Explore how machine learning techniques, such as supervised learning and deep learning, predict critical ADME properties like solubility, permeability, and DDI risk.
Discover how computational methods, including molecular docking and quantum chemistry simulations, optimize high-affinity drug-target interactions for enhanced efficacy.
Attila Csikász-Nagy
Attila is a visionary leader with a strong background in computational and systems biology. As a professor and researcher, he has made significant contributions to the field, with an impressive publication record and expertise in bioinformatics. With experience at renowned institutions like Microsoft Research and King's College London, Attila brings a unique blend of scientific knowledge and business management skills to his role as CEO. In addition to his professional pursuits, Attila enjoys playing basketball competitively with his old high school friends.
David Kombo
