Purification of chimeric heavy chain monoclonal antibody EG2‐hFc using hydrophobic interaction membrane chromatography: An alternative to protein‐A affinity chromatography
Bibliographic record
Abstract
Heavy chain monoclonal antibodies are being considered as alternative to whole-IgG monoclonal antibodies for certain niche applications. Protein-A chromatography which is widely used for purifying IgG monoclonal antibodies is also used for purifying heavy chain monoclonal antibodies as these molecules possess fully functional Fc regions. However, the acidic conditions used to elute bound antibody may sometimes also leach protein-A, which is immunotoxic. Low pH conditions also tend to make the mAb molecules unstable and prone to aggregation. Moreover, protein-A affinity chromatography does not remove aggregates already present in the feed. Hydrophobic interaction membrane chromatography (or HIMC) has already been studied as an alternative to protein-A chromatography for purifying whole-IgG monoclonal antibodies. This paper describes the use of HIMC for capturing a humanized chimeric heavy chain monoclonal antibody (EG2-hFC). Binding and eluting conditions were suitably optimized using pure EG2-hFC. Based on this, an HIMC method was developed for capture of EG2-hFC directly from cell culture supernatant. The EG2-hFc purity obtained in this single-step process was high. The glycan profiles of protein-A and HIMC purified monoclonal antibody samples were similar, clearly demonstrating that both techniques captured similarly glycosylated population of EG2-hFc. Moreover, this technique was able to resolve aggregates from monomeric form of the EG2-hFc.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".