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Intelligent Drug Supply Chain Creating Value from AI About the Deloitte Centre for Health Solutions Intelligent drug supply chain Creating value from AI About the Deloitte Centre for Health Solutions The Deloitte Centre for Health Solutions (CfHS) is the research arm of Deloitte’s Life Sciences and Health Care practices. We combine creative thinking, robust research and our industry experience to develop evidence-based perspectives on some of the biggest and most challenging issues to help our clients transform themselves and, importantly, benefit the patient. At a pivotal and challenging time for the industry, we use our research to encourage collaboration across all stakeholders, from pharmaceuticals and medical innovation, health care management and reform, to the patient and health care consumer. Connect To learn more about the CfHS and our research, please visit www.deloitte.co.uk/centreforhealthsolutions Subscribe To receive upcoming thought leadership publications, events and blogs from the UK Centre, please visit https://www.deloitte.co.uk/aem/centre-for-health-solutions.cfm To subscribe to our blog, please visit https://blogs.deloitte.co.uk/health/ Life sciences companies continue to respond to a changing global landscape and strive to pursue innovative solutions to address today’s challenges. Deloitte understands the complexity of these challenges and works with clients worldwide to drive progress and bring discoveries to life. Contents The rationale for transforming the biopharma supply chain 2 How AI can augment supply chain transformation 6 AI’s role in helping supply chains respond, recover and thrive after COVID-19 16 A roadmap for implementing an intelligent supply chain 21 Endnotes 32 Intelligent drug supply chain The rationale for transforming the biopharma supply chain The Intelligent biopharma series explores the ways artifi cial intelligence (AI) can impact the biopharma value chain. The fi rst two reports, Intelligent drug discovery1 and Intelligent clinical trials,2 highlight the potential of AI to accelerate the development of new drugs. This report explores the poten- tial for AI technologies to improve the value of the biopharma supply chain and manage risks more eff ectively. Evidence shows that the need for dig- ital transformation of the supply chain has never been more pressing. HE BIOPHARMA SUPPLY chain involves a Protecting biopharma supply chains is a priority complex set of steps that are required to pro- not only for companies but also for all governments, Tduce a drug, from sourcing and supply of given the importance of ensuring access to the materials, through manufacturing and distribution, lifesaving and life-enhancing products that are to delivery to the consumer. This forms a golden vital for the health and well-being of their popu- thread between the discovery of new therapies and lations. The COVID-19 pandemic has highlighted patients receiving them (fi gure 1).3 the importance of biopharma supply chains in meeting the demand for leading-edge products.4 FIGURE 1 The different steps in the biopharma supply chain Post-market Research & Clinical Manufacturing Launch & surveillance & discovery development & supply chain commercial patient support SOURCING MANUFACTURING DISTRIBUTION DELIVERY PATIENTS APIs and other Processing, testing Wholesale distributors, Integrated delivery Providing effective materials and packaging labelling and networks of retail and safe treatments serialisation pharmacies, hospitals and clinics PEOPLE, SKILLS AND INFORMATION SYSTEMS REGULATORY RISK AND COMPLIANCE TRANSPORT AND LOGISTICS Source: Deloitte analysis. Deloitte Insights | deloitte.com/insights 2 Creating value from AI Biopharma supply chains create inherent resilience play in its digital transformation (Part 2). Given risks for corporations and governments alike. the unprecedented challenges to the health Supply chains must also meet the expectations of a care ecosystem resulting from the COVID-19 complex range of stakeholders, comprising multiple pandemic, the report also considers the role payers, health care providers and patients with that AI can play in helping the supply chain to complex and varied needs, both within and respond, recover and thrive (Part 3). Finally, the across diff erent countries. Consequently, report provides a strategic roadmap for imple- intelligent and insightful monitoring and man- menting an AI-enabled supply chain (Part 4). agement of the supply chain is an imperative. The risk landscape for biopharma supply This report examines the rationale for transforming chains comprises internal, external the supply chain (Part 1) and the role that AI can and macro risk factors (fi gure 2). FIGURE 2 The complexity and risks affecting the globally distributed biopharma supply chain Macro risk External supply chain Internal risk