Improve your tubing with artificial intelligence

Image: This is a medical illustration of drug-resistant Mycobacterium tuberculosis presented in the US Centers for Disease Control and Prevention (CDC) publication The Threat of Antibiotic Resistance in the United States 2019 (AR Threat Report). look more Credits: Medical Illustrator: Alissa Eckert; James Archer Suppose there are 20 new compounds that have shown efficacy in treating a disease like tuberculosis (TB), which affects 10 million people worldwide and kills 1.5 million people each year. For effective treatment, patients need to take three or four drugs in combination for months or years because tuberculosis bacteria behave differently in different intracellular environments. there is. With 3 and 4 combinations, he has 20 compounds and about 6,000 possible combinations. How do you decide which drugs to test together? In recent studies, Published in the September issue of cell report medicineresearchers at Tufts University used data from a large study that included laboratory measurements of two-drug combinations of 12 anti-tuberculosis drugs. and found a set of rules that drug pairs must satisfy in order to be potentially good therapeutics as part of a 4-drug cocktail. Measuring two drug combinations, rather than three or four drug combinations, greatly reduces the amount of testing that needs to be done before a drug combination can be moved to further study. “Using the design rules that we have established and tested, we can replace one drug pair with another and see that the drug pair acts in concert with the other to kill M. tuberculosis. You can know with a high degree of confidence that the rodent model says Bree AldridgeAssociate Professor of Molecular Biology and Microbiology Tufts University School of Medicine and of biomedical engineering Faculty of Engineeringand Faculty of Immunology and Molecular Microbiology Programs of Graduate School of Medicine, Dentistry and Pharmaceutical Sciences"The selection process we have developed is more streamlined and more accurate in predicting success than previous processes that considered necessarily fewer combinations." The corresponding author of the paper, Tufts Stuart B. Levy Center for Integrated Control of Antimicrobial Resistancepreviously developed and used diamond, or systematically studying diagonal, pairwise and higher-order drug combination interactions in the n-direction to identify shorter, more efficient treatment regimens for tuberculosis and potentially other bacterial infections. how to. The design rules established in this new study, researchers believe, will allow scientists to speed up determining which drug combinations will most effectively treat tuberculosis. journal cell report medicine Survey method Computational simulation/modeling Research theme not applicable article title Design Principles for Assembling Drug Combinations for Effective Tuberculosis Treatment Using Interpretable Pairwise Drug Response Measures Article publication date September 8, 2022 COI statement The authors declare no competing interests. Disclaimer: AAAS and EurekAlert! EurekAlert! is not responsible for the accuracy of news releases posted. Use of information by contributors or via the EurekAlert system. Sources 1/ https://Google.com/ 2/ https://www.eurekalert.org/news-releases/964785 The mention sources can contact us to remove/changing this article

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Improve your tubing with artificial intelligence

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Improve your tubing with artificial intelligence

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