Literature DB >> 30414868

Determining Maximum Sublimation Rate for a Production Lyophilizer: Computational Modeling and Comparison With Ice Slab Tests.

Vaibhav Kshirsagar1, Serguei Tchessalov2, Frank Kanka3, David Hiebert4, Alina Alexeenko5.   

Abstract

Equipment capability is an important factor in scale up and technology transfer for lyophilized pharmaceutical products. Experimental determination of equipment capability limits, such as the maximum sublimation rate at a given chamber pressure, is time-intensive for production lyophilizers. Here, we present computational fluid dynamics modeling of equipment capability and compare it with experimental data for minimum controllable pressure ice slab sublimation tests in a 23 m2 shelf area freeze dryer. It is found that the vapor flow in the production scale is characterized by turbulent effects at high sublimation rates. For the considered freeze dryer configuration, the onset of turbulence occurs at a sublimation rate of 17 kg/h and leads to an increase in the minimum controllable pressure by 3-4 mTorr for the flow rates up to 40 kg/h. Variations in the shelf and duct orientations as well as the valve stroke distance and their effect on the equipment limit and pressure uniformity are also discussed. The minimum controllable pressure measured experimentally agreed within 5% with computational fluid dynamics results. For high vapor sublimation rates at final stages of ice slab testing, the condenser load affects the product chamber pressure control. Estimate of condenser pressure changes because of ice accumulation has been included.
Copyright © 2019 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  freeze-drying; heat and mass transfer; lyophilization; quality by design

Mesh:

Substances:

Year:  2018        PMID: 30414868     DOI: 10.1016/j.xphs.2018.10.061

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  2 in total

1.  Recommended Best Practices for Lyophilization Validation-2021 Part I: Process Design and Modeling.

Authors:  Feroz Jameel; Alina Alexeenko; Akhilesh Bhambhani; Gregory Sacha; Tong Zhu; Serguei Tchessalov; Lokesh Kumar; Puneet Sharma; Ehab Moussa; Lavanya Iyer; Rui Fang; Jayasree Srinivasan; Ted Tharp; Joseph Azzarella; Petr Kazarin; Mehfouz Jalal
Journal:  AAPS PharmSciTech       Date:  2021-08-18       Impact factor: 3.246

2.  LyoPRONTO: an Open-Source Lyophilization Process Optimization Tool.

Authors:  Gayathri Shivkumar; Petr S Kazarin; Andrew D Strongrich; Alina A Alexeenko
Journal:  AAPS PharmSciTech       Date:  2019-10-31       Impact factor: 3.246

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.