Format

Send to

Choose Destination
J Infect Dis. 2015 Jun 15;211 Suppl 3:S83-95. doi: 10.1093/infdis/jiv183.

Nonclinical models for antituberculosis drug development: a landscape analysis.

Author information

1
Center for Infectious Diseases Research and Experimental Therapeutics, Baylor Research Institute, Baylor University Medical Center, Dallas, Texas Department of Medicine, University of Cape Town, South Africa.
2
Department of Microbiology, Immunology, and Pathology, Colorado State University, Ft. Collins.
3
Critical Path Institute, Tucson, Arizona.
4
Center for Tuberculosis Research, Johns Hopkins University, Baltimore, Maryland.

Abstract

BACKGROUND:

Several nonclinical drug-development tools (DDTs) have been used for antituberculosis drug development over several decades. The role of the DDTs used for evaluating the efficacy of antituberculosis drug combinations and the gaps in the evidence base for which new tools or approaches are needed are as yet undefined.

METHODS:

We performed a landscape analysis based on a comprehensive literature review to create evidence based guidelines.

RESULTS:

There are 3 important questions that a DDT should answer with regard to antituberculosis drugs: What combination(s) of drugs will be most effective? What dose(s) and schedule(s) of each drug should be administered? and What duration(s) of treatment will be efficacious? Four DDTs were identified as having a track record to answer these questions: in vitro susceptibility tests, the hollow fiber system model of tuberculosis, mice, and guinea pigs. No single nonclinical in vitro or animal model recapitulates all aspects of human tuberculosis. Therefore, a combination of models is recommended for drug development. Gaps identified include the need for standardization of nonclinical model experiments, evaluation of animal models with pathology more similar to that in humans, and identification of experimental quantitative output in the DDTs that correlates with sterilizing effect in humans.

CONCLUSIONS:

There is a need for formal quantitative analyses of how well DDTs forecast clinical outcomes.

KEYWORDS:

antituberculosis; drug development; drug regimen design; guinea pig tuberculosis model; hollow fiber system model of tuberculosis; mouse tuberculosis model

PMID:
26009617
DOI:
10.1093/infdis/jiv183
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Silverchair Information Systems
Loading ...
Support Center