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Iktos Partners with Medicines for Malaria Venture in Anti-Malarial Drug Discovery
[November 23, 2022]

Iktos Partners with Medicines for Malaria Venture in Anti-Malarial Drug Discovery


Iktos, a leader in Artificial Intelligence for new drug design, today announced a collaboration with Medicines for Malaria Venture (MMV), a leading product development partnership (PDP) in the field of antimalarial drug research and development. Under this collaboration agreement, Iktos will apply its new 'DockAI' technology to expedite the discovery of novel antimalarial drug candidates.

The objective of the collaboration is to tackle a key challenge in the drug discovery process: discovery of "hits" which could be optimized to leads and candidates for clinical development. Classical hit finding approaches usually involve screening of libraries of molecules either in vitro, or in silico, and these approaches have limitations in terms of time, cost efficiency and the limited size of the underlying screening databases. The collaboration between Iktos and MMV will use an alternative to these classical approaches by combining Iktos' proprietary 'DockAI' innovation for ultra-large-scale virtual screening (hundred million plus molecules) with cloud-based high performance computing (HPC) for a computational run. The goal is to deliver novel hit compounds that can then ultimately be optimized into pre-clinical candidates.

Iktos' 'DockAI' approach will be applied on a therapeutic target previously identified and validated by MMV for anti-malarial drug development. Docking simulations are widely used in the pharmaceutical industry to simulate the interaction between screening compounds and a biological target (usually a protein) to predict biological activity of a chemical compound. Iktos' AI approach builds on this and aims to use an iterative workflow to identify the most promising hits from a very large compound database to facilitate rapid and cost-effective identification of hits. By reducing the cost of virtual screening by a factor of 20, this aproach enables the screening of ultra large compound databases, inaccessible with traditional approaches, which should increase the probability of success.



"We are thrilled and proud to join forces with MMV with the aim to discover novel anti-malarial hit compounds" commented Yann Gaston-Mathé, President and CEO of Iktos. "With high performance computing from AWS, we are confident that we will be able to identify promising novel chemical matter by applying our novel 'DockAI' approach to expedite anti-malarial drug discovery. The insights and feedback from this collaboration and HPC run will be highly valuable to guide us into improving our technology and making it a standard for ultra-large scale virtual screening in drug discovery."

"At MMV, we believe that the right application of artificial intelligence and machine learning as proposed by Iktos and partners could bolster malaria drug discovery," said Dr. Jeremy Burrows, Vice President, Head of Drug Discovery at MMV. "We are excited to explore where this technology can take us in terms of identifying the next-generation of compounds that could help to eliminate and eradicate malaria. It's an exciting time to be involved in drug discovery."


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About Iktos
Incorporated in October 2016, Iktos is a French start-up company specialized in the development of artificial intelligence solutions applied to chemical research, more specifically medicinal chemistry and new drug design. Iktos is developing a proprietary and innovative solution based on deep learning generative models, which enables, using existing data, to design molecules that are optimized in silico to meet all the success criteria of a small molecule discovery project. The use of Iktos technology enables major productivity gains in upstream pharmaceutical R&D. Iktos offers its technology both as professional services and as a SaaS software platform, Makya™. Iktos is also developing Spaya™, a synthesis planning software based upon Iktos's proprietary AI technology for retrosynthesis.
More information on: http://www.iktos.ai/

About MMV
https://www.mmv.org/about-us/what-we-do/overview-our-work


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