Comparative therapeutic potential of ALX-0171 and palivizumab against RSV clinical isolate infection of well-differentiated primary pediatric bronchial epithelial cell cultures
Bibliographic record
Abstract
Abstract Respiratory syncytial virus (RSV) causes severe lower respiratory tract infections in young infants. There are no RSV-specific treatments available. Ablynx has been developing an anti-RSV F-specific Nanobody®, ALX-0171. To characterise the therapeutic potential of ALX-0171 we exploited our well-differentiated primary pediatric bronchial epithelial cell (WD-PBEC)/RSV infection model, which replicates several hallmarks of RSV disease in vivo. Using 2 clinical isolates (BT2a; Memphis 37), we compared the therapeutic potential of ALX-0171 with palivizumab, which is currently prescribed for RSV prophylaxis in high-risk infants. ALX-0171 treatment (900 mM) at 24 h post-infection reduced apically released RSV titers to near or below the limit of detection within 24 h for both strains. Progressively lower doses resulted in concomitantly diminished RSV neutralisation. ALX-0171 was approximately 3 fold more potent in this therapeutic RSV/WD-PBEC model than palivizumab (mean IC 50 = 346.9-363.6 nM and 1048-1090 nM for ALX-0171 and palivizumab, respectively), irrespective of the clinical isolate. When viral genomic copies (GC) were measured by RT-qPCR, the therapeutic effect was considerably less and GCs were only moderately reduced (0.62 – 1.28 Log 10 copies/mL) by ALX-0171 treatment at 300 and 900 nM. Similar findings were evident for palivizumab. Therefore, ALX-0171 was very potent at neutralising RSV released from apical surfaces but only had a limited impact on virus replication. The data indicate a clear disparity between viable virus neutralisation and GC viral load, the latter of which does not discriminate between viable and neutralised RSV. This study validates the RSV/WD-PBEC model for the pre-clinical evaluation of RSV antivirals.
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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) | 0.001 | 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 | 0.001 |
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".