Ghent University Academic Bibliography

Advanced

Quantitative risk assessment via uncertainty analysis in combination with error propagation for the determination of the dynamic Design Space of the primary drying step during freeze-drying

Pieter-Jan Van Bockstal UGent, Séverine Mortier UGent, Jos Corver UGent, Ingmar Nopens UGent, Krist V Gernaey and Thomas De Beer UGent (2017) EUROPEAN JOURNAL OF PHARMACEUTICS AND BIOPHARMACEUTICS. 121. p.32-41
abstract
Traditional pharmaceutical freeze-drying is an inefficient batch process often applied to improve the stability of biopharmaceutical drug products. The freeze-drying process is regulated by the (dynamic) settings of the adaptable process parameters shelf temperature 7; and chamber pressure Pc. Mechanistic modelling of the primary drying step allows the computation of the optimal combination of Ts and Pc in function of the primary drying time. In this study, an uncertainty analysis was performed on the mechanistic primary drying model to construct the dynamic Design Space for the primary drying step of a freeze-drying process, allowing to quantitatively estimate and control the risk of cake collapse (i.e., the Risk of Failure (RoF)). The propagation of the error on the estimation of the thickness of the dried layer L-dried as function of primary drying time was included in the uncertainty analysis. The constructed dynamic Design Space and the predicted primary drying endpoint were experimentally verified for different RoF acceptance levels (1%, 25%, 50% and 99% RoF), defined as the chance of macroscopic cake collapse in one or more vials. An acceptable cake structure was only obtained for the verification runs with a preset RoF of 1% and 25%. The run with the nominal values for the input variables (RoF of 50%) led to collapse in a significant number of vials. For each RoF acceptance level, the experimentally determined primary drying endpoint was situated below the computed endpoint, with a certainty of 99%, ensuring sublimation was finished before secondary drying was started. The uncertainty on the model input parameters demonstrates the need of the uncertainty analysis for the determination of the dynamic Design Space to quantitatively estimate the risk of batch rejection due to cake collapse.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
Freeze-drying, Mathematical modelling, Dynamic Design Space, Quantitative risk assessment, Error propagation, Risk of failure control, MASS-TRANSFER RESISTANCE, PHARMACEUTICAL LYOPHILIZATION, QUALITY, PRODUCT, FORMULATIONS, LAYER, IMPACT, BUILD, CYCLE
journal title
EUROPEAN JOURNAL OF PHARMACEUTICS AND BIOPHARMACEUTICS
Eur. J. Pharm. Biopharm.
volume
121
pages
32 - 41
Web of Science type
Article
Web of Science id
000414621100005
ISSN
0939-6411
1873-3441
DOI
10.1016/j.ejpb.2017.08.015
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
8542266
handle
http://hdl.handle.net/1854/LU-8542266
date created
2017-12-18 10:29:09
date last changed
2018-04-26 09:26:41
@article{8542266,
  abstract     = {Traditional pharmaceutical freeze-drying is an inefficient batch process often applied to improve the stability of biopharmaceutical drug products. The freeze-drying process is regulated by the (dynamic) settings of the adaptable process parameters shelf temperature 7; and chamber pressure Pc. Mechanistic modelling of the primary drying step allows the computation of the optimal combination of Ts and Pc in function of the primary drying time. In this study, an uncertainty analysis was performed on the mechanistic primary drying model to construct the dynamic Design Space for the primary drying step of a freeze-drying process, allowing to quantitatively estimate and control the risk of cake collapse (i.e., the Risk of Failure (RoF)). The propagation of the error on the estimation of the thickness of the dried layer L-dried as function of primary drying time was included in the uncertainty analysis. The constructed dynamic Design Space and the predicted primary drying endpoint were experimentally verified for different RoF acceptance levels (1\%, 25\%, 50\% and 99\% RoF), defined as the chance of macroscopic cake collapse in one or more vials. An acceptable cake structure was only obtained for the verification runs with a preset RoF of 1\% and 25\%. The run with the nominal values for the input variables (RoF of 50\%) led to collapse in a significant number of vials. For each RoF acceptance level, the experimentally determined primary drying endpoint was situated below the computed endpoint, with a certainty of 99\%, ensuring sublimation was finished before secondary drying was started. The uncertainty on the model input parameters demonstrates the need of the uncertainty analysis for the determination of the dynamic Design Space to quantitatively estimate the risk of batch rejection due to cake collapse.},
  author       = {Van Bockstal, Pieter-Jan and Mortier, S{\'e}verine and Corver, Jos and Nopens, Ingmar and Gernaey, Krist V and De Beer, Thomas},
  issn         = {0939-6411},
  journal      = {EUROPEAN JOURNAL OF PHARMACEUTICS AND BIOPHARMACEUTICS},
  keyword      = {Freeze-drying,Mathematical modelling,Dynamic Design Space,Quantitative risk assessment,Error propagation,Risk of failure control,MASS-TRANSFER RESISTANCE,PHARMACEUTICAL LYOPHILIZATION,QUALITY,PRODUCT,FORMULATIONS,LAYER,IMPACT,BUILD,CYCLE},
  language     = {eng},
  pages        = {32--41},
  title        = {Quantitative risk assessment via uncertainty analysis in combination with error propagation for the determination of the dynamic Design Space of the primary drying step during freeze-drying},
  url          = {http://dx.doi.org/10.1016/j.ejpb.2017.08.015},
  volume       = {121},
  year         = {2017},
}

Chicago
Van Bockstal, Pieter-Jan, Séverine Mortier, Jos Corver, Ingmar Nopens, Krist V Gernaey, and Thomas De Beer. 2017. “Quantitative Risk Assessment via Uncertainty Analysis in Combination with Error Propagation for the Determination of the Dynamic Design Space of the Primary Drying Step During Freeze-drying.” European Journal of Pharmaceutics and Biopharmaceutics 121: 32–41.
APA
Van Bockstal, P.-J., Mortier, S., Corver, J., Nopens, I., Gernaey, K. V., & De Beer, T. (2017). Quantitative risk assessment via uncertainty analysis in combination with error propagation for the determination of the dynamic Design Space of the primary drying step during freeze-drying. EUROPEAN JOURNAL OF PHARMACEUTICS AND BIOPHARMACEUTICS, 121, 32–41.
Vancouver
1.
Van Bockstal P-J, Mortier S, Corver J, Nopens I, Gernaey KV, De Beer T. Quantitative risk assessment via uncertainty analysis in combination with error propagation for the determination of the dynamic Design Space of the primary drying step during freeze-drying. EUROPEAN JOURNAL OF PHARMACEUTICS AND BIOPHARMACEUTICS. 2017;121:32–41.
MLA
Van Bockstal, Pieter-Jan, Séverine Mortier, Jos Corver, et al. “Quantitative Risk Assessment via Uncertainty Analysis in Combination with Error Propagation for the Determination of the Dynamic Design Space of the Primary Drying Step During Freeze-drying.” EUROPEAN JOURNAL OF PHARMACEUTICS AND BIOPHARMACEUTICS 121 (2017): 32–41. Print.