AOC 1044 induces exon 44 skipping and restores dystrophin protein in preclinical models of Duchenne muscular dystrophy
Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD) is a severe disorder caused by mutations in the dystrophin gene, resulting in loss of functional dystrophin protein in muscle. While phosphorodiamidate morpholino oligomers (PMOs) are promising exon-skipping therapeutics aimed at restoring dystrophin expression, their effectiveness is often limited by poor muscle delivery. We developed AOC 1044, an antibody-oligonucleotide conjugate (AOC) that combines a PMO-targeting exon 44 with an antibody against the transferrin receptor (TfR1), enhancing delivery to muscle tissues for patients with DMD amenable to exon 44 skipping (DMD44). AOC 1044 induces dose-dependent exon 44 skipping and its mouse-active variant elicited dose-dependent dystrophin restoration in skeletal and cardiac muscle in a DMD mouse model. This treatment also reduced muscle damage, as evidenced by decreases in serum creatine kinase and key liver enzymes, suggesting that restored dystrophin is functionally active. In nonhuman primates, single or repeated AOC 1044 doses resulted in dose-dependent increases in PMO concentration and exon 44 skipping across a range of muscle tissues, including the heart. Collectively, these findings highlight AOC 1044 as a promising therapeutic candidate for patients with DMD44, offering improved muscle targeting and meaningful dystrophin restoration, with potential clinical benefits in reducing muscle degeneration.
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 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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".