Modelling cellular processes underpinning recombinant monoclonal antibody production by mammalian cells

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This proposal is concerned with 'bioprocessing'. Bioprocessing collectively describes the range of manufacturing processes that enable the production of new biological medicines. You may be familiar with the one of the first biological medicines produced by recombinant DNA technology - a small protein called insulin. Insulin is now used very successfully to treat an increasingly common metabolic disease, diabetes. Before insulin, diabetics suffered a short life fraught with serious medical complications. This project is targeted at the production of other high-value therapeutic proteins by genetically engineered mammalian cells in culture, specifically monoclonal antibodies. In the body, natural antibodies present in the blood play an important role in our immune system: They target disease-causing microbes and foreign substances for removal. Recombinant monoclonal antibodies, being almost identical to natural antibodies, are specifically designed to target diseased cells. Unlike traditional small-molecule medicines such as penicillin and paracetamol, monoclonal antibody biopharmaceuticals are large, complex and relatively fragile proteins which have to be produced by living mammalian cells in culture, genetically engineered to produce the recombinant protein product. They are proving to be highly successful treatments for serious diseases such as rheumatoid arthritis and a range of cancers. It is anticipated that within the next five to ten years up to fifty percent of all drugs in development will be biopharmaceuticals; a very substantial proportion recombinant proteins produced by mammalian cells in culture. Since the first recombinant protein medicines produced by genetically engineered mammalian cells in culture were licensed as therapeutics over 25 years ago, we have learnt to substantially increase the productivity of biopharmaceutical manufacturing processes (bioprocesses). However, they are still complicated and expensive, and industry has to undertake time-consuming screening processes to find engineered cells making adequate amounts of recombinant protein. To date, the output of industrial bioprocesses has predominantly been increased by gradually improving the growth of producer cells in culture, and not by engineering each cell to make the product more efficiently. This is important, because if we knew how to instruct or programme the cell factory appropriately, we could substantially improve the productivity of manufacturing processes and decrease the time it takes to generate a productive cell culture. However this is not a simple problem. The cell utilises and coordinates a diverse range of its complex machinery to turn, for example, recombinant monoclonal antibody genes in its nucleus into a fully folded protein which can be secreted out of the cell. How can we understand this cellular 'production line' well enough so that we can rationally implement strategies to improve flux from recombinant genes to protein product? In this project we will implement a novel, multidisciplinary combination of technical approaches to answer this question; mathematical modelling, gene expression, molecular cell biology, protein analysis and cell culture. We believe this is crucial - an integrated mathematical bioscience approach can massively increase the information content and utility of biological measurements and enable us to understand cellular processes from a systems control perspective. This project will, for the first time, provide a quantitative understanding of the cell factory on which to rationally build strategies to increase the productivity of therapeutic monoclonal antibody production systems. Without this knowledge, cell culture engineering will largely remain based on trial and error.