Integrated ultra scale-down and multivariate analysis of flocculation and centrifugation for enhanced primary recovery

Abstract

A linked ultra scale-down (USD) flocculation and centrifugation system facilitates rapid bioprocess development and evaluation. These techniques allow studies to be undertaken at high throughput using as little as 50 mL of feed material. They enable the investigation of multiple conditions, thus generating a relatively large amount of data.This study establishes USD flocculation and centrifugation and joins a sequential multivariate data analysis (MVDA) to evaluate the multiparameter effects on primary recovery performance. MVDA techniques such as Principal Component Analysis (PCA) and Partial Least Squares (PLS) were used to handle the complex data sets and investigate the relationships between process parameters and responses. A strategy to assess floc characteristics using PCA was proposed to eliminate the visual inspection, and aid in the analysis, of particle size distribution (PSD) datasets. The PSD of non-sheared and sheared flocs provide good indicators of floc centrifuge performance.The findings show that this USD system can be used to forecast pilot scale performance. The sequential analysis demonstrated that the produced flocs are shear-sensitive in which feed preparation and process shear significantly impact the centrifugation of those flocs. Strong flocs may not necessarily result from high Camp number values (≥ 105) where optimisation of the flocculation chemical parameters is required.The novel integration of the USD systems with MVDA is a powerful platform to optimise and expand process know-how.