AGILE platform: a deep learning powered approach to accelerate LNP development for mRNA delivery
University of Toronto · University Health Network · +3 more institutions
Abstract
Ionizable lipid nanoparticles (LNPs) are seeing widespread use in mRNA delivery, notably in SARS-CoV-2 mRNA vaccines. However, the expansion of mRNA therapies beyond COVID-19 is impeded by the absence of LNPs tailored for diverse cell types. In this study, we present the AI-Guided Ionizable Lipid Engineering (AGILE) platform, a synergistic combination of deep learning and combinatorial chemistry. AGILE streamlines ionizable lipid development with efficient library design, in silico lipid screening via deep neural networks, and adaptability to diverse cell lines. Using AGILE, we rapidly design, synthesize, and evaluate ionizable lipids for mRNA delivery, selecting from a vast library. Intriguingly, AGILE…
Citation impact
- FWCI
- 31.26
- Percentile
- 100%
- References
- 74
Authors
13Topics & keywords
- Agile software development
- Computational biology
- Nanotechnology
- Computer science
- Chemistry
- Biology
- Software engineering
- Materials science