Quantitative microcapillary electrophoresis immunoassay (mCE IA) for end-to-end analysis of pertactin within in-process samples and Quadracel® vaccine
Notice bibliographique
Résumé
Protein concentration is an important attribute in the production of subunit or component-based vaccine antigens. Rigorous monitoring of protein concentration is required to identify potential areas for yield improvement. The current GMP method for quantitation is the plate-based ELISA which requires numerous hands-on steps and has low sensitivity in comparison to new microfluidic systems. To address this issue, a sensitive automated microCapillary Electrophoresis ImmunoAssay (mCE IA) method was developed to accurately separate and quantitate pertactin (PRN), an important antigen of the modern acellular Pertussis (aP) vaccine. PRN is reported to be a low-yielding antigen; thus, it is critical to observe its concentration throughout its manufacturing process. First, a primary antibody for PRN was identified to establish suitable immunoprobing conditions for detection of PRN over a wide linear dynamic range that spans 3 orders of magnitude. Next, the pre-adsorbed PRN Drug Substance (DS) was used as a reference standard to quantitate PRN samples against a calibration curve with adequate accuracy and precision. Four representative samples including three in-process steps and final adjuvanted drug product: Quadracel®, were examined to demonstrate the capability of mCE IA to quantitate PRN with high sensitivity and specificity. The matrices of the selected samples contain additional components (e.g. other proteins, growth factors, cell culture media, residual ammonium sulfate, and aluminum adjuvant) often making the quantitation of PRN challenging. The specificity and method linearity were demonstrated by spiking pre-adsorbed PRN DS into the four representative samples. In addition, it was shown that reportable concentrations of PRN for nine downstream process steps as analyzed by our method is comparable to concentrations obtained with ELISA. Most importantly, this study demonstrated that our method's quantitative accuracy is independent of matrix components, as each sample undergoes extensive dilution. This allows for seamless end-to-end analysis of PRN from fermenter harvest, through to complex downstream process samples to adjuvanted drug products. Finally, for the first time the developed and qualified mCE IA method was shown to quantify PRN throughout the entire manufacturing process to provide rapid feedback for process optimizations allowing for accurate yield and step-loss calculations.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,002 | 0,005 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».