CryptoPolyTech.com
Crypto, Politics, Tech, Gaming & World News.

Using artificial intelligence to improve tuberculosis treatments

Our #TECH_Newser covers ‘news of the day’ #techNewserTechnology content.

| cutline • press clip • news of the day |

Cryptopolytech Public Press Pass
Title: Using artificial intelligence to improve tuberculosis treatments

Originally reported on www.sciencedaily.com by ScienceDaily

20000756 – TECH NEWSer | 20001298 – Artificial Intelligence AI | •| Tech |•| Newser |•| Technology | •| Artificial |•| Intelligence |•| AI |

Using artificial intelligence to improve tuberculosis treatments.

Imagine you have 20 new compounds that have shown some effectiveness in treating a disease like tuberculosis (TB), which affects 10 million people worldwide and kills 1.5 million each year. For effective treatment, patients will need to take a combination of three or four drugs for months or even years because the TB bacteria behave differently in different environments in cells — and in some cases evolve to become drug-resistant. Twenty compounds in three- and four-drug combinations offer nearly 6,000 possible combinations. How do you decide which drugs to test together?

Related Posts

In a recent study, published in the September issue of Cell Reports Medicine, researchers from Tufts University used data from large studies that contained laboratory measurements of two-drug combinations of 12 anti-tuberculosis drugs. Using mathematical models, the team discovered a set of rules that drug pairs need to satisfy to be potentially good treatments as part of three- and four-drug cocktails.

The use of drug pairs rather than three- and four- drug combination measurement cuts down significantly on the amount of testing that needs to be done before moving a drug combination into further study.

“Using the design rules we’ve established and tested, we can substitute one drug pair for another drug pair and know with a high degree of confidence that the drug pair should work in concert with the other drug pair to kill the TB bacteria in the rodent model,” says Bree Aldridge, associate professor of molecular biology and microbiology at Tufts University School of Medicine and of biomedical engineering at the School of Engineering, and an immunology and molecular microbiology program faculty member at the Graduate School of Biomedical Sciences. “The selection process we developed is both more streamlined and more accurate in predicting success than prior processes, which necessarily considered fewer combinations.”

The lab of Aldridge, who is corresponding author on the paper and also associate director of Tufts Stuart B. Levy Center for Integrated Management of Antimicrobial Resistance, previously developed and uses DiaMOND, or diagonal measurement of n-way drug interactions, a method to systemically study pairwise and high-order drug combination interactions to identify shorter, more efficient treatment regimens for TB and potentially other bacterial infections. With the design rules established in this new study, researchers believe they can increase the speed at which scientists determine which drug combinations will most effectively treat tuberculosis, the second leading infectious killer in the world.

Story Source:

Materials provided by Tufts University. Note: Content may be edited for style and length.


‘News of the Day’ content, as reported by public domain newswires.

Find more, like the above, right here on Cryptopolytech.com by following our extensive quiclick links appearing on images or within categories [NEWSer CHEWSer].

Source Information (if available)

It appears the above article may have originally appeared on www.sciencedaily.com and has been shared elsewhere on the internet, repeatedly. News articles have become eerily similar to manufacturer descriptions.

We will happily entertain any content removal requests, simply reach out to us. In the interim, please perform due diligence and place any content you deem “privileged” behind a subscription and/or paywall.

We compile ‘news of the day’ content in an unbiased manner and contextually classify it to promote the growth of knowledge by sharing it just like Using artificial intelligence to improve tuberculosis treatments

First to share? If share image does not populate, please close the share box & re-open or reload page to load the image, Thanks!

You might also like