A Nanocarrier Approach for Oral Peptide Delivery: Evaluation of Cell‐Penetrating‐Peptide‐Modified Liposomal Formulations in Dogs
Bibliographic record
Abstract
Abstract Oral delivery of peptides is severely limited by their instability and poor absorption in the gastrointestinal tract. In contrast to coadministration strategies using medium‐chain fatty acids, which have recently gained regulatory approval with low oral bioavailabilities ≤ 1% (Rybelsus and Mycapssa), efforts to clinically implement delivery systems based on nanocarriers have not been successful to date. The approved drug‐delivery formulations show fairly accurate correlation between clinical results and nonrodent mammal bioavailability, including Beagle dogs for Rybelsus, indicating that Beagle dogs represent a translationally relevant model. Here, a nanocarrier formulation for the oral administration of peptide therapeutics is reported with systemic targets consisting of liposomes decorated with cyclic cell‐penetrating peptides, which significantly increase oral bioavailability in translationally relevant Beagle dogs. This nanocarrier formulation is optimized using the glycopeptide vancomycin, and results in a considerable oral bioavailability of 3.9%. Further, this nanocarrier system increases the oral bioavailability of the large linear peptide therapeutic exenatide 20‐fold, and consistently achieves effective plasma concentrations in Beagle dogs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".