On 22 November, we are organizing our next TechTalk about Artificial Intelligence in Early Drug Discovery. This TechTalk is initiated by the Universiteit Leiden in collaboration with our AI & Digitalization Knowledge Network! For the other LBSP knowledge networks, check our website: Knowledge network leads
Drug discovery is changing, the influence and catalytic effect of Artificial Intelligence (AI) cannot be denied. History dictates this new development will likely be a synergistic addition to drug discovery rather than a revolutionary replacement of existing methods (like the history of HTS, a new tool in the toolbox). As more and more scientific data is becoming public and more and more computing power becomes available the application of AI in drug discovery offers exciting new opportunities.
Central to drug discovery in the public domain is the ChEMBL database which provides literature obtained bioactivity data for a large group of (protein) targets and chemical structures. Machine learning can leverage this data to obtain predictive models able to predict the activity probability of untested chemical structures contained within the large collections of chemical vendors on the basis of the chemical similarity principle.
In this session we will give an overview of research ongoing at the Leiden Bio Science Park. Central in the research is the usage of machine learning.