Dr. Klambauer will present his work at the workshop Towards in silico-guided clinical trials in cancer.
Abstract
Multi-task and representation learning methods have boosted toxicity and bioactivity prediction methods including virtual screening and drug target prediction. Other areas that were influenced by Deep Learning were chemical synthesis and inverse molecular design, drug synergy and drug combination research, and methods relying on high-content microscopy data. This talk give insights into how recent developments in machine learning and Deep Learning have affected early stages of drug discovery and design.