ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024
In Silico Screening Accelerates Nanocarrier Design for Efficient mRNA Delivery.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 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.
- Mechanisms and determinants of mRNALipid Nanoparticle biodistribution: From pharmacokinetics to clinical translation.Bioengineering & translational medicine · 2026Review
- Nanoengineering Systems for Gene Therapy: Mechanisms, Modalities, and Future Directions.International journal of molecular sciences · 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
- Precision Targeting of Myeloid Cells via Peptide Dendrimer-Lipid Nanocarriers: A Novel Platform for Potent Cancer Immunotherapies.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Artificial Intelligence-Driven Nanoarchitectonics for Smart Targeted Drug Delivery.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- Machine Learning-Enhanced Nanoparticle Design for Precision Cancer Drug Delivery.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- The blood-brain barriers: novel nanocarriers for central nervous system diseases.Journal of nanobiotechnology · 2025Review
- In Silico Screening Accelerates Nanocarrier Design for Efficient mRNA Delivery.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lipidic nanocarriers are a broad class of lipid-based vectors with proven potential for packaging and delivering emerging nucleic acid therapeutics. An important early step in the clinical development cycle is large-scale screening of diverse formulation libraries to assess particle quality and payload delivery efficiency. Due to the size of the screening space, this process can be both costly and time-consuming. To address this, computational models capable of predicting clinically relevant physio-chemical properties of dendrimer-lipid nanocarriers, along with their mRNA payload delivery efficiency in human cells are developed. The models are then deployed on a large theoretical nanocarrier pool consisting of over 4.5 million formulations. Top predictions are synthesised for validation using cell-based assays, leading to the discovery of a high quality, high performing, candidate. The methods reported here enable rapid, high-throughput, in silico pre-screening for high-quality candidates, and have great potential to reduce the cost and time required to bring mRNA therapies to the clinic.
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.