This preliminary program is subject to change.

11 Empirical Modeling and Experimental QbD


Description:
QbD is typically addressed and implemented by using experimental design, statistics and empirical modeling. Talks are invited to share their experience in using DOE or alternate proposals to DOE, traditional statistics or multivariate latent variable methods in establishing a Design Space

Sponsor:
Topical I: Comprehensive Quality by Design to Develop and Manufacture Pharmaceutical Products
Co-Sponsor(s):
Systems and Process Design (10a), Process Development Division (12), Pharmaceuticals (15b)


Chair:
Mark-John Bruwer
Chief Technology Officer
ProSensus Inc.
McMaster Innovation Park
Hamilton, ON L8S 4L7
Phone Number: 1-905-528-9136
Email: mj.bruwer@prosensus.ca

Co-Chair:
Chris McCready

Papers:
Improving Process Understanding through Good Experimental Planning
Kelly Canter, Pfizer Inc.; Leonard Perry, University of San Diego
Correlating Powder Flowability to Particle Size Distribution Using Chemometric Techniques
Christopher L. Burcham, Eli Lilly and Company; Robert T. Roginski, Eigenvector Research, Inc.
Predictive Modeling of Pharmaceutical Processes with Missing and Noisy Data
Fani Boukouvala, Rutgers University; Fernando Muzzio, Rutgers University; M.G. Ierapetritou, Rutgers University, the State University of New Jersey
Nonlinear Programming Based Methods for PCA Parameter Estimation Using Data with Missing Elements
Rodrigo López-Negrete de la Fuente, Carnegie Mellon University; Salvador Garcia-Munoz, Pfizer Global Research & Development; Lorenz T. Biegler, Carnegie Mellon University