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Comprehensive Analysis of Methods Used for the Evaluation of Compounds Against Mycobacterium Tuberculosis

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Date 2012 Sep 4
PMID 22940006
Citations 116
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Abstract

In drug development, there are typically a series of preclinical studies that must be completed with new compounds or regimens before use in humans. A sequence of in vitro assays followed by in vivo testing in validated animal models to assess the activity against Mycobacterium tuberculosis, pharmacology and toxicity is generally used for advancing compounds against tuberculosis in a preclinical stage. A plethora of different assay systems and conditions are used to study the effect of drug candidates on the growth of M. tuberculosis, making it difficult to compare data from one laboratory to another. The Bill and Melinda Gates Foundation recognized the scientific gap to delineate the spectrum of variables in experimental protocols, identify which of these are biologically significant, and converge towards a rationally derived standard set of optimized assays for evaluating compounds. The goals of this document are to recommend protocols and hence accelerate the process of TB drug discovery and testing. Data gathered from preclinical in vitro and in vivo assays during personal visits to laboratories and an electronic survey of methodologies sent to investigators is reported. Comments, opinions, experiences as well as final recommendations from those currently engaged in such preclinical studies for TB drug testing are being presented. Certain in vitro assays and mouse efficacy models were re-evaluated in the laboratory as head-to-head experiments and a summary is provided on the results obtained. It is our hope that this information will be a valuable resource for investigators in the field to move forward in an efficient way and that key variables of assays are included to ensure accuracy of results which can then be used for designing human clinical trials. This document then concludes with remaining questions and critical gaps that are in need of further validation and experimentation.

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