Automated and Integrated Micro-scale Downstream Unit Operations for Monoclonal Antibody Process Development

The rapid expansion of monoclonal antibody therapeutics has placed increasing pressure on downstream bioprocess development to deliver scalable, efficient, and data-rich strategies. While high throughput process development has transformed chromatographic development, the absence of micro-scale, automation-compatible workflows that also incorporate non-chromatographic steps has limited the scope of current approaches. Without such platforms, it is difficult to generate holistic process understanding, assess inter-step interactions, or support robust design and optimisation at early stages of development. This thesis set out to design, implement, and evaluate a fully automated micro-scale purification platform capable of reproducing an end-to-end industry-standard model monoclonal antibody downstream process. Benchmark laboratory-scale protocols were successfully translated into micro-scale operations, including capture, viral inactivation, intermediate processing, and polishing, to create an integrated workflow that can operate without manual intervention. The platform was then applied as a rapid development tool, enabling the systematic evaluation of process intermediates, conditions, and outcomes in a high throughput format. By reducing experimental timelines, material requirements, and operator variability, the system provides a reliable surrogate for potential laboratory-scale operations while generating high-quality datasets that can accelerate decision-making. Beyond establishing technical equivalence, the research demonstrates how such micro-scale, automated workflows can unlock new opportunities in process development, optimisation, and design space exploration. Overall, this work delivers the first fully integrated micro-scale purification platform model for monoclonal antibodies, directly addressing key bottlenecks in downstream development. The platform provides a foundation for digital integration, advanced analytics, and autonomous experimentation, supporting the transition of the biopharmaceutical industry towards the Biopharma 4.0 paradigm.