Publications and Presentations

Experimental Validation of Predictive Models in a Series of Novel Antimalarials

This article outlines an open drug discovery competition, help by the Open Source Malaria consortium. Optibrium entered in collaboration with Intellegens. We developed potential anti-malarials by combining our Cerella™ technology and StarDrop™ drug discovery software. We achieved second place with a compound flagged by Cerella. An unusual compound structure, our entry would not have been considered by human scientists alone, showing the usefulness of our machine learning methods.

An Open Drug Discovery Competition: Experimental Validation of Predictive Models in a Series of Novel Antimalarials

Citation details

E. G. Tse, L. Aithani, M. Anderson, J. Cardoso-Silva, G. Cincilla, G. J. Conduit, M. Galushka, D. Guan, I. Hallyburton, B. W. J. Irwin, K. Kirk, A. M. Lehane, J. C. R. Lindblom, R. Lui, S. Matthews, J. McCulloch, A. Motion, H. L. Ng, M. Öeren, M. N. Robertson, V. Spadavecchio, V. A. Tatsis, W. P. van Hoorn, A.D. Wade, T. M. Whitehead, P. Willis, and M. H. Todd, J. Med. Chem. 2021, 64, 22, 16450–16463

DOI: 10.1021/acs.jmedchem.1c00313

Find out more

Download the full article describing the outcomes of the open drug discovery competiton from the journal webpage via the button below. Alternatively, find out more about AI-guided design of antimalarials by watching our webinar. Ben Irwin and Matthew Segall (Optibrium) and Professor Matthew Todd (University College London) describe how Optibrium’s team deployed the cutting-edge AI technologies of Augmented Chemistry® in the Open Source Malaria (OSM) initiative, using predictive models to design active compounds against a novel target in Plasmodium falciparum.



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