Designing Next-Gen LNPs: Tools, Challenges, and Opportunities

Lipid nanoparticles (LNPs) have transformed the field of nucleic acid therapeutics, enabling the clinical success of mRNA vaccines and other genetic medicines. However, the design of next-generation LNPs remains a complex challenge, requiring a balance of efficacy, safety, and precision delivery. This presentation will explore whether rational design of LNPs is truly achievable with current tools, or whether critical gaps remain. We will examine key design parameters — including lipid composition, surface charge, immunogenicity, and tissue biodistribution — and how they can be systematically optimized. Emerging analytical platforms, high-throughput screening methods, and computational modeling offer new opportunities to accelerate rational LNP design, yet important limitations persist, from incomplete knowledge of structure–activity relationships to variability in biological models. By highlighting recent advances and persistent roadblocks, this talk aims to stimulate discussion on how the field can move beyond empirical approaches toward more predictive, design-driven LNP engineering. Ultimately, achieving rational design of next-generation LNPs will be essential for safer, more effective, and more equitable gene-based therapeutics.