Cornering an Ever-Evolving Coronavirus: TATX-03, a fully human synergistic multi-antibody cocktail targeting the SARS-CoV-2 Spike Protein with <i>in vivo</i> efficacy
Bibliographic record
Abstract
ABSTRACT The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created an ongoing global human health crisis and will likely become endemic, requiring novel sustainable therapeutic strategies. We report on the discovery of a fully human multi-antibody cocktail (TATX-03) targeting diversified non-overlapping epitopes on the SARS-CoV-2 spike protein that suppressed replication-competent viral titers to undetectable levels in the lungs of SARS-CoV-2 challenged hamsters upon both prophylactic and therapeutic administration. While monotherapy with two of the individual cocktail components also showed clear in vivo protection, neither recapitulated the efficacy of TATX-03. This synergistic effect was further supported by examining in vivo efficacy of these individual antibodies and corresponding combination therapy at a lower dose. Furthermore, in vitro screenings using VSV-particles pseudo-typed with spike proteins representing the SARS-CoV-2 variants of concern Alpha, Beta, and Delta showed that TATX-03 maintained its neutralization potency. These results merit further development of TATX-03 as a potential therapy for SARS-CoV-2 infection with resistance to mutagenic escape.
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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".