The Importance of Choosing The Appropriate Matrix to Validate A Bioanalytical Method According to The Study Needs
Notice bibliographique
Résumé
Sylvain Lachance is a Bioanalytical Scientific Expert in the Bioanalytical Division of inVentiv Health Clinical Quebec City's (Canada) site, a CRO offering clinical, commercial and consulting services to the healthcare industry. He is responsible for following up on the conduct of bioanalytical method development activities by enhancing the scientific and technical knowledge of the researchers, bioanalytical project coordinators and of the laboratory technicians. He assists bioanalytical project coordinators in investigations during bioanalyses and method validations. He has been working in the Bioanalytical Division of inVentiv Health Clinical for over 16 years, working as a Research Scientist, Chromatographic Specialist and Scientific Expert. He has worked on multiple method developments in HPLC and LC-MS/MS, specifically on troubleshooting. He has been involved in more than 70 posters and publications in the bioanalytical field for different scientific meetings. Ann Lévesque obtained her PhD in Biochemistry at the Université Laval in Québec City in 1994 studying the biological actions of peptide analogs of the gastrin releasing peptide in the growth inhibition of cancer cells. Prior to joining inVentiv Health Clinical, she held management positions at other Contract Research Organizations. Her publications include over 100 posters, 17 scientific articles and book chapters in the clinical biochemistry and bioanalytical fields. Within inVentiv Health, Dr. Lévesque is responsible for managing the R&D and sample analysis teams performing bioanalytical analysis of small molecules and peptides. She is also acting as the Biomedical Laboratory Director accountable for the oversight of all activities related to the safety testing of samples from subjects enrolled in early stage clinical trials. Since joining the Bioanalytical Division, Dr. Lévesque has been instrumental in the great success of the laboratory by developing a culture of quality, innovation and value. Validation guidelines from different agencies mainly recommend that matrix effect should be studied with hemolyzed and hyperlipidemic samples, while the European agency requires also to investigate matrix effect on special population. When studies are done in countries with different dietary habits, or when a medication is administered to decrease the concentration of the endogenous compounds, should the matrix effect in these conditions be evaluated? Herein, three case studies are described to show the importance of choosing the appropriate matrix for the bioanalytical method validations and for their use to analyze the study samples according to the conditions required by the clinical trials. The case studies presented are related to the use of the testosterone, Omega-3 and cortisol methods.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,153 | 0,178 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,004 | 0,002 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,007 |
| Communication savante | 0,007 | 0,005 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,006 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,005 |
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 source (Gemma direct ou Codex distillé), 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 ».