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Next-Gen Pharma Manufacturing: The Advent of Industry 4.0

Next-Gen Pharma Manufacturing: The Advent of Industry 4.0

digital

Saksham Charan, Padmakshi Agarwal

Oct 10, 20227 min read

Over the years the pharmaceutical industry has grown from small-scale manual processing with simple tools to large-scale production employing process control and automation. This trillion-dollar industry has been the slowest to adopt technological advancements such as the internet of things (IoT), artificial intelligence (AI), robotics, and advanced computing due to regulatory, technical, and technological challenges. However, with improving techno-commercial and regulatory conditions, the advent of Industry 4.0 that promises to bring to the forefront autonomous manufacturing systems with little to no human intervention is inexorable. Such advancements have the potential to transform pharmaceutical manufacturing and logistics to unprecedented efficiency and productivity.

Brief History of Pharma Manufacturing

The pharmaceutical industry had very humble origins stemming from herbal plant preparations using hand tools. The industrialization of these botanical, mineral, and animal-derived medicines happened only in the 19th century when hand-operated tools were transformed into industrial equipment able to crush, mill, blend, and press larger quantities of medicine. This period is often classified as Industry 1.0.

The second industrial revolution was enabled by electricity. Early electronic machines, assembly lines, and minimal automation was employed during this period, which allowed manufacturers to control only basic parameters in their processes.

For better quality monitoring, increased automation brought about by process analytical technology (PAT) and model-based processes called Quality by Design (QbD), led to the third industrial revolution at the onset of the 21st century. These advanced technologies provided real-time monitoring and process simulations within predefined parameters. Despite the value addition offered by these technologies, the pharmaceutical industry has been slow in adopting them. This is because a deeper understanding of processes and real-time analytics is required to maximize the potential of PAT and QbD and usher widespread implementation. Industry 4.0, the future of pharmaceutical manufacturing builds upon Industry 3.0 and its shortcomings.

What Industry 4.0 will look like?

AI, IoT, and robotics all interconnected with minimal intervention of humans can be viewed as the face of Industry 4.0. Such integration can be brought about by digitization of multiple complex pieces of the pharmaceutical value chain with the help of IoT and embedded cyber-security. It will also involve the journey from simple data collection to digital maturity in which raw data captured from a manufacturing process will be converted into actionable wisdom by artificial intelligence. It is this “wisdom” that fuels the autonomous systems to self-optimize and make decisions with minimal human involvement.

How it can be deployed?

Pharmaceutical manufacturing, for instance, could combine external data - including variables such as patient experience, market demand, supplier inventories, and public health emergencies - with internal data - such as energy and resource management, modeling and simulation results, and laboratory results. Such data integration and analysis can substantially streamline production capacity utilization and reduce time to market, thereby, leading to resource optimization and major cost savings.

Other areas of automation in manufacturing operations include the use of computer vision technology to replace human inspections of packaging, caps, and vials. Additionally, predictive equipment maintenance can be employed with the help of IoT and AI to reduce disturbances, risks, and production downtime. Furthermore, AI-enabled automation can be used to streamline analytical testing and ensure continuous quality assurance and data integrity across the production line.

AI-enabled technologies can lead to optimizations in not only product manufacturing but also product development. Deep learning models can be used for process simulation during developmental stages. Furthermore, such models can be employed for optimizing different stages of drug discovery from lead generation to the prediction of pharmacokinetics and pharmacodynamics of potential drug targets.

Challenges in Implementation

Industry 4.0 is the future of pharmaceutical manufacturing; however, certain regulatory, technical, and logistical challenges persist that need redressal. The lack of precedent in the industry, the costs associated with development, and the uncertainties surrounding regulatory approval have led many companies to adopt a “first to be second” approach.

Regulatory Challenges

The current regulatory framework which is based on prescriptive processes and parameters rather than performance-based regulation has prevented many pharmaceutical manufacturers from adopting new technologies. The US FDA has been working on the transition to performance-based regulation for almost a decade now and it was only in June 2021 that the draft guidelines for performance-based regulation such as those focusing on the continuous manufacturing of drug substances and products were published. A formalized framework in the near future based on these guidelines will certainly expedite the adoption of modern manufacturing technologies.

Another major hurdle has been the burden of filing regulatory applications across multiple global jurisdictions with varying regulatory expectations, especially for new manufacturing technologies. The constitution of a single regulatory authority and universal manufacturing standards will alleviate this challenge and is therefore the need of the hour. Such harmonization will ensure that high-quality medicines are developed in the most resource-efficient manner globally.

Technical Challenges

Industry 4.0 officiates the need to capture, process, and retrieve large amounts of stored and real-time data to facilitate end-to-end automation of the entire manufacturing process. The challenge in handling such large datasets lies in storing them securely. Robust standards around data capture, storage, analysis, transmission, and protection are therefore required. Manufacturers might have to collaborate with third-party data centers in the future to address their growing need for data storage.

Moreover, a smart factory requires continuous communication between the hardware and the software components. This requires extensive investment in advanced networking technology- from networking cables, sensors, machines, servers to cloud storage- all seamlessly connected for undisrupted communication. Novel, cost-effective modes of communication between networked machines that are compatible with a plug-and-play model need to be developed to enable successful industry-wide adoption in the future.

Logistical challenges

As manufacturers and regulators address multiple data, computing, and automation risks, Industry 4.0 approaches will also require organization-wide cultural changes for successful implementation. A new industry infrastructure based on digitized and interconnected enterprise systems requires several skills beyond those gained through the traditional disciplines of biology, chemistry, and process engineering. Skilled data scientists, computational and systems engineers, IT specialists, and AI experts will need to be hired. This might lead to a higher cost of adoption as the pharmaceutical industry will be competing with the software industry for the same small pool of talent in these areas.

Upskilling the existing workforce, bridging knowledge gaps through extensive training programs, and interdisciplinary hiring are some of the ways through which the talent pool can be broadened and the cost of implementation can be minimized.

Future Implications

While it can be argued that much of the pharmaceutical manufacturing still operates in Industry 2.0, the importance of the efficacy brought about by Industry 3.0 and the paradigm shift in manufacturing that Industry 4.0 promises to usher cannot be undermined. Upon adoption, Industry 4.0 has the potential to dramatically increase the agility, efficiency, flexibility, and quality of the industrial production of medicines. Pharmaceutical supply chains, production processes, distribution, and inventory frameworks could all benefit significantly.

Widespread deployment of advanced manufacturing technologies under Industry 4.0, however, requires a comprehensive regulatory framework, extensive hardware and software infrastructure integration, and highly skilled labour to fully realize the benefits of end-to-end automation. Over the coming years, there is a veritable need for different stakeholders to come together and work in tandem to make smart factories in the field of pharmaceuticals a reality.


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