Accelerating LNP Formulation Design Using Machine Learning: From Trial-and-Error to Data-Driven Optimisation

• Applying machine learning to LNP formulation design to systematically identify optimal ionisable lipids, compositions, and formulation technologies beyond traditional empirical screening
• Integrating formulation, microfluidics, and biological readouts into data-driven workflows, enabling faster iteration and more informed decision-making during early LNP development
• Reducing formulation development timelines while improving robustness, outlining how ML-guided approaches can support scalable, adaptable LNP strategies as mRNA modalities diversify

Speakers:

Joschka Müller

Founder

FormulAIte