Lessons Learned from a Global Genedata Deployment: Impact on Automation, Novel Modalities, and AI/ML

In this webinar, Kannan Sankar from Novartis shares how the Biologics Research Center is leveraging Genedata Biologics to transform biologics discovery through structured data capture, AI/ML modeling, and predictive analytics. The session explores how Novartis integrates molecule and assay data to build models that predict developability of antibody-like molecules, enabling faster, smarter decision-making in early-stage drug development. Learn how sequence-structure-function relationships are being used to accelerate timelines, improve molecule quality, and prepare for scalable AI-driven R&D. 

Key Learning Objectives

• Enable predictive modeling of antibody developability using sequence and structure-based features.
• Integrate molecule and assay data to support AI/ML model development and validation.
• Streamline biologics discovery workflows by centralizing data and enabling automation.
• Bridge wet lab and in silico workflows to reduce development timelines and improve molecule quality.
• Support continuous model evaluation by incorporating in silico predictions into the data platform.
• Empower scientists with tools for data-driven decision-making and molecule selection. 

Who Should Watch

• R&D Scientists and Innovation Leaders: Gain insights into predictive modeling and data integration strategies that accelerate biologics discovery.
• Data Scientists, AI/ML Specialists, and Bioinformatics Teams: Explore how to extract and use sequence and structure-based features to build accurate models for molecule developability.
• IT, Informatics, and Scientific Software Developers: Learn how Novartis connects structured informatics tools, AI frameworks, and Genedata Biologics to enable scalable infrastructure.
• Innovation Managers and Program Leads: Understand how AI and digital tools can deliver measurable impact in early-stage drug development.
• Regulatory, Quality, and Data Governance Experts: See how structured data capture and traceability support compliance and IP protection.
• Biotech Executives and Collaborators: Evaluate the strategic value of integrating predictive modeling into biologics R&D.