Evidence map›Paper›PMID 28624200›Full record

ArticleMolecular therapy. Nucleic acids2017

Mathematical Modeling: A Tool for Optimization of Lipid Nanoparticle-Mediated Delivery of siRNA.

Radu Mihaila, Dipali Ruhela, Edward Keough, Elena Cherkaev, Silvia Chang, Beverly Galinski, René Bartz, Duncan Brown, Bonnie Howell, James J Cunningham

Abstract read
In one paragraph

Article in Molecular therapy. Nucleic acids, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Modeling onActa pharmaceutica Sinica. B · 2024
    Article
  4. Review
  5. Review
  6. Review
  7. Review
  8. Article
  9. Therapeutic siRNA: state of the art.Signal transduction and targeted therapy · 2020
    Review
  10. Review
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Radu MihailaSirna Therapeutics, 1700 Owens Street, Fourth Floor, San Francisco, CA 94158, USA. Electronic address: mihailar@gene.com.
Dipali RuhelaSirna Therapeutics, 1700 Owens Street, Fourth Floor, San Francisco, CA 94158, USA.
Edward KeoughDepartment of RNA Therapeutics, Merck Sharp & Dohme Corp., West Point, PA 19486, USA.
Elena CherkaevDepartment of Mathematics, University of Utah, Salt Lake City, UT 84112, USA.
Silvia ChangSirna Therapeutics, 1700 Owens Street, Fourth Floor, San Francisco, CA 94158, USA.
Beverly GalinskiSirna Therapeutics, 1700 Owens Street, Fourth Floor, San Francisco, CA 94158, USA.
René BartzDepartment of RNA Therapeutics, Merck Sharp & Dohme Corp., West Point, PA 19486, USA.
Duncan BrownSirna Therapeutics, 1700 Owens Street, Fourth Floor, San Francisco, CA 94158, USA.
Bonnie HowellDepartment of RNA Therapeutics, Merck Sharp & Dohme Corp., West Point, PA 19486, USA.
James J CunninghamDepartment of RNA Therapeutics, Merck Sharp & Dohme Corp., West Point, PA 19486, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lipid nanoparticles (LNPs) have been used to successfully deliver small interfering RNAs (siRNAs) to target cells in both preclinical and clinical studies and currently are the leading systems for in vivo delivery. Here, we propose the use of an ordinary differential equation (ODE)-based model as a tool for optimizing LNP-mediated delivery of siRNAs. As a first step, we have used a combination of experimental and computational approaches to develop and validate a mathematical model that captures the critical features for efficient siRNA-LNP delivery in vitro. This model accurately predicts mRNA knockdown resulting from novel combinations of siRNAs and LNPs in vitro. As demonstrated, this model can be effectively used as a screening tool to select the most efficacious LNPs, which can then further be evaluated in vivo. The model serves as a starting point for the future development of next generation models capable of capturing the additional complexity of in vivo delivery.

Indexed as

cellular pharmacokineticsintracellular traffickinglipid nanoparticlesmathematical modelingRNA interferencesiRNA

Identifiers

PMID28624200
PMCPMC5415968

What OpenQuestion holds

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Registered trials

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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.