Evidence map›Paper›PMID 36559175›Full record

ReviewPharmaceutics2022

Recent Advances in Lipid Nanoparticles for Delivery of mRNA.

Lei Yang, Liming Gong, Ping Wang, Xinghui Zhao, Feng Zhao, Zhijie Zhang, Yunfei Li, Wei Huang

Open access · goldAbstract readReview
In one paragraph

Review in Pharmaceutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed
10.8field-weighted citation impact, top 1% of its field
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

80 citing papers in PubMed, 139 citations in OpenAlex.

  1. Review
  2. Article
  3. Personalized neoantigen mRNA vaccines for pancreatic cancer: the role of lipid nanoparticle delivery systems.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2026
    Review
  4. Review
  5. Review
  6. Review
  7. Review
  8. Review
  9. Review
  10. Review
  11. Article
  12. Review
  13. Review
  14. Article
  15. Review
  16. Can we cure autoimmunity?Current opinion in immunology · 2026
    Review
  17. Review
  18. Article
  19. Review
  20. Review

20 more citing papers are in PubMed but not listed here.

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

8 authors at 2 institutions in 1 country.

Lei YangCollege of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
Liming GongState Key Laboratory of Bioactive Substance and Function of Natural Medicines, Department of Pharmaceutics, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.ORCID 0000-0002-8163-099X
Ping WangCollege of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
Xinghui ZhaoBeijing Bio-Bank Co., Ltd., Beijing 100107, China.
Feng ZhaoCollege of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
Zhijie ZhangCollege of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
Yunfei LiCollege of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.ORCID 0000-0002-5287-0003
Wei HuangState Key Laboratory of Bioactive Substance and Function of Natural Medicines, Department of Pharmaceutics, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.
Tianjin University of Traditional Chinese Medicine · CNChinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

CAMS Innovation Fund for Medical Sciences (CIFMS) 2021-I2M-1-026
6 · The paper itself

Abstract

Messenger RNA (mRNA), which is composed of ribonucleotides that carry genetic information and direct protein synthesis, is transcribed from a strand of DNA as a template. On this basis, mRNA technology can take advantage of the body's own translation system to express proteins with multiple functions for the treatment of various diseases. Due to the advancement of mRNA synthesis and purification, modification and sequence optimization technologies, and the emerging lipid nanomaterials and other delivery systems, mRNA therapeutic regimens are becoming clinically feasible and exhibit significant reliability in mRNA stability, translation efficiency, and controlled immunogenicity. Lipid nanoparticles (LNPs), currently the leading non-viral delivery vehicles, have made many exciting advances in clinical translation as part of the COVID-19 vaccines and therefore have the potential to accelerate the clinical translation of gene drugs. Additionally, due to their small size, biocompatibility, and biodegradability, LNPs can effectively deliver nucleic acids into cells, which is particularly important for the current mRNA regimens. Therefore, the cutting-edge LNP@mRNA regimens hold great promise for cancer vaccines, infectious disease prevention, protein replacement therapy, gene editing, and rare disease treatment. To shed more lights on LNP@mRNA, this paper mainly discusses the rational of choosing LNPs as the non-viral vectors to deliver mRNA, the general rules for mRNA optimization and LNP preparation, and the various parameters affecting the delivery efficiency of LNP@mRNA, and finally summarizes the current research status as well as the current challenges. The latest research progress of LNPs in the treatment of other diseases such as oncological, cardiovascular, and infectious diseases is also given. Finally, the future applications and perspectives for LNP@mRNA are generally introduced.

Indexed as

lipid nanoparticlesmessenger RNAnon-viral vectorsviral vectors

Identifiers

PMID36559175
PMCPMC9787894
OpenAlexW4311053789

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.