A Thermostable nasal spray dried COVID vaccine candidate
Bibliographic record
Abstract
• Nanoliposomal adjuvant system and spike protein antigen were encapsulated in dry powder. • Vaccine component contents present after storage at high temperatures for 10 months. • Dry powder platform designed for use with commercial nasal delivery device. • High turbinate, olfactory and nasopharynx depositions observed in idealized nasal model. A nasal dry powder adjuvanted subunit COVID vaccine candidate was manufactured via spray drying and evaluated for physicochemical stability and aerosol performance over the course of 10 months under accelerated conditions. A nanoliposomal adjuvant system containing synthetic TLR 4 agonist GLA and synthetic TLR 7/8 agonist 3 M−052 and a trimeric SARS-CoV-2 spike protein antigen were encapsulated using trehalose and varying amounts of trileucine as excipients. 1 % and 3 % trileucine batches as well as a trehalose-only control batch were spray dried to achieve varying levels of particle surface modification and to study the overall effects on stability and aerosol performance. All batches achieved good yields and low processing losses on drying. Samples were held at 25 °C and 40 °C and monitored for physical and chemical stability. All three batches showed excellent performance over the course of the study. Overall morphology; solid phase; moisture content; contents of GLA and 3 M−052; and aerosol performance were largely maintained after exposure to high temperatures for 10 months. Spike protein antigen remained present in all samples after exposure, and liposomal size distributions remained within acceptable ranges for all but one of the samples. Overall, this vaccine candidate showed performance suitable for distribution independent of the cold chain and would be able to withstand high-temperature conditions encountered during last-mile delivery.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".