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Further success in malaria initiative
June 2020
by DDN Staff  |  Email the author
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CAMBRIDGE, U.K—Optibrium, a provider of software and services for drug discovery, and Intellegens, a spin-out from the University of Cambridge with a unique artificial intelligence (AI) toolset, today announced they have reached a further significant milestone in their contribution to the Open Source Malaria (OSM) initiative.
 
The team has successfully completed the second phase of a global challenge aimed at developing and testing novel antimalarial compounds. During this phase, predictive models from the first phase were combined with generative methods to design novel compounds. The compounds were subsequently validated by testing their activity against the target.
 
According to Optibrium and Intellegens, out of four compounds proposed in this phase, only their entry demonstrated potency against the target, which they say indicated “the powerful combination of StarDrop, Optibrium’s computational platform for small-molecule design and optimization, with the AI-powered technologies of its Augmented Chemistry platform.”
 
In the latest phase of the OSM project, the team deployed the in-silico, generative chemistry capabilities of StarDrop to design new compounds predicted to be active against a putative target in Plasmodium falciparum, the deadliest species of malaria-causing parasites.
 
In the first phase of the initiative, Optibrium’s Augmented Chemistry technologies, which incorporate Intellegens’ Alchemite deep-learning platform, were used to build predictive models for activity against this target. These were applied to guide the design efforts in the second phase.
 
Founded in 2012 by Prof. Matthew Todd, chair of drug discovery at University College London, the OSM consortium aims to find new medicines for the treatment of malaria.
 
“Our latest work with the Open Source Malaria consortium is a testament to the power of Optibrium’s software. It demonstrates, in an open and transparent way, the impact this dynamic blend of computational chemistry and machine learning can have in supporting drug discovery scientists in tackling these serious diseases,” said Dr. Benedict Irwin, senior scientist at Optibrium.
 
Added Todd: “While the use of AI in drug discovery is still in its infancy and in many cases the potential of in-silico-designed compounds hasn’t yet been rigorously validated experimentally, this example can help pave the way and is a valuable contribution to our efforts. I hope to see more from the team in support of our quest to develop effective treatments for malaria.”
 
Code: E062007

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