Scientists at the National University of Pennsylvania used machine learning and genetic data to identify drugs that could help smokers recover from addiction. Research published in the journal Nature Genetics.
A team of more than 70 researchers analyzed the genetic data of 1.3 million people. They identified more than 400 genes associated with smoking. Some contained instructions for the production of nicotinic receptors, others regulated the work of dopamine, which makes people feel relaxed and happy.
Machine learning has made it possible to find drugs that affect the products of these genes. Scientists have discovered that the drugs dextromethorphan to treat cough and galantamine to treat Alzheimer’s disease could potentially be reused to help people quit smoking.
“Drug reuse using biomedical big data and machine learning techniques can save money, time and resources. Some of the drugs we’ve identified are already in clinical trials for their ability to help smokers quit, but there are other possible candidates that may be explored in future studies.”
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Source: Gazeta
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