Systematic screening of generic drugs for progressive multiple sclerosis identifies clomipramine as a promising therapeutic
Bibliographic record
Abstract
The treatment of progressive multiple sclerosis (MS) is unsatisfactory. One reason is that the drivers of disease, which include iron-mediated neurotoxicity, lymphocyte activity, and oxidative stress, are not simultaneously targeted. Here we present a systematic screen to identify generic, orally available medications that target features of progressive MS. Of 249 medications that cross the blood-brain barrier, 35 prevent iron-mediated neurotoxicity in culture. Of these, several antipsychotics and antidepressants strongly reduce T-cell proliferation and oxidative stress. We focus on the antidepressant clomipramine and found that it additionally inhibits B-lymphocyte activity. In mice with experimental autoimmune encephalomyelitis, a model of MS, clomipramine ameliorates clinical signs of acute and chronic phases. Histologically, clomipramine reduces inflammation and microglial activation, and preserves axonal integrity. In summary, we present a systematic approach to identify generic medications for progressive multiple sclerosis with the potential to advance rapidly into clinical trials, and we highlight clomipramine for further development.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".