P.101 Miglustat: a first-in-class enzyme stabiliser for late-onset Pompe Disease
Bibliographic record
Abstract
Background: Late-onset Pompe disease (LOPD) is caused by a deficiency of acid α-glucosidase (GAA), leading to progressive muscle and respiratory decline. Cipaglucosidase alfa (cipa), a recombinant human GAA naturally enriched with bis-mannose-6-phosphate, exhibits improved muscle uptake but is limited by inactivation at near-neutral blood pH. Miglustat (mig), an enzyme stabiliser, binds competitively and reversibly to cipa, enhancing its stability and activity. Methods: In dose-finding studies, Gaa-/- mice were treated with cipa (20 mg/kg) +/- mig (10 mg/kg; equivalent human dose ~260 mg). Clinical study methodologies have been published (Schoser et al. Lancet Neurol 2021:20;1027–37; Schoser et al. J Neurol 2024:271;2810–23). Results: In Gaa-/- mice, cipa+mig improved muscle glycogen reduction more than cipa alone and grip strength to levels approaching wild-type mice. LOPD patients (n=11) treated with cipa alone showed dose-dependent decreases in hexose tetrasaccharide (Hex4) levels by ~15% from baseline, decreasing another ~10% with added mig (260 mg). In a head-to-head study, cipa+mig had a similar safety profile to alglucosidase alfa. Among 151 patients (three trials), mig-related adverse events occurred in 21 (13.9%), none serious. Conclusions: Mig stabilised cipa in circulation, improving cipa exposure, further reducing Hex4 levels and was well tolerated in clinical studies in patients with LOPD. Sponsored by Amicus Therapeutics, Inc.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.013 |
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".