D3net: Driving drug design with deep multimodal and multi-task learning

Term: 07/2019 – 06/2022 (36 Monate)

Partner: UCB Biopharma sprl

Topic:
In this project, UCB Biopharma and the Institute for Machine Learning at Johannes Kepler University Linz team up to investigate, assess and enable the use of Deep Learning-based AI methods in various stages of drug design. Deep Learning methods have recently led to a new state-of-the-art performance for bioactivity and toxicity models, enabled generative models for molecules, and even paved the way for AI-based synthetic route planning. This project aims at advancing the technologies further to increase the efficiency & effectiveness of drug discovery, by decreasing toxic effects such as drug-induced liver injury & cardiotox, while assisting designers in further improving the design of compounds.