دانلود مقاله ISI انگلیسی شماره 63009
ترجمه فارسی عنوان مقاله

تعیین فضای طراحی مبتنی بر مدل فرآیندهای تصفیه کروماتوگرافی پپتید

عنوان انگلیسی
Model-based design space determination of peptide chromatographic purification processes
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
63009 2013 8 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Chromatography A, Volume 1284, 5 April 2013, Pages 80–87

ترجمه کلمات کلیدی
کروماتوگرافی فاز معکوس، پپتیده فضای طراحی، آماده سازی، حساسیت، نیرومندی
کلمات کلیدی انگلیسی
Reversed-phase chromatography; Peptide; Design space; Preparative; Sensitivity; Robustness

چکیده انگلیسی

Operating a chemical process at fixed operating conditions often leads to suboptimal process performances. It is important in fact to be able to vary the process operating conditions depending upon possible changes in feed composition, products requirements or economics. This flexibility in the manufacturing process was facilitated by the publication of the PAT initiative from the U.S. FDA [1]. In this work, the implementation of Quality-by-design in the development of a chromatographic purification process is discussed. A procedure to determine the design space of the process using chromatographic modeling is presented. Moreover, the risk of batch failure and the critical process parameters (CPP) are assessed by modeling. The ideal cut strategy is adopted and therefore only yield and productivity are considered as critical quality attributes (CQA). The general trends in CQA variations within the design space are discussed. The effect of process disturbances is also considered. It is shown that process disturbances significantly decrease the design space and that only simultaneous and specific changes in multiple process parameters (i.e. critical process parameters (CPP) lead to batch failure. The reliability of the obtained results is proven by comparing the model predictions to suitable experimental data. The case study presented in this work proves the reliability of process development using a model-based approach.