“The process is the product” is a common saying in pharmaceutical manufacturing. It is no surprise that pharmaceutical manufacturers face evolving and increasingly stringent regulations governing their processes. The need to improve quality compliance, reduce costs, and optimize operational efficiencies must be a priority for any organization intending to compete in the industry. One of the most important aspects of pharmaceutical manufacturing is proving compliance and adherence to established standard operating procedures (SOPs). Implementing a reliable and auditable monitoring solution for pharmaceutical samples, assets and equipment is an important part of proving compliance.
When monitoring valuable samples, assets and equipment, pharmaceutical manufacturers must focus on ensuring internal and external quality and compliance. Implementing fail-safe procedures that ensure samples or assets are handled, packaged, maintained, and stored in appropriate conditions throughout their lifecycle is critical to a well-functioning manufacturing facility.
Data collected at a manufacturing facility such as ambient parameters, storage conditions, and equipment functionality is critical for root cause analysis, process optimization, and increasing yield. However, there are often disconnects between what is recorded on the manufacturing floor and what is reported to an operational or quality management team due to error-prone, manual tasks. These methods, often paper-based, limit an organization’s ability to improve manufacturing operations and can exacerbate the duration or consequences of an audit.
There are many recent developments occurring in device connectivity and data collection from individual devices, OEMs, and machines in pharmaceutical industries. Machine Learning, Artificial Intelligence and the Internet of Things (IoT) are being leveraged more than ever and have an immense impact on optimizing overall operations. Manufacturing equipment requires constant monitoring and industry leaders are continuously searching for robust software platforms to aggregate and analyze this data to improve their operations.
Implementing a monitoring solution for control over all ambient parameters, equipment functionality, and product storage is an efficient way to ensure that pharmaceutical manufacturing operations are safeguarded. At a manufacturing facility, air quality must be constantly tested for temperature, humidity and airborne particulates, such as volatile organic compounds (VOCs), which can introduce contaminants during manufacturing processes. Sensitive, expensive equipment requires regular calibration and continuous monitoring. If equipment is uncalibrated, data outputs may appear acceptable when they are actually outside of established limits. In addition, the close monitoring of equipment reveals correlations between batch yield and parameter deviations.
Real-time notifications for any deviation from preset parameters is the best way to maintain total control over and continuously improve upon manufacturing operations. A comprehensive monitoring solution should capture pertinent data from any type of equipment or sensor as well as import historical data for analysis. Certain solutions can even leverage predictive analytics to determine if equipment needs maintenance or calibration long before failures occur or yields are ruined. Organizations leveraging advanced monitoring systems are able to minimize production downtime, optimize maintenance schedules, and reduce operational costs.
Pharmaceutical manufacturers that want to understand the benefits of implementing a real-time, autonomous monitoring solution should consider the potential for reducing product variability, increasing operational insight, and reducing quality and compliance risks. There are many monitoring solutions available for pharmaceutical industries, but most are finite solutions that are difficult to integrate into existing manufacturing processes. Simple, rudimentary sensors or data loggers on the market eventually encounter similar problems as the time-consuming, manual data entry that organizations try to avoid. The processes involved with these archaic systems are seldom superior to manual, paper-based tasks and are inadequate for proper reviewing and reporting cycles. A monitoring system that is robust and scalable is paramount for fast-growing companies. A cloud-based platform that is OEM agnostic and capable of monitoring both wired and wireless laboratory asset and equipment sensors will ensure that a company is well prepared for any potential problems. Autonomous, real-time monitoring closes gaps in procedures, increases the quality and traceability of an organization’s data, and mitigates common risks found in data loggers and paper-based monitoring practices.