Chromatography has been a cornerstone of downstream process development (PD) for years, and there is an ever increasing demand for improved speed and efficiency.  Scale-down models are used in process development to optimize operating conditions and study process robustness while expending as little time and material as possible.  The advent of automated liquid handling systems and miniature columns has taken the efficiency of process development to another level by allowing up to eight column runs in parallel with column volumes under 1 ml.  However results between these miniature columns and typical lab scale columns can deviate, resulting in the need for a better understanding of the differences between columns and systems.  Mechanistic models can be used to understand the physics of the process (fluid flow, mass transfer, etc.) as a function of scale.  We have used mechanistic modeling to study the factors leading to differences in pool sizes observed between scales, and to make predictions on lab scale pool sizes from miniature column data.  Results indicate that changes in mass transfer parameters, specifically axial dispersion and film mass transfer rates, between scales leads to the observed differences in pool size.  Additionally, we have studied the effect of system differences between automated liquid handling systems and conventional preparative chromatography systems on process performance.  This work provides new insight on the ability of high-throughput process development to be used for scale down modeling and process characterization. <br/>

Mechanistic modeling analysis of chromatography scale-down models

255th National Meeting (2018)

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.