinib dose reduction was not related to exposure. These results support the benefit-risk profile of first-line brigatinib 180 mg once daily (7-day lead-in dose at 90 mg once daily) in patients with ALK+ NSCLC.

Population Pharmacokinetics of TAK-931, a Cell Division Cycle 7 Kinase Inhibitor, in Patients With Advanced Solid Tumors

A population pharmacokinetic (PK) analysis was conducted to characterize sources of interpatient variability on the PK of TAK‐931, a cell division cycle 7 kinase inhibitor, in adult patients with advanced solid tumors using data from 198 patients who received oral TAK‐931 over the range of 30 to 150 mg once daily in multiple dosing schedules in 2 phase 1 and 1 phase 2 clinical studies. A 2‐compartment model with 2 transit compartments describing the absorption and first‐order linear elimination adequately described the PK of TAK‐931. The apparent oral clearance (CL/F) of TAK‐931 was estimated to be 38 L/h, and the terminal half‐life was estimated to be approximately 6 hours. Creatinine clearance (CrCL) was identified as a covariate on CL/F, and body weight as a covariate on CL/F, apparent central volume of distribution, and apparent intercompartmental clearance. Simulations using the final model indicated that the effect of CrCL (≥35 mL/min) or body weight (29.8‐127 kg) on TAK‐931 systemic exposures was not considered clinically meaningful, suggesting that no dose adjustments were necessary to account for body weight or renal function (CrCL ≥35 mL/min). Sex, age (36‐88 years), race, and mild hepatic impairment had no impact on the CL/F of TAK‐931. Taken together, the population PK analysis supports the same starting dose of TAK‐931 in Asian and Western cancer patients in a global setting.

Population pharmacokinetic (PK) and exposure-response analyses from the pivotal ALTA-1L study: Model-based analyses supporting the brigatinib dose in patients with anaplastic lymphoma kinase (ALK)–positive non–small cell lung cancer (NSCLC)

e21725

Background: Brigatinib is a next-generation ALK tyrosine kinase inhibitor (TKI) with differential activity by dose (90 mg vs 180 mg [with a 7-day lead-in at 90 mg] qd) in the phase 2 post-crizotinib ALTA trial (NCT02094573). Herein, we describe results from population PK and exposure-response analyses of the efficacy and safety of brigatinib 180 mg qd (with a 7-day lead-in at 90 mg) from data in the first-line phase 3 ALTA-1L study (NCT02737501). Methods: Brigatinib plasma concentration-time data were described by a 3-compartment model with transit compartment absorption. Post hoc individual apparent clearance estimates for brigatinib were obtained using Bayesian re-estimation and used to calculate time-averaged area under the concentration-time curve (AUC) values for logistic regression analyses of relationships to response endpoints (confirmed objective response rate [ORR], intracranial ORR) and time-varying AUC values for parametric time-to-event models of relationships to progression-free survival (PFS). Population PK modeling, covariate analysis, and simulations were performed using NONMEM (version 7.3 or higher), running under PsN (Perl-speaks-NONMEM, version 4.6 or higher), while exposure–efficacy and safety analyses were performed using R (version 3.5.2 or higher). Results: Brigatinib PK parameters and estimated systemic exposures for patients in ALTA-1L (ALK TKI–naive setting) were similar to those in the 180 mg qd arm of ALTA. Patient covariates including weight, sex, age, race, and renal function (CrCL ≥30 mL/min) were not found to impact brigatinib exposure, suggesting no dose adjustment based on these covariates. In the exposure-response analyses, brigatinib exposure was not a significant predictor of response (≥partial response) or PFS. This suggests that the efficacy benefit was consistent across the range of exposures achieved with the 180 mg dosing regimen including after dose modifications. There was a significant relationship ( P< 0.05) between exposure and certain laboratory abnormalities (increased amylase and lipase). There was no relationship between exposure and CPK elevation, and brigatinib exposure had no effect on time to first dose reduction. Conclusions: These results support a favorable benefit/risk profile of the proposed 180 mg qd brigatinib dose (with a 7-day lead-in at 90 mg) for the front-line treatment of patients with ALK+ NSCLC. Clinical trial information: NCT02737501.

Modeling and predicting optimal treatment scheduling between the antiangiogenic drug sunitinib and irinotecan in preclinical settings

We present a system of nonlinear ordinary differential equations used to quantify the complex dynamics of the interactions between tumor growth, vasculature generation, and antiangiogenic treatment. The primary dataset consists of longitudinal tumor size measurements (1,371 total observations) in 105 colorectal tumor‐bearing mice. Mice received single or combination administration of sunitinib, an antiangiogenic agent, and/or irinotecan, a cytotoxic agent. Depending on the dataset, parameter estimation was performed either using a mixed‐effect approach or by nonlinear least squares. Through a log‐likelihood ratio test, we conclude that there is a potential synergistic interaction between sunitinib when administered in combination with irinotecan in preclinical settings. Model simulations were then compared to data from a follow‐up preclinical experiment. We conclude that the model has predictive value in identifying the therapeutic window in which the timing between the administrations of these two drugs is most effective.

Preclinical Modeling of Tumor Growth and Angiogenesis Inhibition to Describe Pazopanib Clinical Effects in Renal Cell Carcinoma

The objective was to leverage tumor size data from preclinical experiments to propose a model of tumor growth and angiogenesis inhibition for the analysis of pazopanib efficacy in renal cell carcinoma (RCC) patients. We analyzed tumor data in mice with RCC CAKI‐2 cell line treated with pazopanib. Clinical tumor size data obtained in a subset of patients with RCC were also analyzed. A model accounting for the processes of tumor growth, angiogenesis, and drug effect was developed. The final tumor model was composed of two variables: the tumor and its vasculature. Our results show that, both in mice and in humans, pazopanib exhibits a dual mechanism of action, and parameter estimation values highlight the inherent difference between mice and humans on the time scale of tumor size response. We developed a semimechanistic tumor growth inhibition model that takes into account tumor angiogenesis in order to describe the effects of pazopanib in mice. Analyzing rich preclinical data with a semimechanistic model may be a relevant approach to facilitate the description of sparse clinical longitudinal tumor size data and to provide insights for the understanding of the drug mechanisms of action in patients.