Engineering biology applies engineering principles to the design and construction of biological systems. Since its inception twenty-five years ago, approaches to engineering biology have transitioned from traditional wet lab manual methods, to using individual automated devices, to a complete integration of workflows in fully automated laboratories called Biofoundries.
Engineering biology applications require the navigation of large design spaces and the control of assays. To explore large design spaces in reasonable time and cost statistical methods need to be employed. The solution is automation, which provides a throughput high enough to enable the repetition of large numbers of assays. Automation provides higher control and reduces the influence of human operators. High throughput automation generates large measurement datasets which need to be dealt with computational automation.
The work presented in this thesis took place in the London Biofoundry - SynbiCITE. The contribution of the work presented here is a framework and a software system for supporting infrastructure in a Biofoundry. To study the problems that arise from automating an engineering biology application, a case study based on Lycopene was undertaken.
The lycopene application was chosen because it is a good metabolic engineering case study, based on a model pathway with a large design space. The goal of the case study was the optimisation of bioproduction of a metabolite of high bioeconomic interest, lycopene. Through the development of the lycopene case study, lessons were learned: the necessity to design a scoping study and the necessity to care for errors induced by automated methods.
The work presented in the thesis utilises lessons learned from the case-study and presents an infrastructure/framework to support automation orchestration in a Biofoundry. Our framework was validated on data collected with the lycopene application.