From algorithm to application: AI-powered design of ionizable lipids for mRNA delivery

作者：Danhong Liang, Chi Xu, Haijun Li, Xinpeng Ma, Peng Gao, Bo Ying · 发表于：BME Horizon · 年份：2024 · DOI：10.70401/bmeh.2026.0026 · 研究领域：RNA Interference and Gene Delivery、Lipid Membrane Structure and Behavior、Protein Degradation and Inhibitors

Artificial intelligence (AI) is revolutionizing the design of ionizable lipids, the pivotal components of lipid nanoparticles (LNPs) for messenger RNA (mRNA) delivery, enabling efficient exploration of vast chemical space of ionizable lipids beyond the reach of traditional methods. This mini-review explores the burgeoning field of AI-powered design and optimization of ionizable lipids for mRNA delivery. We also discuss the critical role of high-throughput experimental strategies, particularly barcoding coupled with next-generation sequencing, in generating the large-scale in vivo datasets for model training. Finally, we discuss current challenges, including data quality and the necessity for domain-specific modeling strategies, and present a future outlook on the integration of AI with scientific computing for LNP research.