A novel effective live-attenuated human metapneumovirus vaccine candidate produced in the serum-free suspension DuckCelt®-T17 cell platform
Bibliographic record
Abstract
Abstract Human metapneumovirus (HMPV) is a major pediatric respiratory pathogen for which there is currently no specific treatment or licensed vaccine. Different strategies have been evaluated to prevent this infection, including the use of live-attenuated vaccines (LAVs). However, further development of LAV approaches is often hampered by the lack of highly efficient and scalable cell-based production systems that support worldwide vaccine production. In this context, avian cell lines cultivated in suspension are currently competing with traditional cell platforms used for viral vaccine manufacturing. We investigated whether the DuckCelt®-T17 avian cell line (Vaxxel) we previously described as an efficient production system for several influenza strains could also be used to produce a new HMPV LAV candidate (Metavac®), an engineered SH gene-deleted mutant of the A1/C-85473 strain of HMPV. To that end, we characterized the operational parameters of multiplicity of infection (MOI), cell density, and trypsin addition to achieve optimal production of the LAV Metavac® in the DuckCelt®-T17 cell line platform. We demonstrated that the DuckCelt®-T17 cell line is permissive and is well adapted to the production of the wild-type A1/C-85473 HMPV and the Metavac® vaccine candidate. Moreover, our results confirmed that the LAV candidate produced in DuckCelt®-T17 cells conserves its advantageous replication properties in LLC-MK2 and 3D-reconstituted human airway epithelium models, as well as its capacity to induce efficient neutralizing antibodies in a mouse model. Our results suggest that the DuckCelt®-T17 avian cell line is a very promising platform for scalable in-suspension serum-free production of the HMPV-based LAV candidate Metavac®.
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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) | 0.001 | 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".