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Antitubercular Agents

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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...

Machine learning and docking models for Mycobacterium tuberculosis topoisomerase I.

Tuberculosis (Edinburgh, Scotland)
There is a shortage of compounds that are directed towards new targets apart from those targeted by the FDA approved drugs used against Mycobacterium tuberculosis. Topoisomerase I (Mttopo I) is an essential mycobacterial enzyme and a promising target...

Artificial Intelligence and Amikacin Exposures Predictive of Outcomes in Multidrug-Resistant Tuberculosis Patients.

Antimicrobial agents and chemotherapy
Aminoglycosides such as amikacin continue to be part of the backbone of treatment of multidrug-resistant tuberculosis (MDR-TB). We measured amikacin concentrations in 28 MDR-TB patients in Botswana receiving amikacin therapy together with oral levofl...

An Imbalanced Learning based MDR-TB Early Warning System.

Journal of medical systems
As a man-made disease, multidrug-resistant tuberculosis (MDR-TB) is mainly caused by improper treatment programs and poor patient supervision, most of which could be prevented. According to the daily treatment and inspection records of tuberculosis (...