Faster Hit to Candidate

Deploy private molecular AI, harness generative design, and apply protein-ligand co-folding to overcome potency and ADMET challenges.

Trusted by Industry Leaders

“Structure enablement is a key inflection point for many drug discovery programs. However, getting to this point is not trivial, even with experimental evidence of ligand binding. deepmirror quickly enabled us to leverage empirical data in conjunction with AI structure prediction models to develop testable design hypotheses for our lead compounds.”

Michelle Southey
Drug Maker
Curie.Bio
Michelle Southey

"We found the deepmirror interface very intuitive and user friendly. The AI prediction is easy to use and did a great job of predicting/classifying potency of unknown compounds when applied to larger data sets, and the generative AI made sensible chemical suggestions that could be made and tested."

Sam Butterworth
Senior Lecturer in Medicinal Chemistry
The University of Manchester
Sam Butterworth

"We used the deepmirror App on an active drug discovery program to predict the experimental biological activity outcome of our whole proprietary library and identified and validated novel active scaffolds”

Francesco A. Greco
Senior Research Scientist
Tes Pharma
Francesco A. Greco

”The deepmirror App provides a user-friendly interface for Medicinal chemists to integrate AI into the design of new drugs. We look forward to seeing how the platform can help inspire the next generation of small molecule CNS therapeutics!”

Andrew Stott
Director of Medicinal Chemistry
Cerevance
Andrew Stott

“deepmirror is a huge step forward in the democratization of ML 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. deepmirror helps ensure that no stone is left unturned.”

Andrew McTeague
Senior Scientist
Morphic
Andrew McTeague
Goal-guided Generation

Explore novel chemical space with generative AI to identify molecules that balance potency and ADMET profiles. Prioritise top candidates with confidence before wet-lab testing.

Private Potency & ADMET Models

Build and deploy  programme-specific molecular property models with a single click. Leverage data from multiple programmes to create proprietary fingerprints that enhance modelling accuracy.

Next-Gen Protein-Ligand Co-Folding

Predict ligand–target interactions with state-of-the-art co-folding algorithms. Screen potential hits, explore SAR hypothesis, and optimise lead molecules with structure-aware AI.

Security You Can Trust

Your intellectual property is your most valuable asset, and we treat it with the highest level of protection.
deepmirror guarantees best-in-class security to safeguard your data and discoveries. Learn more in our Trust Center.

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Enterprise-Grade protection

ISO 27001-certified* infrastructure and rigorous policies keep your data and IP safe.

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Your Data,
Your Models

Any data you upload and the models you build remain private and are never shared without your permission.

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End-to-End Encryption

All data is encrypted in transit and at rest using modern, highly secure protocols.

AI is our tool, not our replacement.

We work to enable small and large companies alike to get drug ideas into the clinic within months not years.

We believe that AI will be a key tool for this - one that enhances creativity and human potential - and are proud to make AI an invisible partner in the drug discovery process, enabling chemists to focus on what they do best.

deepmirror brings together leaders at the interface of product, biology, physics, and AI.

Open positions

AI is our tool, not our replacement.

We work to enable small and large companies alike to get drug ideas into the clinic within months not years.

We believe that AI will be a key tool for this - one that enhances creativity and human potential - and are proud to make AI an invisible partner in the drug discovery process, enabling chemists to focus on what they do best.

DeepMirror brings together leaders at the interface of product, biology, physics, and AI.

Open positions