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Thesis Where Reference Has Been Made to the Work of Others Multi-Objective, Multiphasic and Multi-Step Self-Optimising Continuous Flow Systems Adam D. Clayton Submitted in accordance with the requirements for the degree of Doctor of Philosophy School of Chemical and Process Engineering February 2020 The candidate confirms that the work submitted is his/her own, except where work which has formed part of jointly-authored publications has been included. The contribution of the candidate and the other authors to this work has been explicitly indicated below. The candidate confirms that appropriate credit has been given within the thesis where reference has been made to the work of others. The work in Chapter 1 has appeared in: A. D. Clayton, J. A. Manson, C. J. Taylor, T. W. Chamberlain, B. A. Taylor, G. Clemens and R. A. Bourne, React. Chem. Eng., 2019, 4, 1545-1554. ADC, JAM and CJT were responsible for preparation of the review. The contribution from other authors was project supervision (TWC, BAT, GC, RAB). The work in Chapter 2 has appeared in: A. M. Schweidtmann, A. D. Clayton, N. Holmes, E. Bradford, R. A. Bourne and A. A. Lapkin, Chem. Eng. J., 2018, 352, 277-282. ADC was responsible for carrying out all experimentation for one of the case studies, improving the optimisation program and data analysis including modelling and simulations. The contribution from other authors was writing the optimisation algorithm (AMS, EB, AAL), experimentation for a second case study (NH) and project supervision (RAB, AAL). The work in Chapter 3 has appeared in: A. D. Clayton, A. M. Schweidtmann, G. Clemens, J. A. Manson, C. J. Taylor, C. G. Niño, T. W. Chamberlain, N. Kapur, A. J. Blacker, A. A. Lapkin and R. A. Bourne, Chem. Eng. J., 2020, 384, 123340. ADC was responsible for carrying out all experimentation, data modelling and simulations. The contribution from other authors was coding support (AMS, JAM, CJT), reactor construction (CGN) and project supervision (GC, TWC, NK, AJB, AAL, RAB). The work in Chapter 4 has appeared in: J. A. Manson, A. D. Clayton, C. G. Niño, R. Labes, T. W. Chamberlain, A. J. Blacker, N. Kapur and R. A. Bourne, CHIMIA, 2019, 73, 817-822. ADC was responsible for carry out reactor characterisation and all subsequent experimentation. The contribution from other authors was writing the optimisation algorithm (JAM), construction of the LED light array (CGN), preparation of the manuscript for publication (RL) and project supervision (TWC, AJB, NK, RAB). The work in Chapter 5 has appeared in: A. D. Clayton, L. A. Power, W. Reynolds, C. Ainsworth, D. R. J. Hose, M. F. Jones, T. W. Chamberlain, A. J. Blacker and R. A. Bourne, J. Flow. Chem., 2020, 10, 199-206. ADC was responsible for carrying 2 out all optimisation experiments, data modelling, reactor characterisation and improving the optimisation program. The contribution from other authors was pKa determination (LP), characterisation of the membrane-based separator (WR) and project supervision (CA, DRJH, MFJ, TWC, AJB, RAB). This copy has been supplied on the understanding that it is copyright material and that no quotation from the thesis may be published without proper acknowledgement. © 2020 The University of Leeds and Adam D. Clayton 3 “The best time to plant a tree was 25 years ago. The second best time to plant a tree is today.” – Eliud Kipchoge 4 Acknowledgements I would firstly like to thank my supervisor Richard Bourne for the opportunity to work on such an exciting and multidisciplinary project. Although initially overwhelmed by the coding and chemical engineering aspects of the project, Rich has a unique way of making you realise that any goal can be achieved with enough determination – a lesson I will not quickly forget. Also, despite becoming increasingly busy whilst climbing the academic ladder, Rich always found time to help with my own early career development by presenting me with new and exciting opportunities. I would also like to thank my co-supervisors John Blacker and Nik Kapur, whose combined industrial knowledge proved to be invaluable throughout the project. I would like to thank all of the great people I have had the pleasure of collaborating with throughout this project. The team at AstraZeneca (Graeme, Brian, Niall, Anne, Ali, Martin, Caroline, David) who made me feel welcome and taught me so much throughout my three month placement in Macclesfield. The co-authors of published work, with special mentions for Artur Schweidtmann, Jamie Manson and Alexei Lapkin whose coding experience was crucial to the success of the work, and Thomas Chamberlain whose meticulous eye for detail was particularly useful when preparing manuscripts. All present and past members of the iPRD, especially Nicholas Holmes and Alistair Baker who always made time to help train me at