Edaravone in Amyotrophic Lateral Sclerosis’Lessons from the Clinical Development Program and the Importance of a Strategic Clinical Trial Design
Bibliographic record
Abstract
Edaravone significantly slows progression of amyotrophic lateral sclerosis (ALS), and is the first therapy to receive approval by the Food and Drug Administration (FDA) for the disease in 22 years. Approval of edaravone has marked a new chapter in pharmaceutical development since the key trial included a novel strategic clinical design involving cohort enrichment. In addition, approval was based on clinical trials that had a relatively small patient number and were performed outside of the US. Edaravone was developed through a series of clinical trials in Japan where it was determined that a well-defined subgroup of patients was required to reveal a treatment effect within the study period. Amyotrophic lateral sclerosis is associated with wide-ranging disease heterogeneity (both within the spectrum of ALS phenotypes as well as in the rate of progression). The patient cohort enrichment strategy aimed to address this heterogeneity and should now be considered as a viable, and perhaps preferred, trial design for future studies. Future research incorporating relevant biomarkers may help to better elucidate edaravone’s mechanism of action, pharmacodynamics, and subsequently ALS phenotypes that may preferentially benefit from treatment. In this review, we discuss the edaravone clinical development program, outline the strategic clinical trial design, and highlight important lessons for future trials.
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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 | 0.008 | 0.001 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".