Optibrium, a leading developer of software and AI solutions for molecular design, has announced its partnership with TalTech (Tallinn University of Technology) to co-supervise an EU-funded PhD position as part of the Innochembio programme. This research project will focus on developing more accurate metabolism models that will reduce the reliance on costly laboratory experiments while improving speed, efficiency and sustainability in drug discovery.
The PhD research will address a critical need in modern drug development. To overcome the limited amount of available experimental data, existing predictive models use hybrid approaches that combine machine learning with physics-based methods. The most accurate physics-based methods are too computationally expensive to apply routinely, so it’s necessary to use faster but less-accurate approximations. This project aims to replace those methods with more efficient and accurate machine learning interatomic potentials (MLIPs). These improved models will enable pharmaceutical teams to better identify risks associated with drug metabolism and guide the design of optimal compounds for synthesis, saving time and reducing costs while aligning their efforts with green chemistry principles. This research will specifically target MLIPs for drug-like molecules and metabolism mediated by Cytochrome P450 enzymes, a family responsible for the metabolism of 70-80% of all small molecule drugs.
For further information on applying for the Innochembio programme, visit https://taltech.ee/en/innochembio/application-process, contact info@optibrium.com or call +44 1223 815900.
