A population pharmacokinetic-pharmacodynamic model of navtemadlin, its glucuronide metabolite (M1) and serum macrophage inhibitory cykokine-1 (MIC-1).

Navtemadlin is a potent, selective, orally available inhibitor of murine double minute 2 that restores p53 activity to induce apoptosis in wild-type malignancies. Using richly sampled pharmacokinetic (PK) and pharmacodynamic (PD) data from healthy volunteers, a population PK/PD model was developed.A population PK (PPK) model described the PK characteristics of navtemadlin and its major metabolite acyl glucuronide (M1) and quantified enterohepatic recirculation (EHR).

Phase 1 Concentration-QTc and Cardiac Safety Analysis of the MDM2 Antagonist KRT-232 in Patients With Advanced Solid Tumors, Multiple Myeloma, or Acute Myeloid Leukemia.

Cardiac safety and plasma concentration-QTc interval analyses were completed using data from 2 phase 1 studies of the selective mouse double minute chromosome 2 antagonist, KRT-232, in patients with solid tumors or multiple myeloma and acute myeloid leukemia (AML) who received KRT-232 doses of 15 to 480 mg once daily (QD; N = 130). A linear mixed-effects model related change from baseline Fridericia-corrected QT interval (ΔQTcF) to KRT-232 plasma concentrations. The final model included parameters for the intercept (with between-subject variability), KRT-232 concentration-ΔQTcF slope, and baseline QTcF effect on the intercept.

Estimating the Population Health Impact of Recently Introduced Modified Risk Tobacco Products: A Comparison of Different Approaches.

Introduction: Various approaches have been used to estimate the population health impact of introducing a Modified Risk Tobacco Product (MRTP).

Aims And Methods: We aimed to compare and contrast aspects of models considering effects on mortality that were known to experts attending a meeting on models in 2018.

Results: Thirteen models are described, some focussing on e-cigarettes, others more general.

Exposure-Response-Based Product Profile-Driven Clinical Utility Index for Ipatasertib Dose Selection in Prostate Cancer.

The aims of this work were to characterize ipatasertib exposure-response (E-R) relationships in a phase II study and to quantitatively assess benefit-risk using a clinical utility index approach to support ipatasertib phase III dose selection in patients with metastatic castration-resistant prostate cancer. Logistic regression and Cox proportional-hazards models characterized E-R relationships for safety and efficacy endpoints, respectively. Exposure metrics with and without considering dose interruptions/reductions (modifications) were tested in the E-R models.

Population Modeling of Modified Risk Tobacco Products Accounting for Smoking Reduction and Gradual Transitions of Relative Risk.

Introduction: As suggested by the Food and Drug Administration (FDA) Modified Risk Tobacco Product (MRTP) Applications Draft Guidance, we developed a statistical model based on public data to explore the effect on population mortality of an MRTP resulting in reduced conventional cigarette smoking. Many cigarette smokers who try an MRTP persist as dual users while smoking fewer conventional cigarettes per day (CPD). Lower-CPD smokers have lower mortality risk based on large cohort studies.

Population pharmacokinetic analysis of axitinib in healthy volunteers.

Aims: Axitinib is a potent and selective second generation inhibitor of vascular endothelial growth factor receptors 1, 2 and 3 approved for second line treatment of advanced renal cell carcinoma. The objectives of this analysis were to assess plasma pharmacokinetics and identify covariates that may explain variability in axitinib disposition following single dose administration in healthy volunteers.

Methods: Plasma concentration-time data from 337 healthy volunteers in 10 phase I studies were analyzed, using non-linear mixed effects modelling (nonmem) to estimate population pharmacokinetic parameters and evaluate relationships between parameters and food, formulation, demographic factors, measures of renal and hepatic function and metabolic genotypes (UGT1A1*28 and CYP2C19).

Axitinib in metastatic renal cell carcinoma: results of a pharmacokinetic and pharmacodynamic analysis.

Axitinib is a potent and selective inhibitor of vascular endothelial growth factor receptors 1, 2, and 3, approved for second-line therapy for advanced renal cell carcinoma (RCC). Axitinib population pharmacokinetic and pharmacokinetic/pharmacodynamic relationships were evaluated. Using nonlinear mixed effects modeling with pooled data from 383 healthy volunteers, 181 patients with metastatic RCC, and 26 patients with other solid tumors in 17 trials, the disposition of axitinib was best described by a 2-compartment model with first-order absorption and a lag time, with estimated mean systemic clearance (CL) of 14.

Relationship between exposure to sunitinib and efficacy and tolerability endpoints in patients with cancer: results of a pharmacokinetic/pharmacodynamic meta-analysis.

Purpose: In this pharmacokinetic/pharmacodynamic meta-analysis, we investigated relationships between clinical endpoints and sunitinib exposure in patients with advanced solid tumors, including patients with gastrointestinal stromal tumor (GIST) and metastatic renal cell carcinoma (mRCC).

Methods: Pharmacodynamic data were available for 639 patients of whom 443 had pharmacokinetic data. Sunitinib doses ranged from 25 to 150 mg QD or QOD.

A pharmacokinetic-pharmacodynamic model to optimize the phase IIa development program of maraviroc.

Objectives: To use a viral dynamics model to compare the effectiveness of in vivo viral inhibition of several doses of maraviroc (MVC;UK-427,857) and to use a modeling approach to support design decisions for a monotherapy study using various dosing regimens of maraviroc given with and without food.

Design: The pharmacokinetic-pharmacodynamic model was developed using clinical data from a first monotherapy study (study A4001007). This was a randomized, double-blind, placebo-controlled, multicenter study of maraviroc in 44 asymptomatic HIV-1-infected patients.

Combining drug-disease and economic modelling to inform drug development decisions.

Drug-disease models and clinical trial simulations are increasingly being used to support trial design and treatment optimization decisions. Less widely recognized is their potential for guiding strategic development decisions. These decisions require economic valuation of the potential product profile of efficacy, safety, ease of use, and so on.