There are considerable challenges around digitalisation in science, engineering and manufacturing in part due to the inherent complexity in the data generated and the challenges in creating useful data sets with the scale required to allow big data approaches to identify patterns, trends and useful knowledge. Whilst other sectors are now realising the power of predictive data analytics; social media platforms, online retailers and advertisers, for example; much of the pharmaceutical manufacturing R&D community struggle with modest, poorly interconnected datasets, which ultimately tend to have short useful lifespans. A result of poor, under-utilised datasets, is that it is largely impossible to avoid "starting at the beginning" for every new drug that needs to be manufactured, which is very costly with new medicines currently doubling in cost every nine years; $1 billion US Dollars currently "buys" only half a new drug so addressing this issue is key for sustainability of the industry and future medicines supply. This project, ARTICULAR, will seek to develop novel machine learning approaches, a branch of artificial intelligence research, to learn from past and present manufacturing data and create new knowledge that aids in crucial manufacturing decisions. Machine learning approaches have been successfully applied to inform aspects of drug discovery, upstream of pharmaceutical manufacturing, where large genomic and molecule screening datasets provide rich information sources for analysis and training artificial intelligences (AI). They have also shown promise in classifying and predicting outcomes from individual unit operations used in medicines manufacturing, such as crystallisation. For the first time, there is an opportunity to use AI approaches to learn from the data and models from across multiple previous development and manufacturing efforts and then address the most commonly encountered problems when manufacturing new pharmaceutical products, which are knowing: (1) the processes and operations to employ; (2) the sensors and measurements to deploy to optimally deliver the product; and (3) the potential process upsets and their future impact on the quality of the medicine manufactured. All of these data and the AI "learning" will be made available via bespoke, personalisable AR and VR interfaces incorporating gesture and voice inputs alongside more traditional approaches such as dashboards. These immersive interfaces will facilitate pharmaceutical manufacturing process design, and visualisation of the complex data being captured and analysed in real-time. Detailed, interactive 3D visualisations of drug forms, products, equipment and manufacturing processes and their associated data will be created which provide intuitive access across the length scales of transformations involved from the drug molecule to final drug product. This will be unique tool, allowing the user to see their work and engage with their data in the context of upstream and downstream processes and performance data. Virtual and Augmented Reality technologies will be used in the lab/plant environment to visualise live data streams for process equipment as the next step in digitalisation. These advanced visualisation tools will add data rich, interactive visualisation to aid researchers in their work, allowing them to focus on the meaning of results and freeing them from menial manual data curation steps.

The pharmaceutical industry is undergoing a period of unprecedented change in terms of product development, with increased digitization, greater emphasis on continuous manufacture and the rapid advent of novel therapeutic paradigms, such as personalized medicines, becoming more and more business critical. This change is amplified by Quality by Design considerations and the now routine use of the Target Product Profile approach to the design of patient-centred dosage forms. The recent advances in the range of available therapeutic strategies, alongside the breadth of diseases that can now be successfully treated, has resulted in the need for both new dosage forms and manufacturing approaches. Crucially, there has been a shift from high volume, low cost manufacture towards a more specialized, higher value product development. Consequently, ever more sophisticated approaches, not merely to producing medicinal products, but also to controlling their quality at every stage of the manufacturing process, have become paramount. These would be greatly facilitated by the emerging technologies, based on artificial intelligence and machine learning techniques, for enhancing online process analysis as well as real-time responsive process control. These technologies are particularly important for products where the financial and practical margins for manufacturing error are low, as is the case for an increasing proportion of new therapies. In this proposal, we focus on a new way of screening, manufacturing and quality controlling drugs in the form of nanocrystals, that is, drugs prepared as nanosized crystalline particles stabilized by surface-active agents. In particular, we will combine continuous-flow processing, online advanced process analytical technology, real-time process control and quality assurance, design of experiments, advanced data analysis and artificial intelligence to deliver fully automated, self-optimizing platforms for screening and manufacturing drugs as nanocrystals via antisolvent precipitation. These dosage forms have attracted substantial interest as a means of delivering poorly water-soluble (and thus poorly bioavailable) drugs, a persistent and increasing problem for the pharmaceutical industry. While nanocrystals offer a suitable test system for our approach, our methodology and the manufacturing platform we intend to deliver can be applied to other drug delivery systems. We focus on nanocrystals because they are of considerable therapeutic and commercial significance both nationally and internationally. We intend to use continuous-flow small-scale (i.e. millifluidic) systems. These offer excellent process controllability, can generate crystals of nearly uniform size, and as the process is continuous, the product characteristics are more stable than in batch systems. Millifluidic systems are flexible (one platform can produce a larger variety of products) and agile - reacting rapidly to changes in market demands; they reduce the manufacturing time, speed up the supply chain and, being smaller, can be portable. These systems also expedite screening, curtailing the quantities of material required, benefits that design of experiments will amplify. This data-driven technique allows identifying the most informative experiments, maximizing learning while minimizing time and costs, advantages not fully exploited by the pharmaceutical industry. These technologies, coupled with online advanced process analytical methods, real-time process control, cutting-edge data analysis and machine learning methods, have the potential to disrupt the status quo, accelerate process development and deliver transformative platforms for the cost-effective and sustainable manufacturing of active pharmaceutical ingredients in solid dosage form, reducing the timeline from drug discovery to patient, and contributing to placing the UK at the forefront of innovation in the pharmaceutical sector.