the start of the project. Everyone else who made the University of Leeds a great place to work over the last few years: Connor, Calum, Ollie, Holly, Ricardo, Ilias, Chris, Luke, Brendan, Mike, Mary, Lisa, Will, Becky, Tom, Rosie, Sam, Christiane, Nisha. Thank you to all of my family, in particular my parents David and Linda Clayton. Their continual (and sometimes relentless!) encouragement for me to pursue higher education from a young age still remains one of the biggest contributors to my motivation. Finally and foremost I would like to thank my loving wife Laura Clayton. The support you provide on a daily basis accumulates to the biggest reason I am able to undertake projects like these. We are a great team and none of this would be possible without you. 5 Abstract Continuous flow chemistry is currently a vibrant area of research, offering many advantages over traditional batch chemistry. These include: enhanced heat and mass transfer, access to a wider range of reaction conditions, safer use of hazardous reagents, telescoping of multi-step reactions and readily accessible photochemistry. As such, there has been an increase in the adoption of continuous flow processes towards the synthesis of active pharmaceutical ingredients (APIs) in recent years. Advances in the automation of laboratory equipment has transformed the way in which routine experimentation is performed, with the digitisation of research and development (R&D) greatly reducing waste in terms of human and material resources. Self-optimising systems combine algorithms, automated control and process analytics for the feedback optimisation of continuous flow reactions. This provides efficient exploration of multi-dimensional experimental space, and accelerates the identification of optimum conditions. Therefore, this technology directly aligns with the drive towards more sustainable process development in the pharmaceutical industry. Yet the uptake of these systems by industrial R&D departments remains relatively low, suggesting that the capabilities of the current technology are still limited. The work in this thesis aims to improve existing self-optimisation technologies, to further bridge the gap between academic and industrial research. This includes introducing multi-objective optimisation algorithms and applying them towards the synthesis of APIs, developing a new multiphasic CSTR cascade reactor with photochemical capabilities and including downstream work-up operations in the optimisation of multi-step processes. 6 Table of Contents Acknowledgements ......................................................................................................... 5 Abstract ............................................................................................................................... 6 List of Figures ................................................................................................................. 10 List of Schemes ............................................................................................................... 20 List of Tables ................................................................................................................... 23 List of Abbreviations .................................................................................................... 28 Chapter 1 Introduction ................................................................................................ 32 1.1 Ideal and Non-Ideal Reactor Types ................................................................... 32 1.2 Advantages of Flow Chemistry ............................................................................ 36 1.2.1 Diffusion, Mixing and Mass Transfer .................................................... 36 1.2.2 Enhanced Heat Transfer ............................................................................ 38 1.2.3 Greater Control of Reaction Conditions .............................................. 39 1.2.4 High T/p Reactors and Safer Use of Hazardous Reagents............ 40 1.3 Automation of Continuous Flow Systems ....................................................... 41 1.3.1 Analysis and Screening .............................................................................. 41 1.3.2 Process Control ............................................................................................. 43 1.3.3 Optimisation ................................................................................................... 44 1.3.3.1 One-Variable-at-a-Time ................................................................... 44 1.3.3.2 Design of Experiments ..................................................................... 45 1.3.3.3 Self-Optimisation ................................................................................ 49 1.4
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