Industry 4.0: a vision for personalized medicine supply chains?
Cell Gene Therapy Insights 2016; 2(2), 263-270.
10.18609/cgti.2016.027
Industry 4.0 foresees a digital transformation of manufacturing resulting in smart factories and supply chains. At the heart of the concept lies the vision of interconnected materials, goods and machines, where goods find their way through the factory and the supply chain to the customer in a self-organized manner. Industry 4.0 is gaining traction in high value manufacturing sectors. This expert insight article explores what this technology-driven vision has to offer the biopharmaceutical industry, and in particular cell and gene therapies.
What is Industry 4.0?
Industry 4.0 envisages factories and supply chains where goods and machines are all connected to the internet, communicating with each other, exchanging, collecting and analyzing data, and co-ordinating processes in a distributed fashion. This data-driven integrated system will enable improved responsiveness in manufacturing, leading to more flexible factories of the future.
It is derived from several strong technological trends: First, computer chips, sensors and transmitters are increasingly miniaturized and become ever less expensive, which allows embedding them into more and more machines and also goods. Second, wireless communication becomes ubiquitous, which allows connecting almost everything to the internet, blurring the boundary between the digital and the physical world, allowing machines and products to communicate directly and autonomously. Together, these technologies allow for the creation of self-organizing systems that collect and exchange data on an unprecedented scale, and make decisions autonomously, intelligently and in a decentralized fashion. Add to this mix other technological advances such as cloud computing which offers scalability even to small enterprises, big data analytics which enables the handling and interpretation of massive amounts of data in real time, and artificial intelligence which allows machines to learn and adjust, and you get a powerful mix that is able to transform industry processes and take them to a new level.
Industry 4.0 started as a German initiative [1], and its name was chosen because its promoters see it as the fourth industrial revolution, after the introduction of the steam engine, mass production, and electronics and IT (robots and programmable logic controllers). But the topic is gaining momentum across the world, and similar concepts are known as “Smart Factory”, “Advanced Manufacturing”, or, not limited to industrial processes, “Cyber-Physical Systems” [2] and the “Internet of Things” [3].
What Industry 4.0 promises
The typical and most prominent scenario of Industry 4.0 is the self-organizing factory, where half-finished goods find their way through the shop floor and negotiate their processing with machines autonomously. This scenario resonates very well with the manufacturing industry, because it promises cheap and efficient mass customization. Yet, the vision of Industry 4.0 goes far beyond this example, and hopes include:
Real-time control
Aggregating all the collected information centrally, it will be possible to generate a digital real-time image of the entire physical production process in the control centre. Production becomes fully transparent and thus offers more opportunities for monitoring, supervision, control and optimization, even across locations.
Integrated maintenance
Smart production lines will constantly monitor themselves, and can alert the appropriate personnel quickly if any problems are detected or anticipated, or even resolve many problems themselves. Machines may be able to predict optimal service intervals and order spare parts autonomously. Technicians will be able to monitor and interact with the machines remotely. Together, this promises to reduce machine downtimes and the cost for maintenance.
Better adaptability
A self-organizing production system that can make intelligent decisions in a decentralized manner is much more flexible and responsive than centrally controlled production systems. This promises much greater adaptability to changing demand or unforeseen events such as machine breakdowns or contamination.
Enhanced collaboration across the supply chain
With goods carrying information across the supply chain, and a more integrated approach to communication and end-to-end information exchange, Industry 4.0 will allow a much better coordination of the entire supply chain.
Better track-and-trace capabilities
Industry 4.0 means that individual goods will obtain a unique identifier, and be able to keep track of all the information related to their individual production process. This will allow for more efficient and more effective quality control, and help quickly identify problems in the production process. This is also an important prerequisite for Quality by Design (QbD) processes.
Smarter products & new business models
Connecting goods to the internet will not only help in co-ordinating their production, but also allow for better customer services, new product features and new business models. This includes provision of “in-use” information on the product back to the manufacturer; this can be used to improve product and process design for future products.
