The implications of model-informed drug discovery and development for tuberculosis

Drug Discov Today. 2017 Mar;22(3):481-486. doi: 10.1016/j.drudis.2016.09.004. Epub 2016 Sep 28.

Abstract

Despite promising advances in the field and highly efficacious first-line treatment, an estimated 9.6 million people are still infected with tuberculosis (TB). Innovative methods are required to effectively transition the growing number of compounds into novel combination regimens. However, progression of compounds into patients occurs despite the lack of clear understanding of the pharmacokinetic-pharmacodynamic (PKPD) relationships. The PreDiCT-TB consortium was established in response to the existing gaps in TB drug development. The aim of the consortium is to develop new preclinical tools in concert with an in silico model-based approach, grounded in PKPD principles. Here, we highlight the potential impact of such an integrated framework on the various stages of TB drug development and on the dose rationale for drug combinations.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Antitubercular Agents* / therapeutic use
  • Drug Approval
  • Drug Discovery*
  • Humans
  • Models, Theoretical*
  • Tuberculosis / drug therapy

Substances

  • Antitubercular Agents