title: Setting the process parameters for the coating process in order to assure tablet appearance based on multivariate analysis of prior data.
abstract: Designing efficient, robust process parameters in drug product manufacturing is important to assure a drug's critical quality attributes. In this research, an efficient, novel procedure for a coating process parameter setting was developed, which establishes a prediction model for setting suitable input process parameters by utilizing prior manufacturing knowledge for partial least squares regression (PLSR). In the proposed procedure, target values or ranges of the output parameters are first determined, including tablet moisture content, spray mist condition, and mechanical stress on tablets. Following the preparation of predictive models relating input process parameters to corresponding output parameters, optimal input process parameters are determined using these models so that the output parameters hold within the target ranges. In predicting the exhaust air temperature output parameter, which reflects the tablets' moisture content, PLSR was employed based on prior measured data (such as batch records of other products rather than design of experiments), leading to minimal new experiments. The PLSR model was revealed to be more accurate at predicting the exhaust air temperature than a conventional semi-empirical thermodynamic model. A commercial scale verification demonstrated that the proposed process parameter setting procedure enabled assurance of the quality of tablet appearance without any trial-and-error experiments.
authors.affiliation: Formulation Technology Research Laboratories, Daiichi Sankyo Co., Ltd., Hiratsuka 254-0014, Japan; Pharmaceutical Development, Daiichi Sankyo Europe GmbH, Pfaffenhofen 85274, Germany. Electronic address: tanabe.shuichi.h3@daiichisankyo.co.jp.
authors.forename: Shuichi
authors.initials: S
authors.lastname: Tanabe
authors.affiliation: Formulation Technology Research Laboratories, Daiichi Sankyo Co., Ltd., Hiratsuka 254-0014, Japan.
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Nakagawa
authors.affiliation: Formulation Technology Research Laboratories, Daiichi Sankyo Co., Ltd., Hiratsuka 254-0014, Japan.
authors.forename: Tomoyuki
authors.initials: T
authors.lastname: Watanabe
authors.affiliation: Formulation Technology Research Laboratories, Daiichi Sankyo Co., Ltd., Hiratsuka 254-0014, Japan.
authors.forename: Hidemi
authors.initials: H
authors.lastname: Minami
authors.affiliation: Department of Systems Science, Kyoto University, Kyoto 606-8501, Japan.
authors.forename: Manabu
authors.initials: M
authors.lastname: Kano
authors.affiliation: Pharmaceutical Development, Daiichi Sankyo Europe GmbH, Pfaffenhofen 85274, Germany.
authors.forename: Nora A
authors.initials: NA
authors.lastname: Urbanetz
mesh_terms: D002626:Chemistry, Pharmaceutical / Q000379:methods*; D015999:Multivariate Analysis; D013223:Statistics as Topic / Q000379:methods*; D013608:Tablets, Enteric-Coated / Q000138:chemical synthesis*
chemical_list: D013608:Tablets, Enteric-Coated
keywords: Multivariate analysis; Partial least squares regression (PLSR); Process parameter optimization; Scale-up; Tablet film coating