In a groundbreaking open science competition, Conscience, a Canadian nonprofit organization, has identified seven potential treatments for familial Parkinson's disease. The competition, known as the CACHE Challenge, was supported by the Structural Genomics Consortium (SGC) and received a grant from the Canadian government. This innovative approach aims to make artificial intelligence (AI) a viable tool for drug discovery by openly sharing data, information, tools, and research results without the constraints of patents.

The CACHE Challenge, the first of its kind for Conscience, was funded by The Michael J. Fox Foundation for Parkinson's Research (MJFF) and involved participants using computer-based methods to predict molecules that may treat the disease. These predictions were then experimentally tested by the CACHE team.

"We can celebrate the emergence of AI as a promising tool for drug discovery. That's what makes these findings so exciting," said Ryan Merkley, CEO of Conscience. Merkley emphasized the significance of collaboration in drug discovery, contrasting it with the traditional patent-driven approach where scientists work in isolation from competing laboratories.

Parkinson's disease is a progressive neurological disorder characterized by symptoms such as slowness of movement, tremors, and balance problems. Current therapies can provide relief from symptoms but do not slow down or cure the disease. Finding treatments that address the underlying causes is a major goal for researchers, particularly for familial Parkinson's, which has a genetic component.

The CACHE Challenge specifically focused on molecules that bind strongly to the LRRK2 protein, encoded by the LRRK2 gene, the most common genetic cause of familial Parkinson's. Out of the 2,000 molecules submitted, seven were validated experimentally at the SGC in a two-year-long process involving multiple assessments by an independent committee.

This groundbreaking achievement has the potential to explore new therapeutic strategies against Parkinson's disease. "These compounds have an entirely novel mode of action," said CACHE lead scientist Matthieu Schapira from the SGC at the University of Toronto.

The CACHE Challenge is a part of Conscience's mission to accelerate the discovery of new treatments for Parkinson's disease. Their collaborative and transparent approach, which includes making the entire dataset available to the public, aims to benefit the entire scientific community and advance therapeutic development without patent restrictions.

"The application of artificial intelligence within a collaborative open science model is bearing fruit," said François-Philippe Champagne, Canada's Minister of Innovation, Science, and Industry. He applauded Conscience's commitment to this pioneering approach.

In addition to the CACHE Challenge for Parkinson's, Conscience is currently running three other challenges focusing on COVID-19, cancer, and obesity. This alternative and collaborative model for drug development holds the potential to improve efficiency and cost-effectiveness.

An inaugural CACHE Symposium, bringing together specialists in computer-based chemistry and AI, is scheduled to be held on March 6 and 7 in Toronto. The symposium aims to share experiences and insights about open science collaborations and the development of AI tools for drug discovery.