Researchers have developed a method based on Artificial Intelligence (AI) that rapidly identifies currently available medications that may treat Alzheimer's disease. The method could represent a rapid and inexpensive way to repurpose existing therapies into new treatments for this progressive, debilitating neurodegenerative condition. Importantly, it could also help reveal new, unexplored targets for therapy by pointing to mechanisms of drug action. "Repurposing FDA-approved drugs for Alzheimer's disease is an attractive idea that can help accelerate the arrival of effective treatment -- but unfortunately, even for previously approved drugs, clinical trials require substantial resources, making it impossible to evaluate every drug in patients with Alzheimer's disease," said researcher Artem Sokolov from Harvard Medical School. "We therefore built a framework for prioritising drugs, helping clinical studies to focus on the most promising ones," Sokolov added.

New York, March 7 (IANS) Researchers have developed a method based on Artificial Intelligence (AI) that rapidly identifies currently available medications that may treat Alzheimer's disease. The method could represent a rapid and inexpensive way to repurpose existing therapies into new treatments for this progressive, debilitating neurodegenerative condition. Importantly, it could also help reveal new, unexplored targets for therapy by pointing to mechanisms of drug action. "Repurposing FDA-approved drugs for Alzheimer's disease is an attractive idea that can help accelerate the arrival of effective treatment -- but unfortunately, even for previously approved drugs, clinical trials require substantial resources, making it impossible to evaluate every drug in patients with Alzheimer's disease," said researcher Artem Sokolov from Harvard Medical School. "We therefore built a framework for prioritising drugs, helping clinical studies to focus on the most promising ones," Sokolov added.

The Food and Drug Administration on Friday issued an emergency authorization for a new test to detect Covid-19 infections -- one that stands apart from the hundreds already authorized. Unlike tests that detect bits of SARS-CoV-2 or antibodies to it, the new test, called T-Detect COVID, looks for signals of past infections in the body's adaptive immune system -- in particular, the T cells that help the body remember what its viral enemies look like. Developed by Seattle-based Adaptive Biotechnologies, it is the first test of its kind. Adaptive's approach involves mapping antigens to their matching receptors on the surface of T cells. They and other researchers had already shown that the cast of T cells floating around in an individual's blood reflects the diseases they've encountered, in many cases years later.

Researchers have used artificial intelligence to screen 80 FDA-approved drugs and reveal which could be used as Alzheimer's treatments. A team at Massachusetts General Hospital (MGH) and Harvard Medical School (HMS), both US, has developed an artificial intelligence (AI)-based method to screen currently available medications as possible treatments for Alzheimer's disease. According to the researchers, the method could represent a rapid and inexpensive way to repurpose existing therapies into new treatments for the neurodegenerative condition. It could also help reveal new, unexplored targets for therapy by pointing to mechanisms of drug action. "Repurposing US Food and Drug Administration (FDA)-approved drugs for Alzheimer's disease is an attractive idea that can help accelerate the arrival of effective treatment – but unfortunately, even for previously approved drugs, clinical trials require substantial resources, making it impossible to evaluate every drug in patients with Alzheimer's disease," explained Dr Artem Sokolov, at HMS. "We therefore built a framework for prioritising drugs, helping clinical studies to focus on the most promising ones."

Alzheimer's disease is becoming increasingly prevalent as life expectancies lengthen. But the complexity of the condition makes it hard to find effective treatments. One way to expedite the search that's yielded promising results is using AI to find existing drugs that could be repurposed to combat the disorder. Harvard researchers recently used the approach to identify 80 candidate medications that merit further investigation. They discovered the contenders through a framework they call DRIAD (Drug Repurposing In Alzheimer's Disease).

When the Covid-19 pandemic emerged last year, physician Lara Jehi and her colleagues at the Cleveland Clinic were running blind. Who were the patients likely to get sicker? What kinds of care will they need? "The questions were endless," says Jehi, the clinic's chief research information officer. "We didn't have the luxury of time to wait and see what's going to evolve over time."

