# Accelerating ionizable lipid discovery for mRNA delivery using machine learning and combinatorial chemistry

*PRI Rank #6 · Topics and Trends in Most Cited RNA Interference and Gene Delivery Papers, Class of 2026*

*Canonical URL: https://pri.pepkio.com/top-papers/rna-interference-and-gene-delivery/2026/rank-6*

| Field | Value |
| --- | --- |
| Rank | #6 |
| 18m citations | 115 |
| Journal | Nature Materials |
| Year | 2024 |
| DOI | 10.1038/s41563-024-01867-3 |
| Corresponding authors | Bowen Li, Daniel G. Anderson |
| Institution | Massachusetts Institute of Technology, United States |

**Ranking page:** [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)

**Paper link:** [10.1038/s41563-024-01867-3](https://doi.org/10.1038/s41563-024-01867-3)

## 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

## 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
```