Industry 4.0 in the Biopharmaceutical Industry
The predominant mode of operation for the manufacture of biopharmaceuticals, including cell and gene therapies, is batch rather than continuous processing [e.g., 4–7]. This makes the benefits of Industry 4.0 with its vision of a self-organizing factory less obvious for the biopharmaceutical industry. However, the biopharmaceutical industry is currently undergoing a shift away from the one-drug-fits-all paradigm towards personalization, with therapies targeted to particular groups of patients (stratified) or individuals (personalized) such as the case of patient-specific autologous cell and gene therapies. This will require a corresponding shift in manufacturing to agile small-scale individualized production that can make-to-order cost-effectively. The resulting challenges will be similar to the mass customization challenges that made Industry 4.0 so popular in other manufacturing industries (e.g. automotive), heightened by the regulatory constraints paramount in the biopharmaceutical industry and the complex biological and living nature of the materials and products.
But when looking at all the associated benefits of Industry 4.0 mentioned in the previous section, it should become clear that this paradigm has a lot more to offer to the biopharmaceutical industry.
Quality trumps cost in the biopharmaceutical sector. Embracing Industry 4.0 will facilitate the biotech sector’s move towards QbD, including a more flexible process based on having enhanced product and process understanding that can be used to adapt the process to manage critical sources of variability [8,9]. This is because Industry 4.0 will connect Process Analytical Technologies (PAT) comprised of sensors with multivariate data analytics and control algorithms as well as electronic data records and enterprise systems to enable efficient knowledge sharing across components in the supply chain.
Such a knowledge-driven QbD approach will provide the ability to control variability in factors such as raw materials and donor source material, which are particular concerns for autologous cell therapies. As PAT and sensor technologies emerge, it will be possible to develop feedforward control algorithms so as to adjust the process parameters throughout the manufacturing process to cope with feed variability. For example, for autologous cell therapies if the starting cell concentration is lower than expected in the donor source material, Industry 4.0 can potentially make an informed decision on the increase in culture time required (within validated limits) to produce the required final number of cells for treatment. Feedback control, for example, using cell characterization assays and associated online analytics to control cell culture operation will also be desirable in future so as to consistently achieve desired product quality attributes. This will not only have benefits one might expect such as reduced wastage and improved yields, but more critically for patient-specific cell and gene therapies this could be the difference between treating a life-threatening disease and having a failed patient treatment; it may not be possible to repeat manufacturing in the event of a batch failure, especially if new patient source material is required, due to the already immune-compromised health of the patients.
Furthermore, the trend towards more patient-specific therapies will result in an explosion in quality data, batch manufacturing record reviews and release testing required. For example, quality control/quality assurance functions will need to be more automated with continuous real-time release methods to handle larger numbers of patients per year so as to avoid becoming a bottleneck. As can be seen, the quality infrastructure will lie at the heart of the digital transformation of cell and gene therapy manufacture.
Enhanced track-and-trace capabilities are critical for cell and gene therapies and in particular for patient-specific therapies so as to provide assurance that the patient’s treatment is from their own starting material. In such a setting, the supply chain changes from a linear to a circular one with the patient or donor at the centre.
Furthermore, autologous immunotherapies such as CAR T-cells require careful orchestration of three main manufacturing pathways (plasmid DNA, viral vectors, cells) with the additional challenge of different centralized versus local manufacturing setups. Whether cell therapies (allogeneic or autologous) are shipped fresh or cryopreserved, both require temperature-controlled conditions with real-time temperature reports. Blood banks already address some of these issues with barcoding of supplies and managing the logistics of handling blood products requiring controlled temperature storage and distribution. However, it is clear that innovative solutions from Industry 4.0 will provide real-time visibility and control across complex cell and gene therapy supply chains from material sourcing through to manufacturing and temperature-controlled transport to patients. This is particularly critical given that here an expensive asset ($50k+) needs to be tracked needle-to-needle so as to guarantee chain of custody and ensure timely delivery to the correct patients. This needs to be achieved whilst managing temperature and time risk, co-ordinating with manufacturing sites for capacity sourcing and planning, and clinical sites manufacturing, as well as factors such as customs challenges when shipping [10]. It is encouraging to note that there are already important developments in track-and-trace for cell therapies and these are more advanced than elsewhere in the biopharmaceutical sector.
