High-throughput, AI-assisted design and optimization of lipid nanoparticles for drug delivery

Lipid nanoparticles (LNPs) have demonstrated great potential in drug delivery. To fully unlock the therapeutic effect for various diseases, specific design and optimization of the LNP are necessary, which entails an efficient workflow to navigate the LNP design space and tailor the critical attributes. The convergence of high-throughput technology and artificial intelligence (AI) may provide a transformative paradigm to address this challenge. While high-throughput technology serves as a crucial strategy to generate the reliable, large-scale datasets, AI can correlate the critical biological attributes with the LNP structures by learning from the experimental data obtained through the high-throughput method, enabling efficient LNP discovery. In this review, we will discuss the establishment of datasets through high-throughput technology for AI training. AI-assisted LNP design and optimization will be then summarized. Finally, we give an outlook and challenge to discuss the applications of AI for future clinical LNP development.