ReviewImmunologic research2026
mRNA-Encoded antibodies as a next-generation therapeutic paradigm: a rapid and adaptive platform for the prevention and treatment of emerging and re-emerging infectious diseases - A critical review.
Review in Immunologic research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- mRNA-Encoded Antibodies: An Emerging Paradigm in Antiviral Protection.Biomolecules · 2026Review
- Toward Safe and Effective Gene Therapy: Non-Viral Nanostructured Delivery Systems.International journal of nanomedicine · 2026Review
- Mechanisms and applications of camelid variable heavy-chain nanobodies against bacterial and parasitic protozoal pathogens.Frontiers in immunology · 2026Review
- Low effectiveness of influenza vaccines vis-à-vis mechanism of protection by vaccines - potential causes and recommendations to improve control of influenza.Frontiers in immunology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Messenger RNA (mRNA)-encoded antibodies represent a transformative therapeutic platform with the potential to rapidly combat emerging infectious diseases by enabling in situ expression of potent neutralizing antibodies directly in the patient's body. Unlike conventional monoclonal antibody (mAb) therapies, which rely on labor-intensive and time-consuming cell culture production, mRNA-encoded antibodies offer a faster, scalable, and cell-free approach that bypasses protein purification and cold-chain constraints. This strategy has demonstrated considerable promise during the COVID-19 pandemic, where Moderna's mRNA-1940, an mRNA-based neutralizing antibody targeting the SARS-CoV-2 spike protein, entered preclinical and early-phase trials within months of viral emergence, underscoring the potential for rapid response in outbreak settings. The platform leverages advances in nucleoside-modified mRNA, codon optimization, and lipid nanoparticle (LNP) delivery systems to achieve transient, high-level expression of functional antibodies with reduced innate immune activation. Beyond COVID-19, mRNA-encoded antibody approaches have been explored in preclinical models of Zika virus, Ebola virus, and rabies, where a single intramuscular dose provided prophylactic and therapeutic benefits in animal models. As the world faces recurrent viral threats, the development of mRNA-encoded antibodies as a plug-and-play system offers a compelling, adaptable, and clinically feasible strategy for infectious disease preparedness. This review explores the mechanistic foundation, delivery technologies, translational progress, case studies, safety considerations, and future clinical potential of mRNA-encoded antibodies in combating both pandemic and endemic infections.
Indexed as
Identifiers
41521363What 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.