The chemistry track explores how AI is revolutionizing drug design and optimization across both small molecule and biologic therapeutics. This track highlights the use of cutting-edge technologies like generative AI, machine learning, and predictive modelling to accelerate drug discovery. From hit identification and lead optimization to improving ADME properties and drug-target interactions, discover how AI is reducing development timelines, optimizing compound libraries, and fast-tracking drug pipelines.
This track is designed for chemists, biologists, computational scientists, data scientists, and R&D leaders in pharmaceutical and biotechnology companies, as well as AI and machine learning experts working across various drug discovery platforms.
Accelerate Drug Design with AI-Driven Optimization
Discover how AI is revolutionizing drug discovery by accelerating hit identification, lead optimization, and biologic design. See how AI tools like generative design and predictive modeling are reducing cycle times and costs by automating synthesis planning and optimizing drug properties.
Transform Drug Discovery with Cutting-Edge AI Technologies
Explore how AI-powered platforms - from generative AI for small molecules to biologic design - are advancing the discovery of more potent, selective, and developable drug candidates. Learn how AI is shaping the future of chemistry in drug design and development.
Enhance Drug-Target Interactions for Faster Optimization
Learn how AI is improving molecular docking, protein structure prediction, and ADME property optimization to fine-tune drug-target interactions. This session will explore how AI makes lead optimization more efficient, pushing the boundaries of what’s possible in drug discovery.
Relevant Speakers
Agenda Highlights
• Generative AI for Small Molecule Discovery: Explore how AI is transforming the design of novel small molecules by predicting and optimizing potency, selectivity, and ADME properties, reducing development timelines and improving compound quality.
• AI-Driven Lead Optimization: Discover how AI tools enhance the optimization of drug leads by improving molecular docking, protein interactions, and refining drug-target binding affinity to accelerate the path from bench to clinic.
• Biologic Design with AI: Learn how AI is revolutionizing biologic drug design, including ADCs, CAR-T therapies, and engineered proteins, by predicting molecular stability, improving payload efficacy, and optimizing manufacturability.
• AI-Powered Synthesis and Automation: See how AI streamlines synthetic chemistry workflows by automating reaction prediction, retrosynthesis planning, and optimizing synthetic routes for high-yield drug production.
• Optimizing ADME and Drug-Target Interactions with AI: Explore how AI is used to predict and optimize ADME properties, improve solubility, permeability, and reduce DDI risks, while refining drug-target interactions for higher therapeutic efficacy.