The EPSRC CDT in Integrated Catalysis (iCAT) will train students in process-engineering, chemical catalysis, and biological catalysis, connecting these disciplines in a way that will transform the way molecules are made. Traditionally, PhD students are trained in either chemocatalysis (using chemical catalysts such as metal salts) or biocatalysis (using enzymes), but very rarely both, a situation that is no longer tenable given the demands of industry to rapidly produce new products based on chemical synthesis. Graduate engineers and scientists entering the chemical industry now need to have the skills and agility to work across a far broader base of catalysis - iCAT will meet this challenge by training the next generation of interdisciplinary scientists and engineers who are comfortable working in both bio and chemo catalysis regimes, and can exploit their synergies for the discovery and production of molecules essential to society. iCAT features world-leading chemistry and engineering groups advancing the state-of-the-art in bio and chemo catalysis, with an outstanding track record in PhD training. The CDT will be managed by a strong and experienced team with guidance from a distinguished membership of an International Advisory Group. The rich portfolio of interdisciplinary CDT projects will feature blue-sky research blended in with more problem-solving studies across scientific themes such as supramolecular-assisted catalysis using molecular machines, directed evolution and biosynthetic engineering for synthesis, and process integration of chemo and bio-catalysis for sustainable synthesis. The iCAT training structure has been co-developed with industry end-users to create a state-of-the-art training centre at the University of Manchester, equipping PhD students with the skills and industrial experience needed to develop new catalytic processes that meet the stringent standards of a future sustainable chemicals industry in the UK. This chemical industry is world-class and a crucial industrial sector for the UK, providing significant numbers of jobs and creating wealth (currently contributing £15 billion of added value each year to our economy). The industry relies first and foremost on skilled researchers with the ability to design and build, using catalysis, molecules with well-defined properties to produce the drugs, agrochemicals, polymers, speciality chemicals of the future. iCAT will deliver this new breed of scientist / engineer that the UK requires, involving industry in the design and provision of training, and dovetailing with other EPSRC-, University-, and Industry-led initiatives in the research landscape.

