The development of novel tuberculosis (TB) multi-drug regimens that are more efficacious and of shorter duration requires a robust drug development pipeline. Advances in quantitative modeling and simulation can be used to maximize the utility of patient-level data from prior and contemporary clinical trials, thus optimizing study design for anti-TB regimens. This perspective article highlights the work of seven project teams developing first-in-class translational and quantitative methodologies that aim to inform drug development decision-making, dose selection, trial design, and safety assessments, in order to achieve shorter and safer therapies for patients in need. These tools offer the opportunity to evaluate multiple hypotheses and provide a means to identify, quantify, and understand relevant sources of variability, to optimize translation and clinical trial design. When incorporated into the broader regulatory sciences framework, these efforts have the potential to transform the development paradigm for TB combination development, as well as other areas of global health.
Keywords: Drug development; Modeling; Pharmacokinetic/pharmacodynamics (PK/PD); Simulation; Translational science; Tuberculosis (TB).
Copyright © 2016. Published by Elsevier Ltd.