Sustained Delivery of a Monoclonal Antibody against SARS-CoV-2 by Microencapsulated Cells: A Proof-of-Concept Study
Bibliographic record
Abstract
BACKGROUND: Monoclonal antibody (mAb) therapy is a promising antiviral intervention for Coronovirus disease (COVID-19) with a potential for both treatment and prophylaxis. However, a major barrier to implementing mAb therapies in clinical practice is the intricate nature of mAb preparation and delivery. Therefore, here, in a pre-clinical model, we explored the possibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mAb delivery using a mAb-expressing encapsulated cell system. METHODS: Murine G-8 myoblasts were transfected with plasmids coding for the heavy and light chains of CR3022, a well-characterized SARS-CoV-2 mAb that targets the Spike receptor binding domain (RBD), and then encapsulated into alginate microcapsules. The microcapsules were then intraperitoneally implanted into immunocompetent (C57/BL6J) mice and changes in circulating CR3022 titres were assessed. The in vitro and ex vivo characterization of the mAb was performed using western blotting, RBD ELISA, and microscopy. RESULTS: Transfected G-8 myoblasts expressed intact CR3022 IgG at levels comparable to transfected HEK-293 cells. Cell encapsulation yielded microcapsules harbouring approximately 1000 cells/capsule and sustainably secreting CR3022 mAb. Subsequent peritoneal G-8 microcapsule implantation into mice resulted in a gradual increase of CR3022 concentration in blood, which by day 7 peaked at 1923 [1656-2190] ng/mL and then gradually decreased ~4-fold by day 40 post-implantation. Concurrently, we detected an increase in mouse anti-CR3022 IgG titers, while microcapsules recovered by day 40 post-implantation showed a reduced per-microcapsule mAb production. SUMMARY: We demonstrate here that cell microencapsulation is a viable approach to systemic delivery of intact SARS-CoV-2 mAb, with potential therapeutic applications that warrant further exploration.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".