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Merck and Iktos collaborate on compounds
April 2019
by Mel J. Yeates  |  Email the author
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DARMSTADT, Germany—In March, Merck KGaA of Germany announced a collaboration agreement with Iktos for the use of its generative modeling artificial intelligence (AI) technology, in order to facilitate the rapid and cost-effective discovery and design of promising new compounds.
 
As Klaus Urbahns, head of Discovery & Development Technologies at Merck, tells DDNews, “We identified the generative AI technology from Iktos as a great strategic fit to leverage AI to complement our discovery efforts with speed and precision. The decision to proceed with the collaboration was a mutual one. The company looks for partners such as Iktos which share its passion for discovery and whose expertise complements its existing portfolio, and who share its mission to discover treatments that improve patient lives.”
 
Iktos’ deep generative models-based AI technology helps bring speed and efficiency to the drug discovery process by automatically designing virtual novel molecules that have the desired activities for treating a given disease. This tackles one of the key challenges in drug design: rapid identification of molecules which simultaneously satisfy multiple drug-like criteria for clinical testing. The technology is already successfully established in other fields, such as image processing and automatic translation, but has only recently been applied to chemistry.
 
“The agreement enables Merck access to Iktos AI technology across three drug discovery projects. Iktos technology can help accelerate drug discovery projects across the drug design cycle: from early-stage hit discovery to late-stage lead optimization,” Urbahns says. “At this point in time it has not yet been decided which drug discovery projects will benefit from the technology, except for one project which has already started at lead optimization stage, where Iktos technology is used to help identify molecules with optimal profiles for all in-vitro assays (potency, selectivity, ADMET) and which will therefore be likely to have good results in in-vivo testing.”
 
“We are thrilled that Merck ... is collaborating with Iktos to further accelerate its drug discovery capabilities,” commented Yann Gaston-Mathé, president and CEO of Iktos. “In a short space of time, our technology has successfully enabled huge progress, and we are eager to apply the enormous possibilities it holds to help Merck with the successful design of new therapeutic options.”
 
The agreement with Iktos follows a recent announcement in December of a year-long licensing agreement with Cyclica Inc. for the use of its AI-augmented proteome screening platform, Ligand Express. Merck KGaA was also recently granted a U.S. Patent for a novel combination of artificial intelligence and blockchain technology, aimed at providing a solution for the secure integration of physical products into the digital world.
 
And in other discovery-related AI news, Elsevier and The Pistoia Alliance recently announced the results of a joint “datathon” for Drug Repurposing for Rare Diseases. The datathon, conducted in partnership with non-profit groups Cures Within Reach and Mission: Cure, involved participants from a range of organizations including life sciences, technology and academia, and has succeeded in identifying drug candidates for repurposing to treat chronic pancreatitis. The full results of the datathon were released at The Pistoia Alliance Centre of Excellence for AI/ML in Life Sciences workshop in London on March 12.
 
Five drug candidates passed the expert review panel and are being actively considered by Mission: Cure with a view to proceeding to patient trials: lacosamide to target cathepsin B; dapsone to target the cystic fibrosis transmembrane conductance regulator; ibuprofen to target the cystic fibrosis transmembrane conductance regulator; rolipram to target tumor necrosis factor alpha (TNF-α); and prednisolone to target tumor necrosis factor alpha (TNF-α).
 
“The results of the datathon show that by working in unison, we can achieve breakthroughs that will have a real impact on patients’ lives,” said Dr. Steve Arlington, president, The Pistoia Alliance. “In life sciences today, no one company has the resources to ‘go it alone.’ So the datathon was the perfect opportunity to bring all the relevant experts together and pool our knowledge and resources. The results are very promising, and we look forward to seeing these therapies reach those in need.”
 
The datathon had participants apply AI, machine learning and statistical techniques to a real-world problem such as drug repurposing, using Elsevier’s Entellect platform. Participants were able to identify suitable drugs to be repositioned to treat chronic pancreatitis. This involved the use of multiple techniques, including target-based drug discovery, examining the perturbation of a drug on a specific gene known to be disease-modifying and symptomatic-based drug discovery — i.e., examining the perturbation of a drug on the body.
 
“The goal of the datathon was to identify drug candidates for repurposing by using predictive analytics techniques, and we also wanted to explore best practice in the use of data science,” noted Dr. Jabe Wilson, consulting director, Text and Data Analytics, Elsevier. “This was the first public trial for our Entellect platform, and it’s been a great success on all fronts. I want to thank all our partners and participants for their time and commitment to achieving this positive outcome.”
 
Code: E041906

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