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It’s easy to be pessimistic about the search for a breakthrough Alzheimer’s drug. Failures and financial losses are mounting. Drug companies are shell-shocked, and the dominant beta-amyloid hypothesis that has driven — some say hijacked — decades of research is now looking shakier than ever.

But amid all the back-to-the-drawing-board talk, a powerful new tool has emerged — artificial intelligence systems that are starting to demonstrate an ability to detect Alzheimer’s far earlier than traditional methods and surface data that may help explain the variability of the disease and its effects on patients. The rapidly growing body of research promises to make the search for new treatments faster, cheaper, and far more targeted. 


Just in the past nine months, researchers at the University of California developed AI to automate and accelerate analysis of different types of amyloid plaque, the clumps of protein fragments found in the brains of people with Alzheimer’s patients that are believed to play an important — though still uncertain — role in the disease. 

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