Identifying outlier data points using visual and analytical techniques is especially important for proper process validation, control, and monitoring in the FDA regulated industries. Additionally, properly identifying outliers can assist FDA regulated companies with the proper establishment of trending and excursion limits for complaint and nonconformance management, and other aspects such as environmental monitoring, which can trigger investigations or initiate the formal corrective and preventive action (CAPA) process.
Probably the most significant concern for anyone responsible for implementing, deploying, and maintaining a quality management system (QMS) is the integration of risk-based thinking.
This article will present the concept of contingency planning and introduce some considerations that can be utilized to develop an effective contingency plan.
Probably the most significant concern for anyone responsible for implementing, deploying, and maintaining a quality management system is the integration of risk-based thinking. This article will present definitions and requirements pertaining to process and performance trending and introduce some trending tools that can be utilized throughout the QMS.
This article will first present the definitions and requirements regarding risk pertaining to the control of suppliers and then introduce some tools to incorporate and integrate risk management techniques within the QMS specifically applied to supplier management/purchasing controls.
The real issue in developing a QMS failure mode effects analysis (qFMEA) for the quality management system is how to develop the scales traditionally used to calculate the risk priority number.
This article will first present the definitions and requirements regarding risk and then introduce some tools that can be utilized to incorporate and integrate risk management techniques in and throughout the QMS.
FDA regulations, ISO standards, and GHTF guidance documents do not prescribe the number of runs required for process validation activities. Industry has typically used three batches during the process performance qualification phase to demonstrate that a process is capable of consistently delivering quality product, but the so-called "rule of three" is no longer appropriate for process validation activities.
This article will discuss how to establish sample sizes for process validation when the testing required is expensive or destructive. Of all the approaches discussed in this series, this one is probably the most difficult to address and statistically justify.
The first article in this series, Risk-Based Approaches To Establishing Sample Sizes For Process Validation (June 2016), provided and established the relationship between risk and sample size. This article will demonstrate the use of lot tolerance percent defective (LTPD) to establish sample sizes for process validation.