Model-Based Meta-Analysis for Comparative Efficacy and Safety: Application in Drug Development and Beyond

Abstract

High development cost, low development success, cost-disciplined health-care policies, and intense competition demand an efficient drug development process. New compounds need to bring value to patients by being safe, efficacious, and cost-effective as compared with existing treatment options. Model-based meta-analysis (MBMA) facilitates integration and utilization of summary-level efficacy and safety data, providing a quantitative framework for comparative efficacy and safety assessment. This Commentary discusses the application and limitations of MBMA in drug development.

Pharmacometric Approaches to Guide Dose Selection of the Novel GPR40 Agonist TAK‐875 in Subjects With Type 2 Diabetes Mellitus

“…A model-based meta-analysis used controlled clinical trials from the medical literature, the Food and Drug Administration, and the European Medicines Agency. 34 Clinical outcomes data from 74 prospective randomized clinical trials, with >36,300 patients and 208 different randomized treatment arms, were included in this model-based meta-analysis on efficacy of glimepiride and DPP-4 inhibitors (alogliptin, linagliptin, saxagliptin, sitagliptin, and vildagliptin). For TAK-875, data from a randomized placebo-controlled phase 2 study (excluding glimepiride arm) were evaluated.…”

“…34,35,36 Changes in HbA1c in a given treatment arm ( j ) of a trial ( i ) (HbA1c ij ) at time T were modeled as a function of the placebo response for HbA1c in that trial ( E 0, i,T ), i.e., the intercept, and a dose–response relationship for treatment effects on HbA1c (g(x)). Covariates ( X ij ) and trial-specific model parameters ( θ i ) were included and evaluated according to the following general structure:…”

Clinical pharmacology considerations in biologics development

“…Another modelling tool that has been increasingly used is meta-analysis. Meta-analysis synthesises reported clinical data from drugs in the same class to enrich the information for the dose/exposure response of the drug candidate in development [26][27][28][29] and also provides a benchmark for comparison purposes. Simultaneous modelling of exposure-PD response, PD response-clinical response, and exposure/PD response-clinical response has been considered to be an ideal approach for dosing regimen justification.…”

A review of methods for comparing treatments evaluated in studies that form disconnected networks of evidence

“…A 2‐stranded approach was used to systematically review evidence synthesis methods in the scientific literature that allow comparisons to be made between treatments across disconnected networks of evidence (Figure ). This entailed keyword searching of the MEDLINE database (via OvidSP) and pearl growing based on citation searching of 11 published journal articles dealing with novel approaches to making indirect comparisons between treatments forming disconnected networks …”