This preliminary program is subject to change.

Application of Multivariate Analysis in Supporting QbD


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
Co-Sponsor(s):
Applied Mathematics and Numerical Analysis (10D)


Chair:
Koji Muteki
Principal Scientist
Pfizer Inc
Eastern Point Rd
Groton, CT 06340
Phone Number: 860.686.2748
Email: koji.muteki@pfizer.com

Co-Chair:
Huiquan Wu
Chemical Engineer
FDA/CDER/OPS, HFD-003
5515 Security Lane, Room 1054
Rockville, MD 20852
Fax Number: 301-443-5225
Email: wuh@cder.fda.gov


Papers:
Assessing Excipient Variability within QbD Drug Product Development
Joseph Kushner IV, Pfizer Worldwide Research and Development
Inversion of Latent Variable Regression Models to Support Product and Process Development
Emanuele Tomba, University of Padova; Massimiliano Barolo, University of Padova; Salvador García-Muñoz, Pfizer Worldwide Research & Development
Implementing a Recipe Based Framework to Support Product Lifecycle Management
Adam Fermier, Janssen Pharmaceuticals; John Cunningham, PDMS; Thomas Difeo, PDMS; John Dingerdissen, PDMS; James Kenyon, PDMS; Steve Mehrman, PDMS; Terry Murphy, PDMS; Eugene Schaefer, PDMS; Tom Schultz, Janssen; Brian Sherry, Janssen Supply Chain; James Weber, PDMS; Paul McKenzie, Janssen Supply Chain
Variable Selection in Multivariate Modeling of Drug Product Formula and Process
Yong Cui, Genentech, Inc. ; Xiling Song, Genentech, Inc.; King Chuang, Genentech, Inc. ; Cadapakam Venkatramani, Genentech, Inc. ; Sueanne Lee, Genentech, Inc. ; Gregory Gallegos, Genentech Inc.; Thirunellai Venkateshwaran, Genentech, Inc. ; Minli Xie, Genentech, Inc.
A Novel QbD Tool for Statistical Data Analysis
Linas Mockus, Purdue University; José Miguel Laínez, Purdue University; G. V. Reklaitis, Purdue University
Mixture Component Prediction Using Iterative Optimization Technology
Koji Muteki, Pfizer Worldwide Research and Development; Daniel O. Blackwood, Pfizer Worldwide Research and Development; Kyle R. Leeman, Pfizer Worldwide Research and Development; George L. Reid, Pfizer Worldwide Research and Development; Yong Zhou, Pfizer Worldwide Research and Development; Yang A. Liu, Pfizer Worldwide Research and Development; Brent Maranzano, Pfizer Worldwide Research and Development; Paul R. Gerst, Pfizer Worldwide Research and Development; Howard W. Ward, Pfizer Worldwide Research and Development; Andreas AM. Mühlenfeld, Pfizer GMS; Matthias Danner, Pfizer GMS