Journal of Pharmaceutical Innovation

, Volume 4, Issue 4, pp 174–186

Predictive Modeling for Pharmaceutical Processes Using Kriging and Response Surface

Authors

  • Zhenya Jia
    • Department of Chemical and Biochemical EngineeringRutgers–The State University of New Jersey
  • Eddie Davis
    • Department of Chemical and Biochemical EngineeringRutgers–The State University of New Jersey
  • Fernando J. Muzzio
    • Department of Chemical and Biochemical EngineeringRutgers–The State University of New Jersey
    • Department of Chemical and Biochemical EngineeringRutgers–The State University of New Jersey
Process Design, Optimization, Automation, and Control

DOI: 10.1007/s12247-009-9070-6

Cite this article as:
Jia, Z., Davis, E., Muzzio, F.J. et al. J Pharm Innov (2009) 4: 174. doi:10.1007/s12247-009-9070-6

Abstract

Powder feeding is a fundamental unit operation in the pharmaceutical industry. For the cases in which first-principle process models are unknown, such as when new powder mixture feeding operations are being evaluated, or no longer accurately describe current operating behavior, surrogate model-based approaches can be employed in order to quantify input–output behavior. In this work, two such metamodeling techniques—kriging and response surface methods—are used to predict a loss-in-weight feeder unit’s flow variability in terms of unit flowability and feed rate. Based on a comparison of predicted with experimental values, an iteratively constructed kriging model is found to more accurately capture the feeder system behavior compared with the response surface methodology. Although feeders are used as a case study in this paper, the kriging methodology is general to address other processes where first-principle models are not available.

Keywords

Feeders Modeling Kriging Response surface Optimization Powder feeding

Copyright information

© International Society for Pharmaceutical Engineering 2009