Mass spectrometric characterisation of darbepoetin alfa biosimilars with <i>C</i>‐terminal arginine residues
Bibliographic record
Abstract
Human erythropoietin (EPO) and recombinant human EPO (rEPO) are approximately 30-kDa glycosylated proteins comprising 165 amino acids. Darbepoetin alfa (NESP) is a glycosylated protein encompassing five changes in the amino acid sequence of human EPO, which contains two extra sugar chains. NESP is under patent protection in the USA until May 2024 and in Europe until July 2016, which suggests that the number of NESP biosimilars might substantially increase. The detailed characterisation of biosimilar products are required to ensure the identity and purity of the biosimilar products in terms of safety and efficacy for patients. In this study, a mass spectrometric characterisation of NESP biosimilar products is demonstrated. The study comprises a time-of-flight mass spectrometry characterisation for the asialo-NESPs after sialidase digestion and primary structure characterisation using bottom-up analysis after endoproteinase Glu-C digestion of the core protein. The study revealed that there was a wide range of glycoforms spaced by 365 Da intervals, namely, HexHexNAc units, which indicated that NESP biosimilars likely contained more N-acetyllactosamine units in their molecules. The bottom-up analysis also showed that the NESP biosimilars, as well as a rEPO biosimilar, contain not only the des-arginine product but also the C-terminal arginine product comprising 166 amino acids, whereas the innovator products contain des-arginine EPO comprising only 165 amino acids. The C-terminal arginine EPO would be used as a potential marker for doping with EPO bisimilaras. These findings also point to a need for the investigation of immunogenicity and comparability for the biosimilar products. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".