Preprint Paper.

Abstract

Contemporary deep learning approaches still struggle to bring a useful improvement in the field of drug discovery due to the challenges of sparse, noisy and heterogeneous data that are typically encountered in this context. We use a state-of-the-art deep learning method, Alchemite™, to impute data from drug discovery projects, including multi-target biochemical activities, phenotypic activities in cell-based assays, and a variety of absorption, distribution, metabolism, and excretion (ADME) endpoints. The resulting model gives excellent predictions for activity and ADME endpoints, offering an average increase in R² of 0.22 versus quantitative structure-activity relationship methods. The model accuracy is robust to combining data across uncorrelated endpoints and projects with different chemical spaces, enabling a single model to be trained for all compounds and endpoints. We demonstrate improvements in accuracy on the latest chemistry and data when updating models with new data as an ongoing medicinal chemistry project progresses.

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Held on 26 May 2020.

AI-guided Design of Antimalarials with In Vitro Validation

This webinar was presented by Ben Irwin and Matthew Segall (Optibrium) and Professor Matthew Todd (University College London).

In this webinar you can hear how a combination of generative chemistry and deep learning has impacted the design of new compounds in the search for novel antimalarials.

We were joined by our guest Professor Matthew Todd, Chair of Drug Discovery at University College London and founder of the Open Source Malaria initiative, which aims to find new medicines for the treatment of malaria, recognised by the World Health Organisation as one of the world’s deadliest diseases.

We described how Optibrium’s team deployed the in silico generative chemistry capabilities of StarDrop™ and the cutting-edge AI technologies of Augmented Chemistry™ in the Open Source Malaria (OSM) initiative, to design active compounds against a novel target in Plasmodium falciparum.

_{To hear the narration, please increase your speaker volume.}