The biology track explores how AI is revolutionizing early-stage drug discovery, focusing on accelerating target identification and validation. By decoding complex disease biology and integrating multiomics data, this track showcases how AI is unlocking new therapeutic insights and driving faster, more efficient R&D.
This track is designed for biologists, data scientists, bioinformaticians, researchers, and R&D leaders from pharmaceutical and biotechnology companies, as well as AI and machine learning experts focused on target discovery and precision medicine.
Cut Time and Costs in Target Discovery
See how AI is accelerating hypothesis generation and validation by integrating lab automation, digital twins, and multiomic data — helping reduce timelines and resource spend in early R&D.
Accelerate Your Pipeline With the Latest AI Innovations
Discover the latest AI-driven techniques that are reshaping the future of drug discovery, from multiomics integration and digital twins to lab-in-the-loop automation. Learn how to leverage these innovations to accelerate your research and clinical development processes.
Unlock New Opportunities for Precision Medicine
Learn how AI is enhancing biomarker discovery and enabling precision medicine strategies by combining lab and digital insights. Gain valuable knowledge on how to use AI to refine patient stratification, improve therapeutic efficacy, and streamline the path to clinical success.
Relevant Speakers
Agenda Highlights
- AI-Driven Insights: Uncover how AI is transforming therapeutic discovery by decoding complex disease biology, predicting high-confidence drug targets, and identifying novel disease pathways.
- Multiomics Integration: Explore the integration of genomics, proteomics, and transcriptomics with AI to identify drug targets and biomarkers that drive precision medicine and therapeutic breakthroughs.
- Biomarker Discovery: Discover how AI is enhancing the discovery of novel biomarkers for disease diagnosis and therapeutic efficacy through the integration of digital and traditional lab-based biomarkers.
- Antibody Optimization: Learn how AI is accelerating antibody discovery through generative design, epitope prediction, and optimizing affinity and stability for more effective biologics.
- AI-Powered Digital Twins: Delve into how AI is leveraging digital twin technology for simulating patient-specific biology and optimizing target validation through functional genomics and perturbation modelling.