Abstract
AAV gene therapy manufacturing requires scalable processes and reliable small-scale models (SSMs) to support process characterization and regulatory expectations. Ensuring that SSMs accurately represent large‑scale operations is essential for defining robust process acceptance ranges. However, the high dimensionality and multivariate nature of upstream AAV processes limit the use of traditional univariate similarity assessments.
This work presents a multivariate framework for qualifying small-scale cell‑expansion models using historical large-scale data. By applying dimensionality‑reduction and multivariate modeling techniques, we evaluate the alignment between scales and demonstrate the suitability of SSMs for upstream characterization.
Get the full details in our whitepaper: Multivariate Approach to Small-Scale Model Qualification in Upstream Adeno-Associated Virus Production
