viral clearance


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The survey results are in – worst-case conditions for viral clearance

Viral clearance studies are mandated as part of the viral safety evaluation of products derived from human or other mammalian cell lines. When acceptable ranges of process parameters are known, the ICH and EMA recommend that scale-down models are evaluated under worst-case conditions for viral clearance. To identify operating parameters that are commonly considered to present worst-case conditions for viral clearance, our Development Group...

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How to overcome the hurdles of using small-scale models

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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Justification of small-scale models: an industry perspective

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.

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Viral clearance: Retrospective evaluation of cycled resin viral clearance studies

This paper sets out a retrospective analysis of industry data, comparing virus clearance in new and repeatedly cycled resins for two of the most commonly used chromatography steps in biopharmaceutical manufacturing: protein A and anion exchange. The vast data, collected over several decades from 12 member companies, was analyzed by the authors with the support of a statistician. The result is a coherent data set in an accessible, collated format.
The compelling conclusion of the paper is that viral clearance capability is not negatively impacted by resin cycling. This supports the view that viral clearance studies for repeatedly cycled resins are not necessary if appropriate cleaning methods are applied. Companies will be able to compare their own product-specific data with the collated data in the paper to provide an evidence-based rationale for health authorities and regulators for their own manufacturing processes.

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