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Record W4409271389 · doi:10.3390/ijms26083456

Recent Update on siRNA Therapeutics

2025· review· en· W4409271389 on OpenAlexaff
Oluwakemi Ebenezer, Abel Kolawole Oyebamiji, John Oludele Olanlokun, Jack A. Tuszyński, Gane Ka‐Shu Wong

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSmall interfering RNAGene silencingMechanism (biology)Computational biologyDiseaseRNA interferenceMedicineBioinformaticsBiologyRNAGeneGeneticsPathology

Abstract

fetched live from OpenAlex

Small interfering RNA (siRNA) has been deemed a promising therapeutic method for treating diverse diseases. siRNA-based therapeutics provide a distinct mechanism of action by selectively targeting and silencing disease-causing genes at the post-transcriptional level. This paper provides an overview of the present state of siRNA-based therapeutics, highlighting their potential in different therapeutic areas. The first section of this review introduces the basic principles of siRNA technology, including its mechanism of action and delivery methods. Subsequently, we discuss the impediments associated with siRNA delivery and manufacturing development and the strategies for overcoming these obstacles. The clinical advancement of siRNA therapeutics in various disease areas, including cancer, genetic disorders, viral infections, and inflammatory diseases, is summarized. Lastly, we summarize the successes, failures, and lessons learned from the development of siRNAs. With advancements in delivery systems and improvements in target selection, the field of medicine can be revolutionized, and siRNA therapeutics can offer new treatment options for patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score0.677

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.375
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations34
Published2025
Admission routes1
Has abstractyes

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