Interim analyses of a first-in-human phase 1/2 mRNA trial for propionic acidaemia
Bibliographic record
Abstract
Propionic acidaemia is a rare disorder caused by defects in the propionyl-coenzyme A carboxylase α or β (PCCA or PCCB) subunits that leads to an accumulation of toxic metabolites and to recurrent, life-threatening metabolic decompensation events. Here we report interim analyses of a first-in-human, phase 1/2, open-label, dose-optimization study and an extension study evaluating the safety and efficacy of mRNA-3927, a dual mRNA therapy encoding PCCA and PCCB. As of 31 May 2023, 16 participants were enrolled across 5 dose cohorts. Twelve of the 16 participants completed the dose-optimization study and enrolled in the extension study. A total of 346 intravenous doses of mRNA-3927 were administered over a total of 15.69 person-years of treatment. No dose-limiting toxicities occurred. Treatment-emergent adverse events were reported in 15 out of the 16 (93.8%) participants. Preliminary analysis suggests an increase in the exposure to mRNA-3927 with dose escalation, and a 70% reduction in the risk of metabolic decompensation events among 8 participants who reported them in the 12-month pretreatment period.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".