Small-scale models (SSMs) are critical to biopharmaceutical process development, technology transfer, process characterization, and process validation. Demonstrating that an SSM represents the large-scale manufacturing system is also required by regulatory authorities. However, while many biopharmaceutical companies are trying to implement qualified SSMs, there are many hurdles to overcome when designing, executing, and analyzing...
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Small-scale models (SSMs) are widely used in the biopharmaceutical industry. These models are used for process development and optimization, scale-up, technology transfer, process characterization, process validation, virus clearance studies, and resolution of deviations encountered during manufacturing throughout a product’s lifecycle. SSMs are also referred to as ‘scale-down models’ or ‘scaled-down models’. Demonstration that an SSM is representative of the large-scale manufacturing system is called ‘small-scale model qualification’ (SSMQ), which is sometimes also referred to as ‘assessment’, ‘evaluation’, or ‘verification’. The demonstration is an important task that supports process validation and is required by regulatory authorities. However, design, execution and analysis of SSMQ studies can be challenging due to the lack of clear guidance on current best practices. This white paper provides options and tools for design, execution, and data analysis of SSMQs together with illustrative case studies.