Qualification of mechanistic models in biopharmaceutical process development

Area of Science:

• Biopharmaceutical Process Development
• Computational Modeling
• Regulatory Science

Background:

• Mechanistic process models are vital for biopharmaceutical process design and control.
• Lack of clear guidelines hinders model qualification and regulatory acceptance.
• Existing frameworks offer partial solutions but require integration.

Purpose of the Study:

• To introduce a systematic and risk-based framework for qualifying mechanistic process models.
• To provide guidance for model suitability assessment in biopharmaceutical development.
• To foster consensus and harmonize modeling practices in the industry.

Main Methods:

• Development of a novel qualification framework integrating established modeling guidelines.
• Application of the framework to two biopharmaceutical case studies: ultrafiltration/diafiltration and chromatography.
• Risk-based assessment of model suitability for decision-making.

Main Results:

• Demonstrated the framework's applicability through successful case study implementations.
• Identified key elements for model qualification, including data requirements and verification methods.
• Provided a structured approach for evaluating model performance and reliability.

Conclusions:

• The proposed framework offers a robust foundation for mechanistic model qualification in biopharmaceutical development.
• It facilitates dialogue and guides modelers towards standardized, risk-based qualification processes.
• Implementation can lead to harmonized industry practices and increased confidence in model-supported decisions.