AI-Driven Next-Generation Ionisable Lipid Development & Screening Strategies for Improved Transfection Efficiency & Endosomal Escape
1:00 pm - Thursday 18th February 2027
- Leveraging machine learning & AI-driven approaches, from foundation-model pretraining to closed-loop active learning, to accelerate novel ionisable lipid identification from limited datasets
- Addressing endosomal escape & payload–carrier compatibility through rational lipid design & formulation optimisation at reduced RNA doses
- Balancing potency, safety & developability when transitioning from research-scale to GMP-ready lipid platforms, carrying model-derived knowledge into process scale-up & CMC
- Screening novel ionisable lipid structures with multi-objective models to optimise transfection & tissue selectivity
