AIMC Topic: Antitubercular Agents

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Computational Approaches as Rational Decision Support Systems for Discovering Next-Generation Antitubercular Agents: Mini-Review.

Current computer-aided drug design
Tuberculosis, malaria, dengue, chikungunya, leishmaniasis etc. are a large group of neglected tropical diseases that prevail in tropical and subtropical countries, affecting one billion people every year. Minimal funding and grants for research on th...

Artificial intelligence-derived 3-Way Concentration-dependent Antagonism of Gatifloxacin, Pyrazinamide, and Rifampicin During Treatment of Pulmonary Tuberculosis.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
BACKGROUND: In the experimental arm of the OFLOTUB trial, gatifloxacin replaced ethambutol in the standard 4-month regimen for drug-susceptible pulmonary tuberculosis. The study included a nested pharmacokinetic (PK) study. We sought to determine if ...

Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data.

Bioinformatics (Oxford, England)
MOTIVATION: Correct and rapid determination of Mycobacterium tuberculosis (MTB) resistance against available tuberculosis (TB) drugs is essential for the control and management of TB. Conventional molecular diagnostic test assumes that the presence o...