Holistic Design of Experiments Using an Integrated Process Model

Bibliographic Details
Title: Holistic Design of Experiments Using an Integrated Process Model
Authors: Thomas Oberleitner, Thomas Zahel, Barbara Pretzner, Christoph Herwig
Source: Bioengineering, Vol 9, Iss 11, p 643 (2022)
Publisher Information: MDPI AG, 2022.
Publication Year: 2022
Collection: LCC:Technology
LCC:Biology (General)
Subject Terms: design of experiments, holistic experimental design, integrated process model, optimal designs, process characterization, biopharmaceutical process validation, Technology, Biology (General), QH301-705.5
More Details: Statistical experimental designs such as factorial, optimal, or definitive screening designs represent the state of the art in biopharmaceutical process characterization. However, such methods alone do not leverage the fact that processes operate as a mutual interplay of multiple steps. Instead, they aim to investigate only one process step at a time. Here, we want to develop a new experimental design method that seeks to gain information about final product quality, placing the right type of run at the right unit operation. This is done by minimizing the simulated out-of-specification rate of an integrated process model comprised of a chain of regression models that map process parameters to critical quality attributes for each unit operation. Unit operation models are connected by passing their response to the next unit operation model as a load parameter, as is done in real-world manufacturing processes. The proposed holistic DoE (hDoE) method is benchmarked against standard process characterization approaches in a set of in silico simulation studies where data are generated by different ground truth processes to illustrate the validity over a range of scenarios. Results show that the hDoE approach leads to a >50% decrease in experiments, even for simple cases, and, at the same time, achieves the main goal of process development, validation, and manufacturing to consistently deliver product quality.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2306-5354
Relation: https://www.mdpi.com/2306-5354/9/11/643; https://doaj.org/toc/2306-5354
DOI: 10.3390/bioengineering9110643
Access URL: https://doaj.org/article/5a2468d14bb446038736b11aeb0e929c
Accession Number: edsdoj.5a2468d14bb446038736b11aeb0e929c
Database: Directory of Open Access Journals
More Details
ISSN:23065354
DOI:10.3390/bioengineering9110643
Published in:Bioengineering
Language:English