Integrative Transcriptome Analyses Empower the Anti-COVID-19 Drug Arsenal
Bibliographic record
Abstract
The beginning of the 21st century has been marked by three distinct waves of zoonotic coronavirus outbreaks into the human population. The COVID-19 (coronavirus disease 2019) pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and emerged as a global threat endangering the livelihoods of millions worldwide. Currently, and despite collaborative efforts, diverse therapeutic strategies from ongoing clinical trials are still debated. To address the need for such an immediate call of action, we leveraged the largest dataset of drug-induced transcriptomic perturbations, public SARS-CoV-2 transcriptomic datasets, and expression profiles from normal lung transcriptomes. Most importantly, our unbiased systems biology approach prioritized more than 50 repurposable drug candidates (e.g., corticosteroids, Janus kinase and Bruton kinase inhibitors). Further clinical investigation of these FDA-approved candidates as monotherapy or in combination with an antiviral regimen (e.g., remdesivir) could lead to promising outcomes in patients with COVID-19.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".