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Untersuchung der partiellen Regression der kleinsten Quadrate in Nanoemulsionen

Untersuchung der partiellen Regression der kleinsten Quadrate in Nanoemulsionen

Asha Patel

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Editorial:
KS OmniScriptum Publishing
Año de edición:
2025
Materia
Farmacología
ISBN:
9786208615574
41,44 €
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QUALITY BY DESIGN-KONZEPT FÜR DIE ENTWICKLUNG VON ARZNEIMITTELN Die multivariate Datenanalyse (MVDA) ist eine Form der Statistik, die dabei hilft, die Beziehungen zwischen Variablen, Beobachtungen und deren Relevanz zueinander mithilfe der Hauptkomponentenanalyse (PCA) sowie die Beziehungen zwischen unabhängigen Variablen und Antworten mithilfe der partiellen kleinsten Quadrate (PLS) zu verstehen. In Verbindung mit Prozesswissen und dem Verständnis der Kritikalität können PLS- und/oder PCA-Modelle verwendet werden, um multivariate statistische Prozesskontrollkarten (MSPC) zu erstellen , um Abweichungen vom Sollverhalten zu ermitteln. Die Kritikalität wird durch die Bewertung des Ausmaßes der Auswirkung einer Variablen (Parameter/Materialattribut) auf eine Antwort (CQA) bestimmt. Daher muss die Beziehung zwischen dem Parameter und der CQA verstanden werden. MVDA verwendet etablierte Algorithmen, um lineare Modelle zu erstellen, die eine Näherungsfunktion und den Grad des begleitenden Rauschens umfassen. MVDA-Modelle dienen dazu, zu bewerten und sicherzustellen, dass sich das Produkt während der Verarbeitung innerhalb des definierten Designraums weiterentwickelt, wodurch letztendlich Material entsteht, das vordefinierte kritische Qualitätsmerkmale erfüllt. Mit dieser Methode werden die Prozessparameter zusammengefasst.

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