Lifecycle DoE-The Companion for a Holistic Development Process.

Area of Science:

• Biopharmaceutical Process Development
• Chemical and Biochemical Engineering
• Data Science in Bioprocessing

Background:

• Bioprocess development involves numerous independent experimental studies (Design of Experiments - DoE) with diverse objectives.
• Analyzing DoE studies in isolation hinders the integration of data for a holistic process overview.
• Challenges exist in linking individual experimental data sets for comprehensive process understanding.

Purpose of the Study:

• To elucidate the methodology for constructing a Life-Cycle-DoE (LDoE) by integrating data-driven process knowledge.
• To demonstrate how LDoE facilitates the augmentation of existing models with new experiments in a unified design.
• To showcase the application of LDoE for process characterization and early identification of potentially critical process parameters (pCPPs).

Main Methods:

• Developing a strategy for Life-Cycle-DoE (LDoE) that integrates data from multiple experimental studies.
• Implementing design augmentations to incorporate new experimental data into an existing model.
• Consolidating all bioprocess development data into a single file and unified model.

Main Results:

• The LDoE approach enables the augmentation of existing models with new experiments within a unified design.
• It allows for flexible design adaptations based on subject matter expert requirements, enhancing model predictions.
• The LDoE consolidates all bioprocess development data, enabling process characterization studies using solely development data.

Conclusions:

• Life-Cycle-DoE (LDoE) provides a unified framework for integrating experimental data throughout bioprocess development.
• This approach enhances model accuracy and allows for flexible adaptation to expert needs.
• LDoE facilitates early identification of potentially critical process parameters, enabling timely process adaptations and robust characterization.