Mana.bio’s researchers leverage AI-driven ML models to rapidly design and optimize lipid nanoparticle parameters for targeted RNA delivery. Three poster presentations demonstrate predictive capacity for LNP safety and specificity in T-cell and lung tissues, paving the way for precision genetic medicines in oncology, immunology, and respiratory disorders.
Key points
- AI-driven ML models predict lipid nanoparticle properties to streamline formulation workflows.
- Poster AMA1447 showcases optimized LNP delivery to T-cells with enhanced tissue specificity and safety.
- Poster AMA1773 demonstrates lung-targeted LNP potency improvements and favorable safety profiles in vivo.
Why it matters: This AI-enabled approach could dramatically streamline lipid nanoparticle design, accelerating precision RNA therapies development and improving safety for diverse clinical applications.
Q&A
- What are lipid nanoparticles?
- How does machine learning design LNP formulations?
- What is extra-hepatic targeting in RNA therapies?
- How is in vivo safety evaluated for LNPs?