The Business Value of Edge Computing in Pharmaceutical, Medical Device, and Biotech Manufacturing
In the ever-evolving landscape of life sciences, organizations are constantly seeking ways to enhance operational efficiency. With Industry 4.0 concepts helping pharmaceutical, biotech, and medical device companies define their strategies, the digital transformation of manufacturing processes has emerged as a key priority.[1]
At the forefront of these strategies is the integration of IT/operational technologies (OT) to enable a comprehensive view of processes, workforces, and equipment. In this blog post I will look at the enabling role of edge computing in IT/OT integration and at its potential to unlock operational efficiency and drive transformative growth across the different life sciences business functions.
A Resilient and Secure Edge Computing Infrastructure Provides Better Operational Insights
According to a recent IDC survey, more than 40% of life sciences organizations reported significant improvements in operational decision making through enhanced accessibility to edge data. Edge computing is emerging as a critical tool to harness the value of the rapidly growing volume of operational data.[2] Edge computing brings analysis, computation, and storage closer to the source of data generation, enabling real-time automation and management of operations.
To provide resilient infrastructure that can respond to specific security requirements and mitigate downtime risks associated with equipment failure or cyberattack, life sciences IT executives are seeking fault-tolerant platforms to manage and store their edge data. This approach facilitates data integration and exchange between manufacturing equipment, industrial process control systems, quality management solutions, and enterprise applications, while also ensuring that data is protected and available.
Because life sciences manufacturing often spans multiple production lines and sites, edge computing platforms help manage a large number of devices and data, ensuring consistency, systems performance, and synchronization.
From IT Projects to Strategic Initiatives
Edge computing should not be viewed solely as an IT project — it is also a critical enabler of the digital transformation strategies of life sciences organizations. More than 80% of life sciences organizations are investing in edge, having recognized its potential to overcome challenges related to data silos and poor operational visibility.[3] By providing a unified, real-time view from the edge to the enterprise, edge computing platforms help to build the foundations of modern data-centric manufacturing models, aligning with the top priority of operational excellence shared by life sciences organizations worldwide.[4]
Strategic investments in edge computing platforms yield benefits across various roles, functions, and business requirements. Process engineers can leverage these platforms to validate and document changes in production lines and OT, ensuring accuracy, safety, and efficiency.
Real-time information provided by edge computing solutions empowers production technicians to follow SOPs, monitor critical parameters, identify deviations, and initiate prompt corrective actions. This ensures the manufacturing process runs smoothly and in accordance with GMP guidelines.
Edge computing can also provide an audit trail for data, enabling organizations to trace data from source to destination. In regulated industries like life sciences, this capability is critical to ensure data integrity, demonstrate compliance, and maintain trust in the manufacturing process.
Edge computing can play a significant role in transitioning from a culture centered around compliance to one focused on quality. A quality-by-design approach throughout the product life cycle is thus enabled. Edge computing, for example, empowers Process Analytical Technology (PAT) by enabling real-time data analysis. This reduces reliance on manual analysis, enhances process monitoring accuracy, and facilitates the adoption of real-time release testing by quality assurance and quality control teams.
By leveraging technology on the shop floor, edge computing can generate analytical readouts instantly, identify trends, and provide data to quality management systems. This enables the utilization of data not only for retrospective analysis but also for predictive models, thereby improving production processes and control systems.
Empowering the C-Suite and Improving Company Performance
By facilitating real-time data insights, enhancing data quality, and enabling sharper response times, edge computing establishes a vital and strategic link between the shop floor and the top floor of life sciences organizations. C-level executives gain access to superior information that supports both short-term and long-term decision making. Real-time monitoring mitigates the risks associated with equipment failures, downtime, quality deterioration, and product recalls.
Furthermore, edge computing makes the use of predictive analytics possible, aiding in demand forecasting to optimize production lines and enhance product availability. These advancements positively impact company performance by expediting time to market, reducing costs, and improving quality and profitability.
As life sciences organizations pursue digital transformation to achieve operational excellence and to stay ahead in the market, edge computing emerges as a game changer.
When building the business case for edge computing investments, it is crucial to consider the ROI these tools can deliver. Edge computing presents an opportunity for pharma and life sciences executives to enhance their decision-making capabilities, enabling them to make quicker and more informed choices.
An accelerated decision-making process can result in streamlined business operations, enhanced product quality and safety, reduced downtimes, and improved collaboration throughout the company. As a critical component of the foundation stack, edge computing empowers life sciences organizations to handle variability and maintain compliance while embracing the flexible nature required by intelligent manufacturing models.
[1] IDC’s European Health and Life Sciences Survey (2022)
[2] IDC’s Future of Operations Survey (2022)
[3] IDC’s European Health and Life Sciences Survey (2022)
[4] IDC’s Future Enterprise Resiliency and Spending Survey (2023)