Negative impact to Risks in upstream and Potential risks from entire industrial chain downstream supply internal operation due to changes in chain processes macro environment Geopolitical Environmental change protection policies Compliance Insufficient/excess Exchange capacity Trade rate Operational incidents barrier fluctuation change Production safety Quality Technical risks Inaccurate demand forecast bottlenecks Product development delay Trade secret High transportation cost leaks Unstable Long delivery cycle IT system Labour High Large-scale law defect Equipment malfunction rate strikes Cold chain logistics Competition Bankruptcy/ Infringement Epidemic Waste financial risks of IP rights COVID-19 management outbreak Cybersecurity Terrorism/large Extreme weather scale civil strife conditions Source: Deloitte analysis. Deloitte Insights | deloitte.com/insights 3 Intelligent drug supply chain Given the above complexity and risks, governments The complexity of have established an evolving and complex frame- biologics manufacturing work of local, regional and international regulatory and supply chains bodies. There are also global bodies, such as the World Health Organisation (WHO) and Interna- In comparison to ‘traditional’ small molecules, tional Council for Harmonisation of Technical biologics have more complex supply chains (fi gure Requirements for Pharmaceuticals for Human Use, 3). A 2019 survey of 151 experts to understand aimed at improving regulatory collaboration.5 more about manufacturing practices and trends identifi ed that the biggest challenges of biologics FIGURE 3 The different complexities affecting the three main biologics manufacturing processes RECOMBINANT PRODUCTS – VIRUS, BACTERIA, CULTURED CELLS Proteins (recombinant antibodies, cytotokines, enzymes, etc.) Antisense RNAs In vivo gene therapies Initial batch Harvest and Inactivation Formulation Batch quality Transport/ Vaccines (DNA, RNA and thawing purification of and assembly and filling for control, distribution to proteins for prevention and cell/ antigens or (vaccines) cryopreservation validation and hospital and and therapy) microorganism active packaging pharmacies growth molecules (cold chain) HUMAN BLOOD PRODUCTS – BLOOD DONORS Whole blood, blood derivatives and blood components Tissue Transport to Tissue processing Transport to collection processing • Testing hospital for facilities or • Centrifugation patient treatment storage unit • Component separation or to storage unit (cold chain) (cold chain) GENE AND CELL THERAPIES – PATIENTS OR DONORS Gene and cell therapies Autologous, including CAR-T therapies, and allogenic, including stem cell therapies Apheresis or Transport to Personalised Cell Batch quality Transport to other tissue manufacturing bioprocessing concentration, control and hospital (cold collection facilities or • Cells separation formulation validation chain) for storage unit • Gene editing and filling for therapy (cold chain) • Reprogramming cryopreservation application or • Cell expansion to storage unit BIOLOGIC PRODUCTION TAKES FROM SIX MONTHS TO THREE YEARS 70% OF THE TIME IS REQUIRED FOR QUALITY CONTROL COLD CHAIN TRANSPORT AND STEPS INVOLVING CELL CULTURING ARE KEY TO MAINTAINING YIELD AND QUALITY Source: Deloitte analysis. Deloitte Insights | deloitte.com/insights 4 Creating value from AI manufacturing are process robustness (59 per requires a more agile supply chain structure. This cent of respondents), process reproducibility (56 is particularly the case for cell therapies (known as per cent), product yield optimisation (46 per cent) ex vivo); for example, chimeric antigen receptor and product characterisation (42 per cent).6 T-cell (CAR-T) therapies. By the end of 2019, the FDA had approved two CAR-T therapies; however, Deloitte research demonstrates a continued there were some 600 clinical trials involving growth in biologics and estimates an equal split CAR-T therapies in the biopharma pipeline.10 with small molecules in worldwide sales by 2024.7 However, large-scale production of biologics is at present seen as one of the main challenges of the The need for a new supply biopharma industry, mostly due to the inherent chain model is driving the variability of biological systems and the instability digital transformation of most of finished products. Ascertaining the yields and quality of these types of drugs is crucial in ensuring industries, supply chains that they are reproduced effectively and maintained In the past few years, manufacturing companies until they reach patients, with regulatory bodies ap- across all industries have initiated digital trans- plying strict inspection and reporting requirements. formation of the different steps in the supply These need additional analytical methods that chain. Big tech giants such as Amazon, Apple measure specific
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