Crystallization Process Scale‐Up , a Quality by Design ( QbD ) Perspective

设计质量 实验设计 结晶 过程(计算) 比例(比率) 关键质量属性 质量(理念) 放大 计算机科学 透视图(图形) 工艺设计 工艺工程 工程类 数学 统计 人工智能 化学工程 认识论 操作系统 物理 哲学 粒径 经典力学 量子力学 过程集成
作者
Andrei Zlota
标识
DOI:10.1002/9783527697847.ch11
摘要

Chapter 11 Crystallization Process Scale-Up, a Quality by Design (QbD) Perspective Andrei A. Zlota, Andrei A. Zlota The Zlota Company, LLC, 15 Fairbanks Rd., Sharon, MA, 02067-2858 USASearch for more papers by this author Andrei A. Zlota, Andrei A. Zlota The Zlota Company, LLC, 15 Fairbanks Rd., Sharon, MA, 02067-2858 USASearch for more papers by this author Book Editor(s):Rolf Hilfiker, Rolf Hilfiker Solvias AG, Solid State Development, Kaiseraugst, 4303 SwitzerlandSearch for more papers by this authorMarkus von Raumer, Markus von Raumer Idorsia Pharmaceuticals Ltd, Preformulation & Preclinical Galenics, Hegenheimermattweg 91, Allschwil, 4123 SwitzerlandSearch for more papers by this author First published: 10 December 2018 https://doi.org/10.1002/9783527697847.ch11 AboutPDFPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShareShare a linkShare onFacebookTwitterLinked InRedditWechat Summary Crystallization process scale-up is notoriously challenging, and this account summarizes a QbD (Quality by Design) approach for robust crystallization process development. After defining appropriate Critical Quality Attributes (CQA's), risk analysis is used to select factors to be included in screening DoE's (statistical design of experiments), executed with the support of pre-DoE experiments. Strategies for scale-up factor identification are presented allowing the use of scale-dependent factors in a DoE. The complexity of crystallization processes requires a careful analysis of the impact of several mixing parameters on process results. For antisolvent crystallizations the value of considering mesomixing time as a scale-up factor is discussed. Statistically significant factors identified in the screening DoE's are included in optimization DoE's leading to predictive process models used to justify a proposed Design Space. Mechanistic understanding is provided by PAT (Process Analytical Technology). A remarkable example is included where the regulatory agencies approved a process leading to a mixture of polymorphs. Suitable Design Space verification strategies are mentioned. Polymorphism in the Pharmaceutical Industry: Solid Form and Drug Development RelatedInformation

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