Efficient synthesis remains a bottleneck in the drug discovery process. Access to novel biologically active molecules to treat diseases continues to be a major bottleneck in the pharmaceutical industry, costing many lives and many £millions per year in healthcare investment and loss in productivity. In 2016, the Pharmaceutical Industry's estimated annual global spend on research and development (R&D) was over $157 billion. At a national level, the pharmaceutical sector accounted for almost half of the UK's 2016 £16.5bn R&D expenditure, with £700 million invested in pre-clinical small molecule synthesis, and 995 pharmaceutical related enterprises (big pharma, SMEs, biotech & CROs) employing around 23,000 personnel in UK R&D. The impact of this sector and its output on the nation's productivity is indisputable and worthy of investment in new approaches and technologies to fuel further innovation and development. With an increasing focus on precision medicine and genetic understanding of disease there will be to a dramatic increase in the number of potent and highly selective molecular targets; identifying genetically informed targets could double success rates in clinical development (Nat. Gen. 2015, 47, 856). However, despite tremendous advances in chemical research, we still cannot prepare all the molecules of potential interest for drug development due to cost constraints and tight commercial timelines. By way of example, Merck quote that 55% of the time, a benchmarked catalytic reaction fails to deliver the desired product; this statistic will be representative across pharma and will apply to many comparable processes. If more than half of the cornerstone reactions we attempt fail, then we face considerable challenges that will demand a radical and innovative a step change in synthesis. Such a paradigm shift in synthesis logic will need to be driven by a new generation of highly skilled academic and industry researchers who can combine innovative chemical synthesis and technological advances with fluency in the current revolution in data-driven science, machine learning methods and artificial intelligence. Synthetic chemists with such a set of skills do not exist anywhere in the world, yet the worldwide demand for individuals with the ability to work across these disciplines is increasing rapidly, and will be uniquely addressed by this proposed CDT. By training the next generation of researchers to tackle problems in synthetic chemistry using digital molecular technologies, we will create a unique, highly skilled research workforce that will address these challenges and place UK academic and industrial sectors at the frontier of molecule building science. The aspiration of next-generation chemical synthesis should be to prepare any molecule of interest without being limited by the synthetic methodologies and preparation technologies we have relied on to date. Synthetic chemists with the necessary set of such skills and exposure to the new technologies, required to innovate beyond the current limitations and deliver the paradigm shift needed to meet future biomedical challenges, are lacking in both academia and industry. To meet these challenges, the University of Cambridge proposes to establish a Centre of Doctoral Training in Automated Chemical Synthesis Enabled by Digital Molecular Technologies to recruit, train and develop the next generation of researchers to innovate and lead chemical synthesis of the future.

A drug is a molecule that acts upon biological processes in the body. In contrast, a medicine is a complex product that comprises the drug and other ingredients packaged into a final dosage form that can be administered to a patient to ensure there is a beneficial therapeutic effect with minimum side-effects. To achieve therapeutic effect it is essential to ensure that the drug is delivered to the appropriate site in the body, at the right time, and in the correct amount. This is challenging: some drug molecules are poorly soluble in biological milieu, while others are either not stable or have toxic side-effects and require careful processing into medicines to ensure they remain biologically active and safe. The new drug molecules arising from drug discovery and biotechnology have particularly challenging properties. Pharmaceutical technologies are central to developing medicines from these molecules, to ensure patients are provided with safe and efficacious therapy. The design and development of new medicines is an inherently complex and cross-disciplinary process, and requires both innovative research and highly skilled, imaginative, researchers. To sustain and reinforce the UK's future global competitiveness, a new generation of highly-trained graduates educated at doctoral level is required to deliver transformative new therapeutics. Our CDT will train an empowered network of at least 60 PhD students through a consortium of multiple industry partners led by the University of Nottingham and University College London. The involvement of partners from start-ups to major international pharmaceutical companies will ensure that our students receive the cross-disciplinary scientific knowledge needed to develop future medicines, and build the leadership, resilience and entrepreneurial skills crucial to allow them to function effectively as future leaders and agents of change. Through partnering with industry we will ensure that the research work undertaken in the CDT is of direct relevance to contemporary and future challenges in medicines development. This will allow the CDT research to make significant contributions to the development of new therapies, leading ultimately to transformative medicines to treat patients. Beyond the research undertaken in the CDT, our graduates will build careers across the pharmaceutical and healthcare sector, and will in the future impact society through developing new medicines to improve the health and well-being of individuals across the world. We will train our students in four key science themes: (i) predictive pharmaceutical sciences; (ii) advanced product design; (iii) pharmaceutical process engineering; and, (iv) complex product characterisation. This will ensure our graduates are educated to approach challenges in preparing medicines from a range of therapeutic molecules, including emerging cutting-edge actives (e.g. CRISPR, or locked RNAs). These are currently at a critical stage of development, where research by scientists trained to doctoral level in the latest predictive and product design and development technologies is crucial to realise their clinical potential. Our students will obtain comprehensive training in all aspects of medicines design and development, including pharmaceutical engineering, which will ensure that they consider early the 'end game' of their research and understand how their work in the laboratory can be translated into products which can be manufactured and enter the clinic to treat patients.