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Preliminary QIG Considerations regarding Pharmaceutical
Process Models
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Background
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This Quality Innovation Group (QIG) document follows on from the first QIG Listen & Learn Focus
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Group (LLFG) on Continuous manufacturing and the second QIG LLFG on Digital novel technologies,
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held on 13 March 2023 and 12-13 October 2023 respectively.
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It is recognised that regulatory expectations for process models in pharmaceutical manufacturing are
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evolving; the intent of this document is to share QIG?s current thinking with stakeholders and seek
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their comments.
- This, in turn, supports adoption of advanced process
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control strategies, continuous process verification, real-time process monitoring and optimisation, and
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automated or even autonomous operation and management of manufacturing processes.
- Process
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models play an increasingly important role in process design and validation, in control strategies and
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during manufacturing process lifecycle.
- The expected outcome from the use of process models is
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enhanced process understanding, (multivariate) monitoring and control, robustness, performance and
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adaptability.
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A model (in the context of pharmaceutical manufacturing) is a mathematical representation of a
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physical or biological process or system.
- Empirical models (e.g., multivariate models used for Statistical Process Control, regression models
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derived from data collected from Design of Experiments), and
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3.
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Scope
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This document addresses preliminary considerations (general principles) for process models, reflecting
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the use of performance-based approaches in pharmaceutical manufacturing processes.
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The scope of this document is limited to process models such as first-principle models, regression
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models, system models, multivariate statistical process control models, and Machine Learning models
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(ML).
- Complex datasets need not be
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submitted.
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Of note, these are just examples.
- Process validation for finished products ? information and data to be provided in regulatory submissions
(EMA/CHMP/CVMP/QWP/BWP/70278/2012-Rev1,Corr.1)
Process validation for the manufacture of biotechnology-derived active substances and data to be provided in the regulatory
submission (EMA/CHMP/BWP/187338/2014)
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Some models may have a dual purpose e.g., used for process development and used as part of the
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control strategy e.g., to set control limits.
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Process validation (as described in the process validation guidelines) has an overarching role to ensure
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that the process consistently delivers material of the intended quality.
- Depending on the model risk, a model verification protocol may be requested,
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including the model performance metrics and the manufacturing process IPC and CQAs that should be
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followed, the respective acceptance criteria, the number of additional data (independent) that would be
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used, and the monitoring period (parallel testing).
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