Increasing the Throughput of CE-SDS Experiments for the Determination of Purity in Biotherapeutic Products – A Bridging Case Study
Bibliographic record
Abstract
Capillary electrophoresis sodium dodecyl sulfate (CE-SDS) is a workhorse method for the characterization of purity and impurities attributes of biotherapeutic products. In this study, we compared the performance, throughput, and precision of two instruments manufactured by Sciex: the newly developed BioPhase 8800 and the classical PA800+. Four different monoclonal antibodies, anonymized as mAb A-D, were analyzed under reducing and non-reducing conditions and with manual and automated sample preparation on both instruments. In addition, a design of experiment (DoE) study was carried out to fully exploit the high throughput capabilities of the BioPhase 8800. Results demonstrate that data generated on the BioPhase 8800 were highly comparable to those obtained on the PA800+ instrument and that high precision was easily achievable with both manual and automated sample preparation. Moreover, because the throughput of the BioPhase 8800 is 8-fold higher than that of the PA800+, screening and DoE studies become a mainstream application of CE-SDS experiments.
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.
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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".