In-line monitoring of surfactant clearance in viral vaccine downstream processing
Bibliographic record
Abstract
PURPOSE: The goal of this study is to examine the suitability of in-line infrared measurements to monitor, in real-time, surfactant concentration in the viral vaccine drug substance during a 50KDa tangential flow filtration (TFF) process. METHODS: A ReactIR™ 702L instrument was used to gather spectra of process off-line samples and reference materials to assess the feasibility of monitoring surfactant concentration during a TFF process in real-time. Both univariate and multivariate models were used to evaluate the off-line sample data and were found to be in good agreement with surfactant concentration values obtained by HPLC. These results were used as justification for a real-time TFF experiment with live process material. RESULTS: spectral region can be used to predict surfactant concentrations between TFF exchanges 8 to 15. CONCLUSION: The results of this study demonstrated suitability of an in-line infrared measurement to monitor surfactant concentration in the viral vaccine drug substance between exchanges 8-15 of a 50 kDa tangential flow filtration process. The preliminary multivariate model used for this work can be further optimized for the in-line use at manufacturing scale.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".