Iktos and Pfizer collaborate on AI drug design
pharmafile | March 2, 2021 | News story | Manufacturing and Production | AI, Iktos, Pfizer
Iktos has announced that its artificial intelligence (AI) technology for de novo design will be applied to selected Pfizer small-molecule discovery programmes in a new collaboration.
Incorporated in 2016, Iktos is a start-up company specialising in the development of AI solutions applied to chemical research, specifically medicinal chemistry and new drug design. The company is developing a proprietary and innovative solution based on deep learning generative models, which enables, using existing data, the design of molecules that are optimised in silico to meet all the success criteria of a small molecule discovery project.
Earlier this year, Iktos released Makya, its generative AI-driven de novo design software for Multi-Parametric Optimisation (MPO), available as a SaaS platform and for implementation on customer premises or in the customer’s Virtual Private Cloud (VPC).
Iktos is also developing Spaya, a synthesis planning software based upon the company’s proprietary AI technology for retrosynthesis.
Pfizer has been deploying Iktos’s generative modelling technology to small-molecule programmes.
Charlotte Allerton, Head of Medicine Design at Pfizer, said: “Pfizer has had an active interest in AI for de novo design and we are excited to work with Iktos to use their AI technology on a number of our programmes.”
Yann Gaston-Mathé, Co-Founder and CEO of Iktos, added: “We are proud to work with Pfizer and to have their scientists use our software in their early discovery programmes. It is our ultimate goal to put our technology in the hands of drug discovery scientists, who have deep knowledge and understanding of their discovery programmes.
“By combining their drug discovery expertise with our algorithmic and data science know-how and experience derived from the many collaborations we have established to date, we believe that the promise of AI to dramatically improve drug discovery will have a better chance to be realised and impact therapeutic development.”
Darcy Jimenez
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