ArticleJournal of nanobiotechnology2024
High-throughput synthesis and optimization of ionizable lipids through A
Article in Journal of nanobiotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Discovery of Novel Ionizable Lipids for Lipid Nanoparticles: Lipophilicity as a Predictor of Squaramide Head Group Lipid Clearance.Small science · 2026Article
- Decoding Undesirable Inflammatory Responses of Nucleic Acid-Delivering Lipid Nanoparticles.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Lipid Nanoparticle Database towards structure-function modeling and data-driven design for nucleic acid delivery.Nature communications · 2026Article
- High-Throughput Strategies for Streamlining Lipid Nanoparticle Development Pipeline.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Review
- Machine learning techniques for lipid nanoparticle formulation.Nano convergence · 2025Review
- Why do lipid nanoparticles target the liver? Understanding of biodistribution and liver-specific tropism.Molecular therapy. Methods & clinical development · 2025Review
- Enhancing nucleic acid delivery by the integration of artificial intelligence into lipid nanoparticle formulation.Frontiers in medical technology · 2025Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundThe efficacy of mRNA-based vaccines and therapies relies on lipid nanoparticles (LNPs) as carriers to deliver mRNA into cells. The chemical structure of ionizable lipids (ILs) within LNPs is crucial in determining their delivery efficiency.
resultsIn this study, we synthesized 623 alkyne-bearing ionizable lipids using the A
conclusionsOverall, our study provides insights into the structure-function relationships of ILs, providing a foundation for the rational design of ILs to enhance the efficacy of LNPs in mRNA delivery.
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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.