Setting the process parameters for the coating process in order to assure tablet appearance based on multivariate
Shuichi Tanabe1, Hiroshi Nakagawa2, Tomoyuki Watanabe2
1Formulation Technology Research Laboratories, Daiichi Sankyo Co., Ltd., Hiratsuka 254-0014, Japan; Pharmaceutical Development, Daiichi Sankyo Europe GmbH, Pfaffenhofen 85274, Germany.
International Journal of Pharmaceutics
|July 19, 2016
Summary
This study introduces a novel coating process parameter setting procedure using partial least squares regression (PLSR) to predict optimal input parameters. This method ensures drug product quality by minimizing trial-and-error experiments.
Area of Science:
- Pharmaceutical Manufacturing
- Process Engineering
- Quality Assurance
Background:
- Establishing robust process parameters is crucial for drug product quality.
- Current methods may involve extensive trial-and-error, increasing costs and time.
- Utilizing prior manufacturing data can optimize process development.
Purpose of the Study:
- To develop an efficient procedure for setting coating process parameters.
- To establish a predictive model for optimal input parameter selection.
- To ensure critical quality attributes of drug products are met.
Main Methods:
- Developed a novel procedure for coating process parameter setting.
- Utilized prior manufacturing knowledge and partial least squares regression (PLSR).
- Created predictive models relating input and output process parameters.
Main Results:
- PLSR model accurately predicted exhaust air temperature, reflecting tablet moisture content.
- The proposed procedure ensured tablet appearance quality without trial-and-error.
- Achieved higher prediction accuracy compared to conventional thermodynamic models.
Conclusions:
- The developed procedure efficiently sets optimal process parameters for drug product manufacturing.
- PLSR enables accurate predictions using historical data, reducing experimental burden.
- This approach enhances quality assurance and streamlines the manufacturing process.
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