Process Validation - Statistical Process Control 2015

Key Topics

• Strategies for process control and operator activities can be designed to reduce input variation, adjust for input variation during manufacturing and reduced possibility for operator error, as well as an overall blend to manage critical process parameters (CPPs)
• Process knowledge and understanding is the basis for establishing an approach to process control and related instruction sets in the Batch Record for each unit operation and the process overall
• Variation can also be detected by the timely assessment of defect complaints, out-of-specification findings, process deviation reports, process yield variations, batch records, incoming raw material records, and adverse event reports
• Statistical Tracking (database entry and design) along with Annual Report Generation
• To understand the commercial process sufficiently, the manufacturer will need to consider the effects of scale. However, it is not typically necessary to explore the entire operating range at commercial scale if assurance can be provided by process design data. Previous credible experience with sufficiently similar products and processes can also be helpful. In addition, we strongly recommend firms employ objective measures (e.g., statistical metrics) wherever feasible and meaningful to achieve adequate assurance
• Production line operators and quality unit staff should be encouraged to provide feedback on process performance. We recommend that the quality unit meet periodically with production staff to evaluate data, discuss possible trends or undesirable process variation, and coordinate any correction or follow-up actions by production
• Adherence to the CGMP and GDP requirements, specifically, the collection and evaluation of information and data about the performance of the process, will allow detection of undesired process variability. Evaluating the performance of the process identifies problems and determines whether action must be taken to correct, anticipate, and prevent problems so that the process remains in control (§ 211.180(e))
• The goal of the third validation stage is continual assurance that the process remains in a state of control (the validated state) during commercial manufacture. A system or systems for detecting unplanned departures from the process as designed is essential to accomplish this goal
• FDA recommends that a statistician or person with adequate training in statistical process control techniques develop the data collection plan and statistical methods and procedures used in measuring and evaluating process stability and process capability
• An ongoing program to collect and analyze product and process data that relate to product quality must be established (§ 211.180(e)). The data collected should include relevant process trends and quality of incoming materials or components, in-process material, and finished products. The data should be statistically trended and reviewed by trained personnel. The information collected should verify that the quality attributes are being appropriately controlled throughout the process
• The old Process Validation or PQ (process qualification) was originally set-up in the pharmaceutical, not biotech or biopharmaceutical, using three runs with all variables being run at the target (center of the limits or range values). When biotech and biologics grew to such a large component of the industry, coincidental process variables still within limits began to introduce product failures which is why the FDA has added the phraseology about "sound science and the overall level of product and process understanding as well as demonstrable control – i.e. Sound Scientific Rational (SSR)

Who should Attend

• Formulation
• Manufacturing Operations
• QA/QC
• Engineering
• Regulatory Affairs
• Product and Process Development
• Sterility Assurance
• Research and Development
• Technical Operations and Validation Professionals as well as FDA inspectors and Internal auditors