ArticleProceedings of the National Academy of Sciences of the United States of America2025
Rational design and modular synthesis of biodegradable ionizable lipids via the Passerini reaction for mRNA delivery.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed.
- Bioactive lipid-derived nanoparticles for RNA delivery.Materials today (Kidlington, England) · 2026Article
- Overcoming hepatic tropism: Precision engineering of lipid nanoparticles for extrahepatic RNA delivery.Materials today. Bio · 2026Review
- Lipid nanoparticles optimized for large RNA cargo and tissue targeting enhance in vivo genome editing.Nature biotechnology · 2026Article
- Structural evolution of ionizable lipids for nucleic acid delivery.Nature reviews. Chemistry · 2026Review
- Engineering mRNA-LNP Medicines for the Ageing Brain: Opportunities and Challenges for Neurodegenerative Diseases.Exploration (Beijing, China) · 2026Review
- mRNA Therapeutics Beyond Infectious Diseases: Expanding Therapeutic Applications and Future Perspectives.Immunity, inflammation and disease · 2026Review
- Next-Generation Nanocarrier Platforms for RNA Vaccines: Advances in Formulation, Stability Engineering, and Translational Manufacturing Challenges.Pharmaceutics · 2026Review
- Molecular Dynamics-Guided Sterol Engineering of mRNA-Lipid Nanoparticles Reprograms Biodistribution and Enhances Spleen-Selective Immunity.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Spatial Tail Design in Ionizable Lipids Enhances the Safety and Efficacy of mRNA Delivery.Small methods · 2026Article
- Delivery Systems for Therapeutic Genome Editing: Challenges, Innovations, and Future Perspectives.MedComm · 2026Review
- Analytical Characterization and Stability Assessment of RNA-Based Vaccines.Pharmaceutics · 2026Review
- Machine Learning-Driven QSAR Modeling for pKInternational journal of molecular sciences · 2026Article
- Delivery of mRNA Therapeutics Beyond Infectious Diseases: Design Innovations and Applications in Oncology, Cardiovascular, and Rare Genetic Diseases.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Lipid-based nanosystems for atherosclerosis treatment: Evolving approaches and novel therapeutic strategies.Acta pharmaceutica Sinica. B · 2026Review
- Programmable lipid nanoparticles for RNA therapeutics: Design principles and clinical translation.Materials today. Bio · 2026Review
- Myocarditis After mRNA Vaccination: A Metabolic-Innate Immune Cascade Centered on Lipid Nanoparticles.Mediators of inflammation · 2026Review
- A Comprehensive Dataset of Lipid Nanoparticle Compositions and Properties for Nucleic Acid Delivery.Scientific data · 2025Article
- Engineering Anti-Tumor Immunity: An Immunological Framework for mRNA Cancer Vaccines.Vaccines · 2025Review
- A naturally derived lipopeptide lipid nanoparticle platform enabling multiple nucleic acids delivery.Bioactive materials · 2025Article
- High-Throughput Strategies for Streamlining Lipid Nanoparticle Development Pipeline.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
The ionizable lipid component of lipid nanoparticle (LNP) formulations is essential for mRNA delivery by facilitating endosomal escape. Conventionally, these lipids are synthesized through complex, multistep chemical processes that are both time-consuming and require significant engineering. Furthermore, the development of new ionizable lipids is hindered by a limited understanding of the structure-activity relationships essential for effective mRNA delivery. In this work, we have developed a modular platform utilizing the Passerini reaction to rapidly generate large, chemically diverse libraries of biodegradable ionizable lipids. This high-throughput approach enables the systematic exploration of various lipid components-head groups, tails, and spacers-and their impacts on mRNA delivery efficiency. By investigating the hydrogen bonding potential between the lipid's head groups and the mRNA's ribose phosphate complex, we found that optimizing the methylene units between the lipid's head groups and linkages could enhance endosomal escape and, consequently, mRNA delivery efficiencies. Leveraging this insight, our platform has led to the identification of the biodegradable ionizable lipid A4B4-S3, which outperforms the current clinical benchmark, SM-102, in gene editing efficacy in mouse liver following systemic administration and demonstrates the promise for repeat-dose protein replacement treatments. This work not only offers a rapid, scalable method for ionizable lipid synthesis but also deepens our understanding of their structure-activity relationships, paving the way for more effective mRNA therapeutics.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.