Causal Machine Learning for
Drug Discovery

Introducing causality to representation-based models for improved extrapolation in challenging data regimes.

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Our Technology

⌬ Causal-Chemprop

SCM built on Chemprop representations and additional molecular descriptors for small molecule property prediction and optimization.

🧬 Causal-ESM

SCM built on ESM-2 sequence-level representations and additional physicochemical descriptors for enzyme property prediction.

🔬 Custom

We’ll build a structural causal model using your in-house AI model for your use case.

Publications

Causal-Chemprop: Causal Molecular Machine Learning for Property Prediction and Molecular Optimization

Christian Natajaya (1), Lucas Attia (2), Jackson Burns (2), Patrick Doyle (2)

(1) Neopoly Ltd, London, United Kingdom

(2) Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA

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