An Integrated Approach to Viral Vector Manufacturing and Supply Chain Network Development

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Advanced Therapy Medicinal Products (ATMPs) form a novel class of biologic therapeutics whichpave the way to prevention and treatment of life-threatening diseases. The versatility ofgenetically-engineered drug delivery vehicles is also seen in preventive healthcare, with recentapprovals of vector-based vaccine platforms. Viral vectors are currently at the forefront of bothnext-generation vaccines and therapeutics; the unprecedented demand for viral vectors forcesmanufacturers to simultaneously tackle engineering product and process-related challenges, whilescaling up their production. This is highlighting the need for sophisticated decision-making tools,which enable effective manufacturing and distribution planning throughout product lifetimes.Process systems engineering (PSE) has traditionally assisted the pharmaceutical, and moregenerally, process industries in the development of such tools. Despite the absence of worksaddressing the novel viral vector industry, a review of literature to date reveals classes oftransferable PSE tools for planning of single- and multi-site manufacturing and distribution networks;these often address complexities of flexible multi-product and multi-purpose manufacture.Computational challenges emerge alongside the problem of planning under uncertainty, which isconsidered in frameworks for capacity planning and portfolio management for the pharmaceuticalindustry. Limitations in well-established approaches emerge and the opportunity brought byapplication-driven tools for the viral vector industry to operations research is highlighted.A series of research aims and objectives is proposed, followed by an overview of the progressto date in light of said objectives. A preliminary mixed-integer linear programming (MILP) modelfor the design and optimisation of UK viral vector supply chains is presented and results illustratethe capabilities and areas of improvement of the developed snapshot model. The framework inturn relies on techno-economic analyses obtained from computer-aided modelling of well-establishedviral vector manufacturing protocols. A local sensitivity analysis highlights a need to systematicallyaccount for uncertainty of the assumed inputs when characterising model outputs.