Signal management in quality control

Abstract

The concept of signal management is not new, primarily in pharmacovigilance. Signal management in quality control requires a reflection in qualifying and quantifying its correlation to quality assurance. The increased regulatory interest and focus on quality and risk management are significant for implementing and maintaining a quality management system, that incorporates risk-based thinking. It is unacceptable to be within the specification limits but out of statistical control. The research aims to identify and develop tools that can be utilised to integrate signal management techniques and investigate trend analysis in the quality control testing of finished pharmaceutical products. It aims to define outlier results, develop methods for identifying them and utilise control charts to help in understanding and evaluating variations in a process over time. The research also discusses the procedure for conducting a laboratory investigation, the responsibilities of the personnel involved and the final evaluation of the test result. Signals were identified through the development and validation of a questionnaire to further evaluate potential problems that could occur during the testing process. Quality Control personnel working in the pharmaceutical industry were asked to assign an impact level, from very low to very high, on factors which can be considered as signals and pointing to non-conforming aberrant test results. The questionnaire was categorised into building and facilities, the laboratory environment, personnel, sample preparation, equipment, materials, methods and integration of chromatograms. The outcomes were analysed and presented in the form of bar charts. Based on the results, signals were identified and managed by discussing the appropriate implementation of corrective and preventive actions. Eighteen participants took part in the questionnaire directed to personnel working in Quality Control. The signals with the highest scores were mix-ups, contamination and test preparation errors. Out of the respondents, five believe that all signals should be investigated the same way, regardless of their urgency or impact, while eight others believe that the urgency of signals should be determined by how frequently they occur. Overall, all respondents agree that high-quality training is crucial in achieving high-quality results and that the identification of signals is an effective way to predict non-conformities. Signal detection has pointed out practices in the Quality Control laboratory that require attention. The finding points out that signal management can be used for continual improvements of the quality system and hence quality assurance. The signal management process in quality control is an effective process for the evaluation of risks, alert and action limits and proactively deals with signals before the process is out of control.