Evidence map›Paper›PMID 35604765›Full record

ArticleMolecular pharmaceutics2022

Optimization of Lipid Nanoparticles for saRNA Expression and Cellular Activation Using a Design-of-Experiment Approach.

Han Han Ly, Simon Daniel, Shekinah K V Soriano, Zoltán Kis, Anna K Blakney

Abstract read
In one paragraph

Article in Molecular pharmaceutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing 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

44 citing papers in PubMed.

  1. Review
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  3. Transgene sequence codon optimization and composition determines replication competence of self-amplifying RNA.Molecular therapy : the journal of the American Society of Gene Therapy · 2026
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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

5 authors.

Han Han LyMichael Smith Laboratories, School of Biomedical Engineering, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada.
Simon DanielDepartment of Chemical Engineering, Imperial College London, London SW7 2BX, United Kingdom.
Shekinah K V SorianoMichael Smith Laboratories, School of Biomedical Engineering, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada.
Zoltán KisDepartment of Chemical Engineering, Imperial College London, London SW7 2BX, United Kingdom.
Anna K BlakneyMichael Smith Laboratories, School of Biomedical Engineering, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada.ORCID 0000-0002-5812-9689

Funding

Wellcome Trust
6 · The paper itself

Abstract

Lipid nanoparticles (LNPs) are the leading technology for RNA delivery, given the success of the Pfizer/BioNTech and Moderna COVID-19 mRNA (mRNA) vaccines, and small interfering RNA (siRNA) therapies (patisiran). However, optimization of LNP process parameters and compositions for larger RNA payloads such as self-amplifying RNA (saRNA), which can have complex secondary structures, have not been carried out. Furthermore, the interactions between process parameters, critical quality attributes (CQAs), and function, such as protein expression and cellular activation, are not well understood. Here, we used two iterations of design of experiments (DoE) (definitive screening design and Box-Behnken design) to optimize saRNA formulations using the leading, FDA-approved ionizable lipids (MC3, ALC-0315, and SM-102). We observed that PEG is required to preserve the CQAs and that saRNA is more challenging to encapsulate and preserve than mRNA. We identified three formulations to minimize cellular activation, maximize cellular activation, or meet a CQA profile while maximizing protein expression. The significant parameters and design of the response surface modeling and multiple response optimization may be useful for designing formulations for a range of applications, such as vaccines or protein replacement therapies, for larger RNA cargoes.

Indexed as

COVID-19NanoparticlesAmino AlcoholsCaprylatesDecanoatesHumansLiposomesRNA, MessengerRNA, Small Interfering1-octylnonyl 8-((2-hydroxyethyl)(6-oxo-6-(undecyloxy)hexyl)amino)octanoate(4-hydroxybutyl)azanediyl)bis(hexane-6,1-diyl)bis(2-hexyldecanoate)Amino AlcoholsCaprylatesDecanoatesLipid NanoparticlesLiposomesRNA, MessengerRNA, Small InterferingBox−Behnken Designcytokine responsedefinitive screening designdesign-of-experiment (DoE)lipid nanoparticle (LNP)mRNA (mRNA)protein expressionself-amplifying mRNA (saRNA)

Identifiers

PMID35604765
PMCPMC9176215

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.