How AI is disrupting traditional Drug Discovery by leveraging platforms across biology, chemistry and clinical development.

This talk explores how Artificial Intelligence is transforming the traditionally slow, expensive, and failure-prone process of drug discovery. At the center of this shift is PandaOmics—a powerful, cloud-based AI platform that integrates multimodal omics data and biomedical literature to identify and prioritize novel therapeutic targets and biomarkers with high translational potential. In this session, attendees will gain an in-depth understanding of how AI technologies are being applied across the drug discovery pipeline—from target identification to biomarker selection and drug repurposing. The talk will walk through how PandaOmics uses bioinformatics and deep learning to analyze massive datasets across biology, chemistry, and clinical development, enabling rapid hypothesis generation that can be validated in both in vitro and in vivo models. Key learning objectives: 1. Understand how AI is being integrated into the early stages of drug discovery and development. 2. Explore the use of multimodal omics data and natural language processing in identifying novel therapeutic targets. 3. Discover how AI platforms like PandaOmics help reduce time, cost, and risk in drug discovery. 4. Review real-world examples of successful target validation enabled by AI-generated hypotheses. This session is ideal for researchers, biotech professionals, and healthcare innovators looking to explore the frontier of AI-enabled pharmaceutical R&D.