Jun 2022 | Conference, Deliverable, Deliverables Report, Development Group, Viral Clearance
This member only resource developed by the BioPhorum Development Group Viral Clearance team is based on their analysis of the worst-case conditions benchmarking survey and was presented at the PDA Viral Clearance conference in Brussels in June 2022.Â
Oct 2021 | Benchmarking, Deliverables Report, Development Group, Viral Clearance
A benchmarking survey on the experiences in applying prior knowledge and modular claims to health authority regulatory submission for clinical programs and licensure applications.
Oct 2021 | Conference, Deliverables Report, Development Group, Viral Clearance
Poster presentation at BPI East based on analysis of the Viral Clearance worst-case conditions benchmarking survey.
Oct 2021 | Benchmarking, Deliverables Report, Development Group, Viral Clearance
A benchmarking survey looking at worse-case conditions, which is contributing to a paper that the team are currently writing.
May 2021 | Deliverable, Development Group, Publication, Qualification of Small-Scale Models
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.