Intellegens, the artificial intelligence (AI) start-up co-founded by Gonville & Caius College Fellow Dr Gareth Conduit, has celebrated joint success in the Open Source Malaria (OSM) global initiative aimed at identifying the best predictive models for antimalarial compounds.
Partnered with Optibrium, the leading providers of software and services for drug discovery, they have developed one of the top models, deploying a cutting-edge deep neural network algorithm, Alchemite™, which can accurately predict active compounds with novel mechanisms of actions that could be critical to future malaria control and elimination.
Dr Tom Whitehead, Machine Learning Scientist at Intellegens, commented on the new technology: “Alchemite™ demonstrates real-world applicability and has the potential to provide accurate predictions for problems in drug discovery, such as finding active compounds that can counteract tropical diseases like Malaria.”
Dr Gareth Conduit added, “Alchemite™ was trained with the known antimalarial activity levels of existing compounds, with a unique ability to deliver deep insights into compounds with missing data - where not all activities have been measured. Alchemite™ can then make the highest quality prediction for newly proposed compounds, allowing scientists to focus on the most favourable targets.”
The model is one of four prizewinners, allowing it to progress through the next phase of the initiative that involves further proposals, synthesis and testing against the malaria parasite.
Dr Benedict Irwin, Senior Scientist at Optibrium, said, “In order to combat the increasing incidences of resistance to antimalarial medication, it is essential to discover new compounds with novel mechanisms of action. We have previously seen that the Alchemite method can add significant predictive value across a range of projects and data sets both large and small. The Open Source Malaria data set was a new challenge and we are thrilled that our partnership with Intellegens has been recognised by the consortium and we look forward to progressing to the next phase of the initiative.”
Professor Matthew Todd, Founder of the OSM consortium, added, “It's frequently the case in infectious disease drug discovery that we're working without knowledge of the mechanism of action. This so-called phenotypic drug discovery can make it a challenge to see the patterns in the data in order to predict what to make next. I hope that new developments in AI and machine learning (ML) can help us to make our research more predictive and hence more efficient. The recent competition in Open Source Malaria, where teams openly contributed models to improve a promising series of antimalarials, suggests that new AI/ML technologies have enormous promise. Congratulations to the Optibrium/Intellegens team for contributing one of the best models, using Alchemite™. We're excited by the new molecules that were suggested because they are not ones that we would necessarily have thought of ourselves. We're now making them in the lab.”
Gareth provides further information about Intellegens in an interview published in Physics World https://physicsworld.com/a/neural-networks-extract-information-from-sparse-datasets/