The enhanced track-and-trace capabilities of Industry 4.0 will also make it easier to comply with different geographical regulatory jurisdictions that may have differences in formulation, packaging or quality control requirements. Further drivers for Industry 4.0 adoption are based on new EU regulation that is likely to require a unique serial number for most prescription drugs from 2018 [11], as well as WHO estimates that about 10% of drugs in Europe may be counterfeit drugs [12]. If every item has its own specific identification label, it is straightforward to envision a system where every patient could easily check the origin of the drug they have been given by simply holding its packaging in front of their computer’s webcam.
Industry 4.0 will also help in the biopharmaceutical industry’s transition towards increased industrialization. In some cases this will include moving from batch to continuous manufacturing. Continuous biomanufacturing is actively being investigated in the therapeutic protein manufacturing space with a potential end-to-end continuous manufacturing vision [e.g., 13–15]. For viral vector manufacture for cell and gene therapies, continuous biomanufacture is being explored on the upstream front, with perfusion culture in fixed bed bioreactors [16] or stirred tank bioreactors, as well as the downstream front with continuous chromatography [17]. For cell therapy manufacture one can also envisage the use of perfusion culture to enhance productivities within a smaller footprint linked to continuous volume reduction, washing [18] and purification, where appropriate. For continuous biomanufacture, the sophisticated monitoring and control capabilities expected from Industry 4.0 will be even more important for successful implementation and track-and-trace.
Industry 4.0 will support also the formation of company networks, or virtual organizations, by enabling more efficient communication across company walls. Given the general trends towards specialisation and outsourcing in the industry, this could become an effective co-ordination mechanism. Furthermore, current (bio)pharmaceutical supply chains are characterized by low velocities and large amounts of stocks present at all levels in the supply chain [19]; the adoption of Industry 4.0 should lead to more effective material management and improved responsiveness.
Last but not least, Industry 4.0 will enable both forward flow of information through the supply chain as well as backward flow of real-time patient data with direct communication between manufacturer, clinician, payer and patient, in various ways. Monitoring devices worn by the patient would allow automatically adjusting the treatment (such as time and dosage) to a patient’s individual lifestyle, or notify a doctor if it detects that intervention would be beneficial. It would also allow a much better monitoring of efficacy and detecting side effects more quickly. A pharmaceutical pill box or biopharmaceutical self-administered injection (e.g., subcutaneous or intramuscular) linked to the internet could send the patient automatic reminders via email or call if they forget to take their medicine, leading to better patient compliance. It could also automatically re-order medicine as needed, which would be immediately known to the manufacturer. Such approaches not only promise improved delivery of the drug, but also lead to higher customer loyalty and retention. With many more possibilities enabled by a connected patient, and radically new business models, this clearly has the potential to change the healthcare industry substantially.
Challenges
As exciting as the vision of Industry 4.0 may be, there are still numerous challenges that need to be addressed. With the increased interoperability required by the internet of things, systems need to be able to communicate, not only on the technical level, but also on the application level. This means global standards and data sharing protocols are absolutely crucial for its success.