New treatments for Alzheimer's disease are desperately needed, but numerous clinical trials of investigational drugs have failed to generate promising options. Now a team at Massachusetts General Hospital (MGH) and Harvard Medical School (HMS) has developed an artificial intelligence-based method to screen currently available medications as possible treatments for Alzheimer's disease. The method could represent a rapid and inexpensive way to repurpose existing therapies into new treatments for this progressive, debilitating neurodegenerative condition. Importantly, it could also help reveal new, unexplored targets for therapy by pointing to mechanisms of drug action. "Repurposing FDA-approved drugs for Alzheimer's disease is an attractive idea that can help accelerate the arrival of effective treatment--but unfortunately, even for previously approved drugs, clinical trials require substantial resources, making it impossible to evaluate every drug in patients with Alzheimer's disease," explains Artem Sokolov, Ph.D., director of Informatics and Modeling at the Laboratory of Systems Pharmacology at HMS. "We therefore built a framework for prioritizing drugs, helping clinical studies to focus on the most promising ones."

Independent validation of the nominated drug targets could provide new insights into the mechanisms behind Alzheimer's disease and lead to novel therapies. BOSTON – New treatments for Alzheimer's disease are desperately needed, but numerous clinical trials of investigational drugs have failed to generate promising options. Now a team at Massachusetts General Hospital (MGH) and Harvard Medical School (HMS) has developed an artificial intelligence–based method to screen currently available medications as possible treatments for Alzheimer's disease. The method could represent a rapid and inexpensive way to repurpose existing therapies into new treatments for this progressive, debilitating neurodegenerative condition. Importantly, it could also help reveal new, unexplored targets for therapy by pointing to mechanisms of drug action.

The mass affordability of sequencing enables a paradigm shift from sequencing only those with risk factors (such as someone's family history or medical symptoms) to sequencing proactively to identify risk factors. It will allow every individual to build up genomic data capital, opening the door for new applications and business models across health insurance, care delivery, and everyday life. New approvals & patents - Ava, a Swiss digital healthcare company focused on women's reproductive health, announced that the United States Food and Drug Administration (FDA) clearance for its fertility tracking wearable. BrainQ, an Israeli start-up, announced that the FDA has designated its AI-powered electromagnetic field therapy that aims to enhance recovery and reduce disability after neurological damage caused by stroke as a Breakthrough Device, giving access to the new Medicare Coverage of Innovative Technology (MCIT) pathway. Voluntis (French DTx) announced the issuance of a new patent by the European Patent Office (EPO) for intelligent patient support in drug dosing applied in the field of diabetes for insulin titration support.

The UK's Scientific Advisory Group for Emergencies (SAGE) advised the government to introduce mandatory hotel quarantine for travellers arriving into the UK two weeks ago, according to minutes from a meeting on 21 January that were leaked to the Times. On Thursday 21 January, SAGE reportedly warned that "reactive, geographically targeted" travel bans couldn't be relied on to prevent faster-spreading coronavirus variants, such as those identified in South Africa and Brazil, from reaching the UK, adding that: "no intervention, other than a complete, pre-emptive closure of borders, or the mandatory quarantine of all visitors upon arrival in designated facilities, irrespective of testing history, can get close to fully preventing the importation of new cases or new variants." A Downing Street spokesperson said SAGE did not directly advise UK prime minister Boris Johnson to close borders. Universities minister Michelle Donelan told Sky News that the government "always based our decisions on the best medical and scientific advice" and said "the SAGE advice actually said it would probably be ineffective, in fact, to close the borders, which was the same advice that we got at the time from the World Health Organization". Johnson announced geographically targeted hotel quarantine measures for travellers returning from 30 countries, including Brazil and South Africa, last week. UK health minister Matt Hancock urged people living in postcodes in England singled out for enhanced coronavirus testing for the so-called South Africa variant to stay at home unless "absolutely essential". Urgent door-to-door testing for the faster-spreading variant has been deployed after 11 cases with no link to foreign travel were identified in parts of England.