AI-Enabled Biologics R&D: From Scientific Data to Business Decisions

The complexity of biologics development requires organisations to integrate scientific expertise with advanced data-driven approaches. AI and machine learning are increasingly being applied across discovery, process development, analytical development, cell-line optimisation and scale-up decision-making. This one-day program helps biologics R&D professionals understand where AI can create meaningful value across the development lifecycle. Participants explore applications ranging from target identification and experimental design to process optimisation, knowledge management and scientific decision support. The program focuses on practical adoption challenges including data quality, model interpretability, validation, governance and the role of scientific judgement in AI-assisted decision-making. Through case discussions and hands-on exercises, participants learn how to translate scientific data into operational recommendations and business decisions.

Who Should Attend

• Biologics R&D Scientists
• Process Development Teams
• CMC Professionals
• Analytical Development Teams
• Cell-Line Development Scientists
• Manufacturing Science & Technology (MSAT) Professionals
• Digital Transformation Teams supporting R&D
• Scientific Project Managers
• R&D Leaders evaluating AI adoption

Business Outcomes

• Identify high-value AI opportunities across biologics R&D workflows.
• Understand how AI can support scientific discovery and development decisions.
• Improve experimental planning through data-driven approaches.
• Convert complex scientific datasets into management-ready insights.
• Evaluate AI outputs with appropriate scientific validation.
• Understand AI implementation requirements related to data, governance and scalability.
• Build a structured approach for AI-enabled R&D transformation.