Obvious concerns when connecting everything to the internet are safety and data security. Related to data security is also the question of data ownership. Data security is important for example, for protection of intellectual property and company data, but is of particular concern to the (bio)pharmaceutical industry because health data is very sensitive. And an increased connectedness also comes with an increased risk of cyber attacks, which in the pharmaceutical industry could for example, lead to tampering with the production process and result in ineffective or even harmful manipulated drugs delivered to the patient. Even without a maleficent attacker, one has to think about liability and accountability in a self-organized production network consisting of multiple parties if something goes wrong. And even for a single smart machine, one can ask the question whether it is the drug manufacturer’s or the machine manufacturer’s responsibility if the “intelligent” machine makes incorrect decisions.
Finally, self-organizing systems require new tools and paradigms for effective control. Since these systems are very complex and rely on many decentralized decision making entities, the use of exact and provably optimal techniques will not be possible. Instead, those systems will be inherently of heuristic nature [e.g. 20] and the regulatory framework which currently tightly controls every step in the biopharmaceutical industry would have to become much more open to allow for a new type of flexible and self-organized production processes.
Translational Insight
It may be too much to say that Industry 4.0 means another revolution also for the biopharmaceutical industry. But the technology certainly bears great potential, in particular in terms of fusion of automation and robotics systems, track-and-trace capabilities, real-time quality testing and control, greater collaboration between manufacturers and suppliers and end-to-end communication. This will enable the supply chain to be redesigned and customized around the patient and to bring manufacturing closer to patient when desired. Industry 4.0 will play a crucial role in the shift to personalized medicine and enable a higher level of mass customization than is possible today.
Implementation will require disruptive approaches to transform the supply chain, vendor-manufacturer relationships and data sharing protocols to increase manufacturing flexibility whilst allowing for cost-effective production of small lot sizes. In order to take full advantage of Industry 4.0, the cell and gene therapy sector will need to move more strongly towards digitally integrated and automated or robotically-controlled equipment [e.g. 7, 21–22] rather than the manual, labor-intensive kit in use today. With the supply chain including healthcare providers and patient data, it will also need to consider challenges around data ownership and the implications from patient feedback data. The creation of automated manufacturing and testing solutions, standardization of procedures across the supply chain as well as real-time traceability has the potential to be game-changing and a critical lever for survival and success for the cell and gene therapy industry. Industry 4.0 adoption will also be a key factor in ensuring increased patient access to these novel biological therapies in an affordable manner.
Acknowledgements
Funding from the UK Engineering & Physical Sciences Research Council (EPSRC) through the EPSRC Centre for Innovative Manufacturing in Emergent Macromolecular Therapies (EP/I033270/1) and the EPSRC Frontier Engineering Programme (EP/K038648/1) is gratefully acknowledged.
Financial & competing interests disclosure
The authors have no relevant financial involvement with an organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock options or ownership, expert testimony, grants or patents received or pending, or royalties.
No writing assistance was utilized in the production of this manuscript.
This work is licensed under a Creative Commons Attribution- NonCommercial – NoDerivatives 4.0 International License.
References
1. Recommendations for implementing the strategic initiative INDUSTRIE 4.0 (2013)
2. Cyber physical systems: Design challenges. Lee, E.A., Proceedings of 11th IEEE Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing, Orlando, FL, MAY 2008.
