How Edge Computing Supports GMP Data Collection and Reporting

My second blog in the series on digital transformation in the life sciences industry explains how edge computing (EC) will support GMP data collection and reporting due to the need to improve efficiencies and expand production to deliver more drug development and manufacturing services. This need results from the growing novel therapies market and the need to streamline operations to keep up with demand.

What is edge computing?

According to IBM, “In the past, the promise of cloud and AI was to automate and speed innovation by driving actionable insight from data. But the unprecedented scale and complexity of data that’s created by connected devices has outpaced network and infrastructure capabilities.”

This is where the EC model comes in. Instead of transmitting data through a central hub, it is processed “on the edge,” closer to where the data is collected. The data is collected at a greater speed and volume than before, leading to faster response times in case of anomalies or other issues.

What are the benefits of edge computing?

EC offers unique advantages over traditional models, enabling companies to improve their management and usage of physical assets while creating new interactive human experiences. Think of “smart” devices – speakers, watches, phones – locally collecting and processing data while touching the physical world. For example, inventory systems and sensors can all be edge devices if their computer lives locally and communicates with the cloud. There is no separate “edge network.” Instead, the network is located on individual devices or a router. If a separate network is involved, it’s simply another location between users and the cloud.

More benefits include:

1. Reduced Latency: EC enables data processing and analysis closer to the source, minimizing latency so critical data can be processed and analyzed in real time. In turn, decision-making and responses to potential problems are faster than without it.
2. Enhanced Data Security: EC processes and maintains sensitive, good manufacturing practice GMP data locally instead of a centralized cloud server, reducing the risk of data breaches during transmission. It also ensures that critical manufacturing data is secure on the local network.
3. Improved Reliability: EC allows GMP data collection and reporting to continue functioning in cases of network disruptions or latency issues. By leveraging local processing capabilities, edge devices can store and process data independently, minimizing the impact of network failures on real-time data monitoring and reporting.
4. Bandwidth Optimization: EC reduces the amount of data that needs to be transmitted to a centralized server or cloud. By performing data processing and analysis at the edge, only relevant and actionable insights need to be transmitted, resulting in optimized bandwidth usage and reduced costs associated with data transfer.
5. Scalability and Flexibility: EC allows for distributed architecture, enabling the deployment of edge devices across multiple manufacturing locations. This scalability provides the flexibility to collect and process data from various sources simultaneously, supporting multi-site manufacturing operations and facilitating centralized monitoring and reporting.
6. Compliance with Regulatory Requirements: GMP regulations often require real-time monitoring and reporting of critical manufacturing parameters. EC facilitates the collection, analysis, and reporting of data promptly, ensuring compliance with regulatory requirements.
7. Cost Efficiency: EC reduces the need for extensive cloud infrastructure and the associated costs. By leveraging existing edge devices and gateways, manufacturers can optimize their IT infrastructure investments and allocate resources more efficiently, resulting in cost savings.

What are the challenges of edge computing?

As with any new system, there is a learning curve involved in adapting EC, though the benefits far outweigh the challenges. Some risks attributed to EC – and methods to overcome them – include:

1. Network Connectivity and Reliability: Maintaining reliable network connectivity at the edge is often challenging, causing problems with intermittent connectivity, latency, and bandwidth limitations. Overcome these issues by using technologies such as edge caching, content delivery networks (CDNs), and network redundancy tools. Using edge frameworks that support offline operation and local processing can also help decrease reliance on constant connectivity.
2. Security and Privacy: When processing and applications are centralized at a hub, technical and physical security can be standardized by building a virtual wall around the resources. With EC, all remote servers need the same network and physical security to reflect location and traffic patterns. User access must be organized, as users may need access rights over several devices. Counteract this issue by employing edge-to-cloud or edge-to-data center architectures to enable seamless data transfer and storage in scalable infrastructure, providing the necessary capacity to handle edge-generated data.
3. Scalability and Resource Constraints: Remember that EC isn’t just about more hardware in remote locations. The knock-on effect scales everything IT touches: computing, network, storage, management, security, licensing, and more. To overcome such obstacles, implement frameworks that distribute workloads across devices, optimize resource use, and enable seamless load balancing. Cloud integration can help offload high-bandwidth tasks to a more powerful infrastructure, leaving your edge devices to focus on critical load processing.
4. Control and management: While EC can be flexible (private cloud, 5G mobile, or a public cloud), management and controls must follow the same protocols. For remote devices, software updates, and application deployment, it’s best to use the most up-to-date tools to help manage and control applications consistently. Automation tools can help streamline software and remote access. By centralizing monitoring and analytics, users can better see the big picture and provide maintenance and fix issues as soon as they begin.

How can EC help solve industry challenges?

Every industry has challenges that can affect daily production, security, data, and compliance. These problems can be incredibly costly and result in downtime, wasted products, data breaches, and even factory shutdowns. Using an EC platform can help avoid issues affiliated with:

1. Optimize production processes: Consistent product quality requires precise requirements in pharmaceutical manufacturing processes. Employing an EC platform ensures continuous uptime and minimal disruptions, allowing for monitoring and optimization of production processes. Inefficiencies are quickly identified for real-time adjustments, resulting in a consistent product and less waste.
2. Regulatory compliance: Non-compliance with strict regulations can incur fines and downtime. Companies using EC monitor real-time data for audit tracking, ensuring regulatory compliance.
3. Critical data collection: A GMP facility produces such massive amounts of data daily that managing it can be a tall task. EC helps manufacturers collect, analyze, and secure data near the source, allowing for quick and accurate decisions, preventing data loss.
4. Data security: EC collects and stores data in the facility instead of external networks, adding an extra layer of security. Because the platform shows assets in real-time, any abnormalities or potential data breaches can be found and addressed quickly. Most EC models have built-in security features that ensure platform integrity and protect companies from unauthorized access.
5. Predictive equipment health: Product development and the manufacturing process as a whole are severely affected when equipment stops working correctly. By using EC, manufacturers accurately analyze sensor data and alert workers to potential equipment failures before they occur.

Final thoughts

The world of life sciences is moving so quickly today that keeping up with new methods, models, and technologies is difficult yet crucial to researching, developing, and distributing the best therapeutics possible. If you’re not already using EC in your facility, your ability to collect data as fast as possible while maintaining a secure network may be at risk.

Resources

“Edge Computing in Pharmaceutical Manufacturing.” Stratus. Accessed 10/17/23. https://resource.stratus.com/solution-brief/edge-computing-in-pharmaceutical-manufacturing

“How to Overcome the Top 5 Challenges of Edge Computing.” ASBResources. 7/31/23. Accessed 10/17/23. https://asbresources.com/how-to-overcome-the-top-5-challenges-of-edge-computing

“What is edge computing?” Accenture. Accessed 10/17/23. https://www.accenture.com/us-en/insights/cloud/edge-computing-index

“What is edge computing?” IBM. Accessed 10/17/23. https://www.ibm.com/topics/edge-computing