Conscience, a Canadian nonprofit biotech company, announced last month that seven molecules had been identified as potential treatments for familial Parkinson’s disease as a result of its CACHE Challenge. The Critical Assessment of Computational Hit-Finding Experiments (CACHE) Challenge takes a unique approach to drug discovery by combining artificial intelligence with an open-science, collaborative method not limited by patents or intellectual property.
The process began with a call to academic centers and commercial organizations to use AI and computational chemistry to identify molecules that would bind to the LRRK2 gene. This target was chosen because mutations on LRRK2 are the most common cause of inherited Parkinson’s disease. The Structural Genomics Consortium at the University of Toronto identified seven of 2,000 molecules at potential “hits,” and these results were validated by an independent review committee.
“In an era where new therapies for many diseases have been scarce despite substantial investment, the CACHE Challenge provides an alternative, collaborative model for drug development,” said Ryan Merkley, CEO of Conscience. “We can also celebrate the emergence of AI as a promising new tool for drug discovery.”
Additional CACHE Challenges are planned for Covid and a rare form of cancer. Data from the Parkinson’s CACHE Challenge are available to the public here.
