A new model for drug development

On average, it costs nearly $1 billion and takes almost 10 years to bring a new medicine to market. MBZUAI Department Chair and Professor of Machine Learning Le Song is aiming to reduce both of these significantly using a powerful, AI-driven simulation.

Taking rich data from the societal level, all the way down through organs, tissues, cells, and into the molecular level, he aims to build the most comprehensive model of the human body currently available. In doing so, he will effectively remove the need for biological research done in a wet lab and chart a new path to drug discovery.

Song is an experienced educator and researcher in the field of machine learning and artificial intelligence. He is an active member of several regional and international groups in this field and was a chair of the 39th International Conference on Machine Learning (ICML 2022).

Prior to joining MBZUAI, Song served as an associate professor of computational science and engineering and the associate director of the Center for Machine Learning at Georgia Institute of Technology in the USA. He holds a Ph.D. in computer science from the University of Sydney and National ICT Australia. He has published more than 160 papers in peer-reviewed, top machine learning conferences and journals such as NeurIPS, ICML, ICLR, AISTATS and JMLR during the past 15 years.