With the advent of Google’s Alphafold2 (3D models) and OpenAI’s ChatGPT4 (Large language models), researchers anticipate game changes in drug development. Alphafold3 (honoured with the Nobel prize of Chemistry on October 2024) would allow structure based drug design in every disease area and ChatGPT could help in diagnoses and personalized medicine. Furthermore AI is used to help set up large international phase 3 trials. However, training the models well depends on the quality of the data used and access to positive as well as negative data, like disease versus healthy. What is the current status?

This year we are pleased to have a diverse expertise of data science for small molecules, nucleic acids and proteins.

We start with dr. Tudor Oprea, who was at the front of using data science in drug discovery, while working in industry as well as academia. He was keynote speaker at the DMD in 2010.

Prof. Jeroen de Ridder applies innovative data science on genomics and epigenomics data sets to understand disease biology.

And dr. Pavel Sinitcyn will explain how data science on proteomics data sets can help drug discovery.