Finite Element Method (FEM) Modeling of Freeze-drying: Monitoring Pharmaceutical Product Robustness During Lyophilization

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• 作者：Xiaodong Chen ; Vikram Sadineni ; Mita Maity ; Yong Quan…
• 关键词：lyophilization ; modeling ; process deviation ; robustness study ; scale ; up
• 刊名：AAPS PharmSciTech
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：16
• 期：6
• 页码：1317-1326
• 全文大小：4,987 KB
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• 作者单位：Xiaodong Chen (1)
  Vikram Sadineni (1)
  Mita Maity (1)
  Yong Quan (1)
  Matthew Enterline (2)
  Rao V. Mantri (1)
  
  1. Drug Product Science and Technology, Bristol-Myers Squibb, 1 Squibb Drive, New Brunswick, NJ, 08903, USA
  2. Department of Chemical Engineering, University of Delaware, Newark, DE, 19716, USA
  
• 刊物主题：Pharmacology/Toxicology; Biotechnology; Biochemistry, general; Pharmacy;
• 出版者：Springer US
• ISSN：1530-9932

文摘

Lyophilization is an approach commonly undertaken to formulate drugs that are unstable to be commercialized as ready to use (RTU) solutions. One of the important aspects of commercializing a lyophilized product is to transfer the process parameters that are developed in lab scale lyophilizer to commercial scale without a loss in product quality. This process is often accomplished by costly engineering runs or through an iterative process at the commercial scale. Here, we are highlighting a combination of computational and experimental approach to predict commercial process parameters for the primary drying phase of lyophilization. Heat and mass transfer coefficients are determined experimentally either by manometric temperature measurement (MTM) or sublimation tests and used as inputs for the finite element model (FEM)-based software called PASSAGE, which computes various primary drying parameters such as primary drying time and product temperature. The heat and mass transfer coefficients will vary at different lyophilization scales; hence, we present an approach to use appropriate factors while scaling-up from lab scale to commercial scale. As a result, one can predict commercial scale primary drying time based on these parameters. Additionally, the model-based approach presented in this study provides a process to monitor pharmaceutical product robustness and accidental process deviations during Lyophilization to support commercial supply chain continuity. The approach presented here provides a robust lyophilization scale-up strategy; and because of the simple and minimalistic approach, it will also be less capital intensive path with minimal use of expensive drug substance/active material. Keywords lyophilization modeling process deviation robustness study scale-up