3. Atzori L, Iera A, Morabito G. The Internet of Things: A survey. Computer Networks 2010; 54(15), 2787–2805. CrossRef
4. Simaria AS, Hassan S, Varadaraju H et al. Allogeneic cell therapy bioprocess economics and optimization: single-use cell expansion technologies. Biotech. Bioeng. 2014; 111(1), 69–83. CrossRef
5. Hassan S, Simaria AS, Varadaraju H, Gupta S, Warren K, Farid SS. Allogeneic Cell Therapy Bioprocess Economics and Optimization: Downstream Processing Decisions. Regen. Med. 2015; 10 (5), 591–609. CrossRef
6. Hassan S, Huang H, Warren K et al. Process change evaluation framework for allogeneic cell therapies: impact on drug development and commercialization. Regen. Med. 2016; 11(3), 287–305. CrossRef
7. Trainor N, Pietak A, Smith T. Rethinking clinical delivery of adult stem cell therapies. Nature Biotech. 2014; 32, 729–735. CrossRef
8. Looby M, Ibarra N, Pierce J et al. Application of Quality by Design (QbD) Principles to the Development and Technology Transfer of a Major Process Improvement for the Manufacture of a Recombinant Protein. Biotech. Prog. 2011; 27 (6), 1718–29. CrossRef
9. Chhatre S, Farid SS, Coffman J, Bird P, Newcombe AN, Titchener-Hooker NJ. How implementation of Quality by Design and advances in Biochemical Engineering are enabling efficient bioprocess development and manufacture. J. Chem. Technol. Biotech. 2011; 86, 1125–29. CrossRef
10. Farid SS & Davidson A. BioIndustry Association Guest Blog: Improving the biopharma supply chain. November 2014. Website
11. See, for example, EFPIA- European Federation of Pharmaceutical Industries and Associations: Coding and Serialisation. Website
12. See, for example, Bulletin of the World Health Organization: Growing threat from counterfeit medicines. Website
13. Godawat R, Konstantinov K, Rohani M, Warikoo V. End-to-end integrated fully continuous production of recombinant monoclonal antibodies, J. Biotechnol. 2015, 213, 13–19. CrossRef
14. Klutz S, Magnus J, Lobedann M et al. Developing the biofacility of the future based on continuous processing and single-use technology. J. Biotechnol. 2015 213, 120–30. CrossRef
15. Farid SS, Pollock J, Ho SV. Evaluating the economic and operational feasibility of continuous processes for monoclonal antibodies. In: Subramanian G. Continuous Processing in Pharmaceutical Manufacturing. First Edition. 2014; Wiley-VCH Verlag GmbH & Co. KGaA, 17. CrossRef
16. Moncaubeig F. Simpler and More Efficient Viral Vaccine Manufacturing. BioProcess Intl 11(9)s, 1–3. Website
17. Silva RJS, Mota JPB, Peixoto C, Alves PM, Carrondo MJT. Improving the downstream processing of vaccine and gene therapy vectors with continuous chromatography. Pharmaceutical Bioprocessing 2015; 3 (8), 489–505. CrossRef
18. Cunha B, Aguiar T, Silva MM et al. Exploring continuous and integrated strategies for the up- and downstream processing of human mesenchymal stem cells, J. Biotechnol. 2015; 213, 97–108. CrossRef
19. Shah N. Pharmaceutical supply chains: key issues and strategies for optimisation, International Conference on Foundations of Computer-Aided Process Operations, Publisher: Pergamon-Elsevier Science Ltd. 2004; 929–41. CrossRef
20. Pickardt C, Hildebrandt T, Branke J, Heger J, Scholz-Reiter B. Evolutionary generation of dispatching rule sets for complex dynamic scheduling problems. Intl J. Production Econ. 2013; 145(1), 67–77. CrossRef
21. Jenkins MJ, Bilsland J, Allsopp TA, Ho SV, Farid SS. Patient-specific hiPSC bioprocessing for drug screening: Bioprocess economics and optimisation. Biochem. Eng. J. 2016; 108, 84–97. CrossRef
22. Harris IR, Meacle F, Powers D. Automation in Cell Therapy Manufacturing. BioProcess Intl 2016; 14(4), S18–21. Website
Affiliations
*Corresponding Authors
Juergen Branke*
Warwick Business School, University of Warwick, CV4 7AL Coventry, UK
Juergen.Branke@wbs.ac.uk
Suzanne S Farid*
The Advanced Centre for Biochemical Engineering, Dept. of Biochemical Engineering, University College London, Gordon Street, London WC1H 0AH, UK
s.farid@ucl.ac.uk
Nilay Shah
Department of Chemical Engineering, Imperial College London, London SW7 2AZ, UK
n.shah@imperial.ac.uk