Accelerating ionizable lipid discovery for mRNA delivery using machine learning and combinatorial chemistry
Most Cited Paper
in RNA Interference and Gene Delivery
18 Months Post-Publication
Class of 2026
“Accelerating ionizable lipid discovery for mRNA delivery using machine learning and combinatorial chemistry”
A research intelligence initiative by Pepkio
pri.pepkio.com/top-papers/rna-interference-and-gene-delivery/2026/
Topics
Ionizable lipids · mRNA delivery · machine learning · High-throughput screening · Lipid nanoparticles · structure-activity relationship · High-throughput screening · Lipid design · Transfection · predictive modeling · Lipid design · nucleic acid therapeutics · Formulation · In silico screening · chemical space exploration
Share
Cite this ranking
Pepkio Research Index (PRI). Topics and Trends in Most Cited RNA Interference and Gene Delivery Papers, Class of 2026. https://pri.pepkio.com/top-papers/rna-interference-and-gene-delivery/2026. Accessed 2026-07-21. Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459