Role of membrane structure on the filtrate flux during monoclonal antibody filtration through virus retentive membranes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Virus removal filtration is a critical step in the manufacture of monoclonal antibody products, providing a robust size-based removal of both enveloped and non-enveloped viruses. Many monoclonal antibodies show very large reductions in filtrate flux during virus filtration, with the mechanisms governing this behavior and its dependence on the properties of the virus filter and antibody remaining largely unknown. Experiments were performed using the highly asymmetric Viresolve® Pro and the relatively homogeneous Pegasus™ SV4 virus filters using a highly purified monoclonal antibody. The filtrate flux for a 4 g/L antibody solution through the Viresolve® Pro decreased by about 10-fold when the filter was oriented with the skin side down but by more than 1000-fold when the asymmetric filter orientation was reversed and used with the skin side up. The very large flux decline observed with the skin side up could be eliminated by placing a large pore size prefilter directly on top of the virus filter; this improvement in filtrate flux was not seen when the prefilter was used inline or as a batch prefiltration step. The increase in flux due to the prefilter was not related to the removal of large protein aggregates or to an alteration in the extent of concentration polarization. Instead, the prefilter appears to transiently disrupt reversible associations of the antibodies caused by strong intermolecular attractions. These results provide important insights into the role of membrane morphology and antibody properties on the filtrate flux during virus filtration.
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.
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 | 0.000 | 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) | 0.000 | 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 it