Repurposing of rituximab biosimilars to treat B cell mediated autoimmune diseases
Bibliographic record
Abstract
Rituximab, the first monoclonal antibody approved for the treatment of lymphoma, eventually became one of the most popular and versatile drugs ever in terms of clinical application and revenue. Since its patent expiration, and consequently, the loss of exclusivity of the original biologic, its repurposing as an off-label drug has increased dramatically, propelled by the development and commercialization of its many biosimilars. Currently, rituximab is prescribed worldwide to treat a vast range of autoimmune diseases mediated by B cells. Here, we present a comprehensive overview of rituximab repurposing in 115 autoimmune diseases across 17 medical specialties, sourced from over 1530 publications. Our work highlights the extent of its off-label use and clinical benefits, underlining the success of rituximab repurposing for both common and orphan immune-related diseases. We discuss the scientific mechanism associated with its clinical efficacy and provide additional indications for which rituximab could be investigated. Our study presents rituximab as a flagship example of drug repurposing owing to its central role in targeting cluster of differentiate 20 positive (CD20) B cells in 115 autoimmune diseases.
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 | 0.001 |
| 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 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".