Bibliographic record
Abstract
Aspartate (Asp) isomerization is a common post-translational modification of recombinant therapeutic proteins that can occur during manufacturing, storage, or administration. Asp isomerization in the complementarity-determining regions of a monoclonal antibody may affect the target binding and thus a sufficiently robust quality control method for routine monitoring is desirable. In this work, we utilized a liquid chromatography–mass spectrometry (LC/MS)-based approach to identify the Asp isomerization in the complementarity-determining regions of a therapeutic monoclonal antibody. To quantitate the site-specific Asp isomerization of the monoclonal antibody, a UV detection–based quantitation assay utilizing the same LC platform was developed. The assay was qualified and implemented for routine monitoring of this product-specific modification. Compared with existing methods, this analytical paradigm is applicable to identify Asp isomerization (or other modifications) and subsequently develop a rapid, sufficiently robust quality control method for routine site-specific monitoring and quantitation to ensure product quality. This approach first identifies and locates a product-related impurity (a critical quality attribute) caused by isomerization, deamidation, oxidation, or other post-translational modifications, and then utilizes synthetic peptides and MS to assist the development of a LC-UV–based chromatographic method that separates and quantifies the product-related impurities by UV peaks. The established LC-UV method has acceptable peak specificity, precision, linearity, and accuracy; it can be validated and used in a good manufacturing practice environment for lot release and stability testing. LAY ABSTRACT: Aspartate isomerization is a common post-translational modification of recombinant proteins during manufacture process and storage. Isomerization in the complementarity-determining regions (CDRs) of a monoclonal antibody A (mAb-A) has been detected and has been shown to have impact on the binding affinity to the antigen. In this work, we utilized a mass spectrometry–based peptide mapping approach to detect and quantitate the Asp isomerization in the CDRs of mAb-A. To routinely monitor the CDR isomerization of mAb-A, a focused peptide mapping method utilizing reversed phase chromatographic separation and UV detection has been developed and qualified. This approach is generally applicable to monitor isomerization and other post-translational modifications of proteins in a specific and high-throughput mode to ensure product quality.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".