SOURCE-LINKED INTELLIGENCE

ALINA: Active Learning Inference for Nucleic Acid Delivery

CORDIS · observation · Publication date unknown

and-error, one-factor-at-a-time approaches that deliver incremental gains and rarely unlock extrahepatic delivery. ALINA will establish the technical and commercial proof-of-concept for an integrated machine learning (ML) and molecular dynamics (MD) platform that accelerates the design and optimization of mRNA-loaded lipid nanoparticle (LNP) formulations. The platform combines curated multi-modal datasets, physics-informed MD descriptors, active-learning experiment selection, and higher-translational biological models to identify globally optimal, FTO-conscious LNP compositions with significantly fewer experiments. The project will deliver (i) an industry-compatible MVP of the ALINA platform, (ii) quantitative benchmarks demonstrating faster convergence and improved predictive accuracy versus current methods, and (iii) an IP strategy covering newly identified lipid components and a commercialization plan combining platform-access services and licensing. By improving development speed, predictive power, resource efficiency, and route-to-impact beyond the liver, ALINA addresses a major

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recordType

award

status

SIGNED

region

EU

value

150000

unit

EUR