Where do we see AI the most?

In early stage drug development, much of the work involves identifying biological targets, designing molecules, and validating assays. We will review where AI excels today, where some of the opportunities may be, and greatest opportunities lie, and where human creativity and judgment are still essential.

Roles Already Using AI Heavily

• Computational chemists/medicinal chemists: Design and optimize drug-like molecules, screen vast chemical libraries

  • Current AI usage: Virtual screening, generative molecule design, predicting binding affinities, and ADMET properties

• Structural biologists/bioinformaticians: Predict and analyze 3D protein structures and interactions with ligands

  • Current AI usage: AlphaFold and RoseTTAFold have revolutionized structure prediction

• Genomics & transcriptomics scientists: Analyze genetic and transcriptomic data to identify disease mechanisms and biomarkers

  • Current AI usage: Machine learning is used for clustering, variant effect prediction, and multi-omics integration

• Target discovery & validation teams: Prioritize and validate disease-relevant targets using available evidence

  • Current AI usage: Data mining of literature, omics, and clinical datasets to rank targets