High‐throughput in silico workflow for optimization and characterization of multimodal chromatographic processes

Author:

Altern Scott H.12,Lyall Jessica Y.3,Welsh John P.45,Burgess Sean3,Kumar Vijesh6,Williams Chris3,Lenhoff Abraham M.6ORCID,Cramer Steven M.12ORCID

Affiliation:

1. Department of Chemical and Biological Engineering Rensselaer Polytechnic Institute Troy New York USA

2. Center for Biotechnology and Interdisciplinary Studies Rensselaer Polytechnic Institute Troy New York USA

3. Purification Development Genentech South San Francisco California USA

4. Process Research and Development Merck & Co., Inc. Rahway New Jersey USA

5. Rivanna Bioprocess Solutions Charlottesville Virginia USA

6. Department of Chemical and Biomolecular Engineering University of Delaware Newark Delaware USA

Abstract

AbstractWhile high‐throughput (HT) experimentation and mechanistic modeling have long been employed in chromatographic process development, it remains unclear how these techniques should be used in concert within development workflows. In this work, a process development workflow based on HT experiments and mechanistic modeling was constructed. The integration of HT and modeling approaches offers improved workflow efficiency and speed. This high‐throughput in silico (HT‐IS) workflow was employed to develop a Capto MMC polishing step for mAb aggregate removal. High‐throughput batch isotherm data was first generated over a range of mobile phase conditions and a suite of analytics were employed. Parameters for the extended steric mass action (SMA) isotherm were regressed for the multicomponent system. Model validation was performed using the extended SMA isotherm in concert with the general rate model of chromatography using the CADET modeling software. Here, step elution profiles were predicted for eight RoboColumn runs across a range of ionic strength, pH, and load density. Optimized processes were generated through minimization of a complex objective function based on key process metrics. Processes were evaluated at lab‐scale using two feedstocks, differing in composition. The results confirmed that both processes obtained high monomer yield (>85%) and removed of aggregate species. Column simulations were then carried out to determine sensitivity to a wide range of process inputs. Elution buffer pH was found to be the most critical process parameter, followed by resin ionic capacity. Overall, this study demonstrated the utility of the HT‐IS workflow for rapid process development and characterization.

Funder

National Institute for Innovation in Manufacturing Biopharmaceuticals

Publisher

Wiley

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