Administration of nucleoside-modified mRNA encoding broadly neutralizing antibody protects humanized mice from HIV-1 challenge
Bibliographic record
Abstract
Abstract Monoclonal antibodies are one of the fastest growing classes of pharmaceutical products, however, their potential is limited by the high cost of development and manufacturing. Here we present a safe and cost-effective platform for in vivo expression of therapeutic antibodies using nucleoside-modified mRNA. To demonstrate feasibility and protective efficacy, nucleoside-modified mRNAs encoding the light and heavy chains of the broadly neutralizing anti-HIV-1 antibody VRC01 are generated and encapsulated into lipid nanoparticles. Systemic administration of 1.4 mg kg−1 of mRNA into mice results in ∼170 μg ml−1 VRC01 antibody concentrations in the plasma 24 h post injection. Weekly injections of 1 mg kg−1 of mRNA into immunodeficient mice maintain trough VRC01 levels above 40 μg ml−1. Most importantly, the translated antibody from a single injection of VRC01 mRNA protects humanized mice from intravenous HIV-1 challenge, demonstrating that nucleoside-modified mRNA represents a viable delivery platform for passive immunotherapy against HIV-1 with expansion to a variety of diseases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".