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).
DRIAD works by quantifying potential associations between stages of the disease and molecular mechanisms that are encoded in lists of genes.
This allows it to measure what happens to brain cells when someone’s treated with a drug, and determine whether the changes correlate with molecular markers of disease severity.
The researchers used the framework to screen 80 FDA-approved and clinically-tested drugs. Their analysis identified several anti-inflammatory drugs used to treat arthritis and blood cancers as top contenders for repurposing.
The drugs work by blocking the action of inflammation-fueling proteins, which are thought to play a role in Alzheimer’s disease.
One of the drugs, baricitinib, which is typically used to reduce pain caused by rheumatoid arthritis, was also recently identified as a potential treatment for COVID-19 in a separate AI study. The drug will now enter a clinical trial for patients with subjective cognitive complaints, mild cognitive impairment, and Alzheimer’s disease.
The researchers believe that their method could provide a fast and inexpensive way to find other medications that could treat Alzheimer’s disease. It could also provide new insights into the mechanisms behind the condition.
You can read the study paper in the journal in Nature Communications.