I have had the opportunity to work on projects that involved the use of data monitoring / data logging instruments to validate environmental chambers, sterilizers, washers, and facilities. This post and future posts will introduce the basic terms, engineering concepts, and quality concerns for data monitoring equipment. The terms data monitoring and data logging will be used interchangeably in this blog. An article with this content was also published in the Journal of GXP Compliance, an Institue of Validation Technology publication.
I welcome your comments as I hope to make this dicussion interactive with those of you familiar to this equipment or those of you who want to learn more.
Data logging is the process of collecting information over a certain period of time at predetermined time intervals. The data is generally collected sequentially and at rates faster than what is possible by human observation. Data logging instruments allow for highly accurate measurements to be obtained. One of the most common types of data logging is temperature data recording. This practice is common in the pharmaceutical, biotech, and medical device industries and will therefore be the primary focus and example in this blog. However, with appropriate instruments, many other forms of data can be collected. Examples include:
- Relative humidity
- Pressure
- Electrical currents
Many of the concepts discussed in this blog can also be applied to other forms of data logging. Applications and importance of data logging. Data logging is used in engineering and validation activities to gather sequential readings that can be analyzed to gain a greater understanding of the operation of a system. Systems that may utilize data logging can include any area that has a requirement to maintain a given temperature specification such as:
- Warehouses
- Production rooms
- Refrigerators
- Freezers
- Sterilizers
Data is usually collected simultaneously at multiple locations within the area being tested. Locations are carefully chosen so that the entire area is “mapped”. The data is then analyzed to determine the worst-case locations within the area or system (i.e., the hottest or coldest locations). The data can then be used to perform additional calculations including:
- Minimums
- Maximums
- Averages
- Standard Deviations
- Lethality of a sterilization cycle (F-sub-zero)
Since a complete data logging event contains hundreds to thousands of data points, these calculations make it possible to draw conclusions about the system from the data collected. Data logging is critical to obtaining an accurate, detailed representation of how a system operates. Some systems change temperature very fast, such as a sterilizer, while other systems, such as a refrigerator, change temperature slowly. These systems may also have long cycle times that make it impractical for manual data recording. Data logging also enables a significant number of measurements to be collected over short or long periods of time. The large number of measurements can easily surpass the quantity of points required to be statistically significant.
Follow this blog for future discussions on:
- Types of data loggers, including stand-alone and computer-based instruments
- Temperature elements used in data loggers, including thermocouples, thermistors, and resistance temperature detectors (RTD)
- The configuration of data loggers, including wiring, multiple channels, and self-contained instruments
- Calibration of data loggers
- Use of data loggers in Validation (Qualification), including environmental chambers, steam sterilizers, warehouses, and production rooms
- Collecting data, including probe placement, sampling intervals, and the duration of monitoring protocols
- Electronic data, including electronic files, printing directly from software, exporting to Excel, and key aspects of 21 CFR Part 11 compliance
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