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DeepMirror Chem

DeepMirror Chem is our web app that accelerates Design-Make-Test-Analyse (DMTA) cycles in preclinical drug discovery by 4x. With it, you can apply generative AI to incept ideas (structure and R Group substitutions) and prioritise hypothetical compounds based on predicted affinity (QSAR) and properties (ADMET).


Get in touch to request access to our app.

Small Molecules
Antibodies & Peptides

We simulated small molecule lead optimisation workflows both with and without DeepMirror Chem and estimate that we enable users to find the most optimal drug up to ~4x faster.

4x acceleration of small molecule lead optimisation

In this case study, we use DeepMirror Chem to learn and predict PROTAC properties to accelerate PROTAC discovery

Predict PROTAC affinity and degradation


QSAR and ADMET properties within minutes using our optimised autoML infrastructure


Compounds for synthesis with confidence estimates and multi parameter optimisation


Novel & promising compounds with generative AI and iterative design


Our technology: Small Data AI

Case Studies

Upload your experimental data through our user-friendly interface

The best performing model is automatically selected for a given dataset

Experimental endpoints
are predicted using
the best model

A large library of different machine learning models are trained on a user's experimental data

Small Data AI

Confidence Estimates

Cloud Services

Intuitive Interface

Generative AI

Predict QSAR and ADMET from small datasets or no data at all

Our platform automatically cycles through ~100 algorithms to deliver the best possible predictions

Use validated prediction confidence estimates to inform your next step 

Safe and private cloud computing (ISO27001 and SOC2 certification in progress)

Easy to use, no-code software so you don't need to know how to program to use our technology

Generate in silico small molecule libraries using Generative AI 


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