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The authors discuss the role of quality-control automation in providing better data, enhanced compliance, and potentially faster release times.
Existing regulations involving quality-control (QC) monitoring for biopharmaceutical companies require review of production control records and investigation of issues, including any signs of failures that could affect product sterility. Industry guidelines call for quality data analysis to identify and respond to adverse trends. Visualization and trending tools allow analysts to track adverse trends. As a result, companies must monitor in-process, utility-support systems, and the production environment on a consistent and standard basis (1).
Currently, designing QC programs for water and utility systems includes the identification of critical monitoring points, potential design flaws, and operator error. They also include continuous in-process monitoring, system validation, and system maintenance. Although QC organizations provide sound monitoring systems, a shift from paper-based QC to automated QC will help improve the management of the data being produced.
Figure 1: Using a quality-control repository allows for a smooth flow of information, automation of processes, and capture of information. (ALL FIGURES ARE COURTESY OF THE AUTHORS)
A paper-based QC process is still common for planning activities, collecting and processing samples, and analyzing data. Recording data on paper and in spreadsheets is time-consuming and creates many opportunities for errors and delays. Production and QC organizations each have responsibility for different parts of the monitoring process. This division of responsibility isolates key information. For example, QC is typically responsible for monitoring microbial activity via manual samples processed through the laboratory. Production is typically responsible for the in-process and continuous-monitoring points that provide indicators of microbial activity and process control. These disconnected sources of information and a lack of standards for sharing data may result in critical information not being shared until after an out-of-specification event occurs. The disconnected process results in increased labor costs, wasted time on recordkeeping, and delays in reporting, which in turn leads to ineffective data analysis, a reduction in the overall effectiveness of the QC program, and potentially the speed of product release. Automated processes provide an speed of product release.
Figure 2: The paperless quality-control process can eliminate11 of 25 tasks across the sample scheduling, collection, processing, and reporting operations. Light blue boxes indicate eliminated tasks; darker blue boxes indicate retained tasks.
Automated processes provide an electronic representation of the QC program, eliminating many of the clerical steps required in a manual, paper-based system—recording, reconciling, storing, and retrieving information. Compliant and accurate information goes to a QC repository that is available on corporate networks providing comprehensive data on all key monitoring points. Data are immediately available for reporting, trending, and investigative support through a variety of ad hoc analytical and visualization tools, statistical process control software, and other widely used software packages for professionally formatted report output.
Throughout the process, samples are collected containing information such as location, time, product/lot, and equipment traditionally transcribed on paper. Specialized QC software allows this information to be recorded electronically at the point of sample and prevents omission errors through the system by requiring entry of information into each field. It also can automatically fill in correct information where possible and incorporate bar-coded information to further reduce the potential for handwritten errors.
These samples are checked into laboratory storage or equipment such as incubators. The QC software controls which samples can be submitted and their destination points, thereby further reducing the chance of error. To reduce the chance for deviation from a procedure, controls also are in place to manage the duration of incubation/storage.
Samples are tested and results are read. Information is electronically recorded for these steps, and calculations are automatically performed eliminating the risk of calculation error. Results are compared against the alert/action limits by the software and users are notified when a sample is out-of-specification.
Lastly, these samples are ready to be reviewed. Reviewers are able to see all the information recorded during the previous steps, including the task performers. Visual cues specify the samples that are out-of-specification. The data is available for trending. Traditionally, paper information had to be entered into a spreadsheet or database then manually reformatted for trending. The use of QC software allows the user to trend at the click of a button.
A typical paperless QC process starts by scanning a barcode to identify QC sampling requirements at a specific location such as a cleanroom, utility port, or production line. The location at which the sample is taken, media used, equipment used (i.e., total organic carbon apparatus, conductivity meter, and pH meter) is recorded.
Wireless tablet personal computers, barcode scanners, and thermal barcode printers using sterile label stock can be used to perform the mobile data acquisition. Sealed laptop computers can provide the capability to run the specialized QC software as well as other software systems such as document management applications for standard operating procedure (SOP) access within an aseptic production environment. This automated solution component eliminates the risk of introducing shed particles from paper copies and helps to improve overall compliance.
Automation can reduce scheduling, sampling, and associated time for managing the monitoring routines by 35–50%, as reported at Lonza's manufacturing facility for biopharmaceutical products in Walkersville, Maryland. Products range from research reagents to licensed test kits to regulated parenteral products.
Integration of monitoring devices such as total organic carbon and endotoxin analyzers eliminates separate data flows from these respective devices and the problem of an analyst having to manually enter the data into another system such as a laboratory information management system (LIMS) database or spreadsheet. Data from these devices transfers directly into the system of record, eliminating paper data recording, manual reconciliation, and transfer and reformatting. The data from the devices is stored in a structured format to report, trend, and correlate the information obtained from other sources for immediate decision support.
Integrating the QC repository with in-process and continuous monitoring systems is a next crucial step in further automation. In-process data in a common format with manual QC data provides a single view across production and quality assurance. Anomalies in the sample can be correlated to the continuous monitoring performed when the manual sample was obtained. The single dataset can provide critical information to identify potential contamination events before they interrupt production. The primary objective is preventive action performed with real-time trend analysis, shorter investigation time, root-cause analysis, and immediate alerts for critical events. With these tools, system trends such as seasonal mold can be identified, and cleaning regimens adjusted proactively.
Comprehensive data reporting, analytics and trending tools, and a dedicated repository, or "data mart" combine relevant information sources from production and QC. Custom analytical views or "dashboards" combine key performance metrics and user alerts with targeted information that the user can apply in QC, production, or other production-release decisions. Trend analysis improves over time and across processes. More importantly, the information can be used as a common communication tool between QC and production. A QC test revealing contaminated water, for example, can be quickly communicated to production so that the water is not used in any process.
The value of an automated QC process is measured by its ability to support product-release decisions for a wide range of pharmaceutical products, thereby moving organizations toward the ultimate goal of release in full compliance with real-time information. QC information needs to meet the following four requirements to support product-release decisions:
The benefits of automatic mobile data acquisition and workflow, device and in-process integration, and common analytical standards and tools include increased productivity, improved compliance, and faster product-release decisions. A fully integrated QC process using these technology solutions is an important part of any regulated organization's process analytical technology initiatives. An organization focused on producing high-quality, actionable QC information has the ability to continuously improve a production process focused on delivering product of the highest quality with maximum efficiency.
Michael Goetter is director of informatics strategy, Lonza Wayne Inc., 1255 Drummers Lane, Suite 202, Wayne, PA 19087, tel. 484.253.1000 ext 101, fax 484.253.4054, firstname.lastname@example.orgJeremy Tanner is product specialist, Lonza Walkersville Inc.
*To whom all correspondence should be addressed.
1. FDA, Guidance for Industry: Sterile Drug Products Produced by Aseptic Processing: Current Good Manufacturing Practice (Rockville, MD 2004).