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DeepMirror’s AI drug discovery is ‘as simple as a spreadsheet’





After a successful beta test over many months, DeepMirror has launched its early access programme which makes designing drug molecules using AI “as simple as using a spreadsheet”.

Founded by a team of researchers at the University of Cambridge in 2019, DeepMirror’s purpose is to fast-track the drug discovery process. This acceleration can be achieved in the ‘hit-to-lead’ and ‘lead optimisation’ phases: DeepMirror’s platform can predict relevant properties such as drug binding, (bio-)activity, and toxicity – both from user data and from large proprietary curated databases.

DeepMirror, a University of Cambridge spin-out company developing intuitive design software for the discovery of novel therapeutic drugs, announces the launch of its Early Access Programme, from left Cecilia Cabrera, Max Jakobs, Andrea Dimitracopoulos, Jacob Greenand Ryan Greenhalgh. Picture: Keith Heppell
DeepMirror, a University of Cambridge spin-out company developing intuitive design software for the discovery of novel therapeutic drugs, announces the launch of its Early Access Programme, from left Cecilia Cabrera, Max Jakobs, Andrea Dimitracopoulos, Jacob Greenand Ryan Greenhalgh. Picture: Keith Heppell

The laboratory results can be used to refine predictions and generate novel drug candidates for further experimentation, ultimately speeding up the drug discovery process by up to four times, as estimated by the Wellcome Trust and the Boston Consulting Group.

Until DeepMirror, AI-enabled drug discovery programmes mostly started with pharmaceutical companies partnering with AI companies to deliver insights for their drug discovery efforts. Extensive crosstalk between the two parties is the norm, resulting in long waiting times and large amounts of resources spent on both sides.

DeepMirror is looking to solve this issue by enabling R&D teams to carry out AI-driven research from day one, with seamless workflow integration and without the need to engage external stakeholders, develop internal teams or software, or relinquish any intellectual property.

Dr Andrew McTeague, senior scientist, medicinal chemistry, at US-based Morphic Therapeutic, said: “DeepMirror is a huge step forward in the democratisation of machine learning models and their application in drug discovery.

“Its user-friendly interface enables medicinal chemists of all levels to deploy this powerful approach in a fraction of the time. The ability to apply DeepMirror’s platform to any desired endpoint, whether it be potency, selectivity, or even ADME [absorption, distribution, metabolism and excretion] properties, empowers its users to make more informed decisions and to do so faster.

“We’re always looking for new tools to improve the efficiency of our DMTA cycles and DeepMirror helps ensure that no stone is left unturned.”

Earlier this month, CB2-based DeepMirror successfully secured an Innovate UK Biomedical Catalyst grant in collaboration with Impington-based Nuclera.

Nuclera, from left, are founders Jiahao Huang, Gordon McInroy and CEO Micheal Chen. Picture: Keith Heppell.
Nuclera, from left, are founders Jiahao Huang, Gordon McInroy and CEO Micheal Chen. Picture: Keith Heppell.

The grant will enable Nuclera and DeepMirror to extend their platforms and capabilities in a synergistic manner, while developing an integrated product that combines cutting-edge screening and AI-assisted identification of potent and specific drug candidates.

Dr Max Jakobs, co-founder and CEO of DeepMirror, said: “Our mission is to make AI-powered drug design as simple as browsing the web.

“After 12 months of development and a successful beta testing programme, we are excited to officially launch DeepMirror to early adopters. We are inviting researchers to get in touch to use our secure and user-friendly AI platform for drug design.

“DeepMirror was already used on active drug discovery programmes and led to the discovery of novel lead series and inspired the synthesis of novel compounds.”

Details of how to apply for the early access programme are available here.



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