ArticleScientific data2025
A Comprehensive Dataset of Lipid Nanoparticle Compositions and Properties for Nucleic Acid Delivery.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Critical chemistry manufacturing and controls considerations for mRNA lipid nanoparticle translation.Discover nano · 2026Review
- Lipid Nanoparticles for Gene Therapy: Unresolved Challenges in Manufacturing, Transdermal Delivery, Machine Learning, Endosomal Escape, and the Protein Corona.Pharmaceutics · 2026Review
- Extracellular vesicles: Navigating new frontiers in glioblastoma therapy.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2026Review
- The Application of Nanomaterials in Kidney Stone Disease: Emerging Strategies for Early Diagnosis, Targeted Therapy, and Prevention.International journal of nanomedicine · 2026Review
- A Comprehensive Dataset of Lipid Nanoparticle Compositions and Properties for Nucleic Acid Delivery.Scientific data · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Lipid nanoparticles (LNPs) have emerged as the leading delivery platform for nucleic acid therapeutics, with clinical success demonstrated in mRNA vaccines and therapeutic applications. However, rational design of LNP remains challenging due to the complex relationships among LNP composition, physicochemical properties, and biological performance, as well as the scattered experimental data across the literature. Here, we present LNP Atlas, a comprehensive dataset containing LNP formulations extracted from peer-reviewed publications. We developed an artificial intelligence-assisted data extraction workflow, followed by automated standardization pipelines implemented in Python to ensure data consistency and quality. The dataset contains lipid types and compositions, including molar ratios and SMILES codes, physicochemical properties (particle size, polydispersity index, zeta potential), synthesis parameters, and bioactivity profiles. This resource is expected to support the research community by facilitating data-driven insights into lipid nanoparticle formulation and accelerating the development of effective nucleic acid delivery systems.
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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.