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Original Article

Spray-drying process optimization for manufacture of drug–cyclodextrin complex powder using design of experiments

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Pages 1219-1229 | Received 23 Aug 2008, Accepted 10 Mar 2009, Published online: 08 May 2009
 

Abstract

Background: Design of experiments (DOE), a component of Quality by Design, is systematic and simultaneous evaluation of variables (process or formulation) to develop a product with predetermined quality attributes. This study presents a case study to understand the effects of process variables in a spray-drying process used in the manufacture of drug-cyclodextrin complex for a drug that is prone to chemical instability at elevated temperature conditions encountered during processing. Methods: Experiments were designed, and data were collected according to a three-factor, three-level face-centered central composite design. The factors investigated were inlet temperature, spray rate, and batch size. Responses analyzed for computing the interaction effects were drug content, impurities, moisture content, and process yield. The spray-drying process conditions were optimized using DOE to maximize production yields while minimizing moisture content and drug-related impurities. Process validation batches were executed using the optimum process conditions obtained from software Design-Expert® to evaluate both the repeatability and reproducibility of spray-drying technique. Results: Optimization of process variables using DOE resulted in a significant improvement of process yields, above 90% and moisture content below 6% (w/w). The impurities were controlled within acceptable limits. The desirability function used to optimize the response variables and observed responses were in agreement with experimental values. These results demonstrated the reliability of selected model for manufacture of powder complex with predictable quality attributes. Conclusion: The study indicates the general applicability of DOE approach to optimize critical process parameters in the manufacture of drug product with desired quality attributes.

Acknowledgments

We sincerely acknowledge the following individuals for their invaluable advice during the course of this work: Dr. A.L.N. Murthy (Indian Statistical Institute, Hyderabad, India) and Dr. M. Ganesan (CPS Product Development Team, Dr. Reddy's Laboratories Limited, Hyderabad, India).

Declaration of interest: The authors report no conflicts of interest.

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