AI has been used to identify potential new drugs for Parkinson’s Disease. A new artificial intelligence (AI) based strategy has significantly sped up the identification of potential new drugs to treat Parkinson’s disease. The work, published in the journal Nature Chemical Biology , could mean that new treatments for Parkinson’s reach clinical trials and patients more quickly.
Drug discovery for serious diseases from Parkinson’s to dementia and cancer is often a slow, laborious and expensive process. AI and machine learning techniques have also shown promise in discovering potential drugs for cancers and dozens of biomedical startup companies are betting on the potential of AI for drug discovery.
“This is an extremely time-consuming process – just identifying a lead candidate for further testing can take months or even years," said Michele Vendruscolo leader of the research and professor in the Yusuf Hamied Department of Chemistry at the University of Cambridge in the U.K.
The new study showed how an AI-based strategy sped up this process significantly and was a thousand times cheaper than traditional methods, identifying a small number of potentially useful compounds which were taken forward for laboratory testing. The results from these experiments were then fed back into the machine learning model to further optimize the predictions.
"One route to search for potential treatments for Parkinson’s requires the identification of small molecules that can inhibit the aggregation of alpha-synuclein, which is a protein closely associated with the disease," said Vendruscolo in a press release .
“The use of AI to develop machine learning […]
AI Identifies New Potential Treatments For Parkinson’s Disease
