Applications of Multivariate Data Analysis In Pharmaceutical Process Development: Traditional and Advanced Multivariate Methods

Wednesday, October 19, 2011: 12:30 PM
Symphony III (Hilton Minneapolis)

Description:
The application of multivariate latent variable methods (PCA, PLS, LPLS, JYPLS, OPLS ..) has dramatically increased in the pharmaceutical sector after the introduction of concepts like Process Analytical Technology and Quality by Design . Early applications of these techniques were heavily concentrated on pure Chemometrics for the development of soft sensors or monitoring. Applications have since evolved from pure Chemometrics isolated from process engineering, to an integral usage of the data from analytical instruments combined with data and models from the process engineering perspective to derive fundamental process understanding from a system. This session seeks submissions where multivariate methods where used to understand analytical information (NIR, UV, HPLC, NMR, FBRM,…etc) in combination with process engineering principles to support or derive process understanding, ultimately seeking for a valid design space. Examples of this work include (but not limited to): Reaction kinetic studies supported by spectra; drug product and process performance and using intermediate complex analytical data; and scale-up.


Sponsor:
Topical I: Comprehensive Quality by Design in Pharmaceutical Development and Manufacture


Chair:
Salvador García-Muñoz
Email: Salvador.Garcia-Munoz@pfizer.com

Co-Chair:
Jacob Albrecht
Email: jacob.albrecht@bms.com



12:30 PM
(497a) Transferring Monitoring Models Between Different Scales Through Multivariate Statistical Techniques
Emanuele Tomba, Pierantonio Facco, Fabrizio Bezzo, Salvador García-Muñoz and Massimiliano Barolo


12:55 PM
(497b) Implementation of Genetic Algorithms In the Generation of High-Order Statistical Models
Brendan C. Mack, Nathan Domagalski, Daniel Hallow, Michael Fenster, Lindsay Hobson and Jose Tabora





2:35 PM
(497f) Insights Into Lactate Metabolism Through Multivariate Analysis of Cell Culture Bioprocess Data
Huong Le, Santosh Kabbur, Ziran Sun, Luciano Pollastrini, Kevin Johnson, Keri Mills, George Karypis and Wei-Shou Hu