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Artificial intelligence-guided design of lipid nanoparticles for mRNA delivery
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Kexin Su, Junjie Qiu, Tengfei Xu, Shuai Liu
Acta Pharmaceutica Sinica B | 2026, 16(2) : 709 - 727
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Acta Pharmaceutica Sinica B | 2026, 16(2): 709-727
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Artificial intelligence-guided design of lipid nanoparticles for mRNA delivery
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Kexin Su, Junjie Qiu, Tengfei Xu, Shuai Liu
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doi: 10.1016/j.apsb.2025.11.029
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Lipid nanoparticles (LNPs) hold significant potential for mRNA-based therapeutics, as evidenced by their successful use in SARS-CoV-2 mRNA vaccines. LNPs effectively protect and transport mRNA to target sites, thereby ensuring its stability and efficient transfection. Despite the progress, some challenges remain in the development of mRNA-LNP delivery systems, such as limited targeting specificity, the complexity of formulations, and the time-consuming and high-throughput screening process. Artificial intelligence (AI) has emerged as a powerful tool to address these challenges, accelerating the design and optimization process of LNPs. AI-guided approaches can improve the efficiency of lipid structure and formulation screening by rapidly identifying key design parameters and employing predictive modeling to optimize LNP properties. The combination of AI and LNP technology offers significant advantages, including enabling the design of more personalized and precise delivery systems, streamlining the development process, and reducing the cost. This review discusses recent advancements in AI-guided mRNA-LNP delivery systems and highlights their potential to revolutionize mRNA therapeutics.
mRNA delivery  /  Lipid nanoparticles  /  Artificial intelligence  /  Machine learning  /  Deep learning  /  Nanomedicine  /  Precise delivery  /  mRNA therapeutics
Kexin Su, Junjie Qiu, Tengfei Xu, Shuai Liu. Artificial intelligence-guided design of lipid nanoparticles for mRNA delivery[J]. Acta Pharmaceutica Sinica B, 2026 , 16 (2) : 709 -727 . DOI: 10.1016/j.apsb.2025.11.029
Year 2026 volume 16 Issue 2
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doi: 10.1016/j.apsb.2025.11.029
  • Receive Date:2025-04-07
  • Online Date:2026-09-17
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  • Received:2025-04-07
  • Revised:2025-06-06
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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