ArticleSmall (Weinheim an der Bergstrasse, Germany)2025
Rational Design of Lipid Nanoparticles for Enhanced mRNA Vaccine Delivery via Machine Learning.
Article in Small (Weinheim an der Bergstrasse, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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
23 citing papers in PubMed.
- Dual pKa Lipid Nanoparticles for Lung-tropic mRNA Delivery and pH-Programmed Endosomal Escape.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- 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
- A novel machine learning framework-based rapid screening of ionizable lipids in LNPs for highly-efficient mRNA expression.Acta pharmaceutica Sinica. B · 2026Article
- Artificial Intelligence-Driven Nanomedicine: From Drug Formulation and Nanocarrier Design to Clinical Translation.Pharmaceutics · 2026Review
- Functionalized Lipid Nanoparticles for Targeted RNA Delivery in Immune and Inflammatory Diseases.Biomedicines · 2026Review
- Functional Reclassification of Lipid-Based Drug Delivery Systems and Advances in Formulation Strategies and Manufacturing Challenges.AAPS PharmSciTech · 2026Review
- Pharmaceutical design of mRNA vaccines for endemic infectious diseases: integrating antigen discovery with platform engineering.Clinical and experimental vaccine research · 2026Review
- Artificial intelligence for drug delivery: Yesterday, today and tomorrow.Acta pharmaceutica Sinica. B · 2026Review
- Machine learning empowered formulation design, optimization and characterization of nanoparticulate drug delivery systems: Current applications, challenges, and future perspectives.Acta pharmaceutica Sinica. B · 2026Review
- Artificial intelligence-guided design of lipid nanoparticles for mRNA delivery.Acta pharmaceutica Sinica. B · 2026Review
- Simulation Insights into the Assembly of Polyplexes for RNA Delivery.Biomacromolecules · 2025Article
- mRNA delivery systems 2.0: Engineering extrahepatic delivery for non-vaccine therapeutics.Materials today. Bio · 2025Review
- Harnessing smart nanomaterials to reprogram neutrophil plasticity in immune modulation.Journal of nanobiotechnology · 2025Review
- Self-assembled extracellular matrix-lipid nanoparticle composite for site-specific siRNA delivery to improve cardiac repair post-myocardial infarction.Materials today. Bio · 2025Article
- Emerging Approaches for the Discovery of Lipid-Based RNA Delivery Systems.Pharmaceutics · 2025Review
- The Use of Computational Approaches to Design Nanodelivery Systems.Nanomaterials (Basel, Switzerland) · 2025Review
- Recent strategies for enhanced delivery of mRNA to the lungs.Nanomedicine (London, England) · 2025Review
- Rational Design of Lipid Nanoparticles for Enhanced mRNA Vaccine Delivery via Machine Learning.Small (Weinheim an der Bergstrasse, Germany) · 2025Article
- ApoE deficiency protects from mRNA vaccine-induced mitochondrial dysfunction at the injection site under metabolic stress.Theranostics · 2025Article
Corrections and comments
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Authors and funding
28 authors.
Funding
Abstract
Since the coronavirus pandemic, mRNA vaccines have revolutionized the field of vaccinology. Lipid nanoparticles (LNPs) are proposed to enhance mRNA delivery efficiency; however, their design is suboptimal. Here, a rational method for designing LNPs is explored, focusing on the ionizable lipid composition and structural optimization using machine learning (ML) techniques. A total of 213 LNPs are analyzed using random forest regression models trained with 314 features to predict the mRNA expression efficiency. The models, which predict mRNA expression levels post-administration of intradermal injection in mice, identify phenol as the dominant substructure affecting mRNA encapsulation and expression. The specific phospholipids used as components of the LNPs, as well as the N/P ratio and mass ratio, are found to affect the efficacy of mRNA delivery. Structural analysis highlights the impact of the carbon chain length on the encapsulation efficiency and LNP stability. This integrated approach offers a framework for designing advanced LNPs and has the potential to unlock the full potential of mRNA therapeutics.
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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.