Process Validation 2016 - Process Validation in Statistical Process Control-By AtoZ Compliance

Key Take Away:
How to design strategies for process control and operator activities to reduce/adjust for input variation during manufacturing and reduced possibility for operator error, as well as an overall blend to manage critical process parameters (CPPs).
Overview:
The ultimate goal of FDA Process Validation is to ensure continual assurance that the process once initially validated (PQ now PPQ) and submitted for FDA/EU approval remains in a state of control by detecting unplanned departures from the initially proven acceptable process to meet Current Good Manufacturing Practice requirements using the collection and evaluation of data about the consistency of the process. By conducting a specifically designed monitoring system and then as required by regulatory requirements that a statistician or person with adequate training in statistical process control to monitory, sample and analyze the quality attributes of each critical step of a process and also compare batch to batch consistency using the statistical analysis using the appropriate model.
Why Should You Attend:
To gain a current comprehension of the new PV Guidelines and the determination of how to do the required Statistical Monitoring and Data Analysis to prove the process is consistent and to avoid situations that could cause 483s, Warning Letters and Consent Decrees as well as gaining the capability of avoiding rework and recall expenses.
Areas Covered In This Webinar:
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.
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).
Statistical Tracking (database entry and design) along with Annual Report Generation
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.
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
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
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
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)).
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
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
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).
Learning Objectives:
Process knowledge and understanding is the basis for establishing an approach to process control and related instruction sets in the Batch Record for each critical step of the process operation and the overall process results based on statistical database for each batch of that product code. Strategies for process control and operator activities can be designed to reduce variation, adjust for variation during manufacturing and reduced possibility for operator error, as well as an overall blend to manage critical process parameters (CPPs) as well as the original process limits which typically change after the initial validation as well as the trend analysis for each critical step of the process.
Batch Records are to be configured to demonstrate and provide documented evidence each element of the process has been evaluated for potential quality impact with implemented risk remediation and objective (not subjective) evidence each step has been executed as instructed in the Batch Record. The Batch Record Review document is to be formatted in a way that ensures each critical element of the process has been executed and documented according to industry standards for Gross Domestic Product.
Who Will Benefit:
Manufacturing Operations Professionals
Formulation Professionals
Engineering Professionals
QA/QC Professionals
Product and Process Development Professionals
Regulatory Affairs Professionals
Research and Development Professionals
Sterility Assurance Professionals
Technical Operations Professionals
Validation Professionals
FDA inspectors
Internal auditors
Speakers Profile:
Jerry Dalfors
Jerry Dalfors has extensive (40+ years) of business administration, consultative, technical and managerial experience in the development and manufacture of highly regulated biopharmaceutical products including injectables, biologics, medical devices and oral dosages. He has held permanent employee, temporary employee and company representative management positions with a multitude of the major pharmaceutical and biotechnology companies in the US.
He has worked with or assisted more than two dozen companies with the establishment of controlled document/quality systems, FDA briefing and submittal documents, project management of several multimillion dollar projects including design, start-up and validation to assure fast track FDA approval by maintaining strict regulatory compliance during all phases of engineering, construction, commissioning and validation, and has written numerous submission documents for product, process and facility approval/licensing which also required the development of quality systems which included customer complaint management, deviation management, CAPA and associated site wide employee training.
Each of his projects have been received and accepted by the FDA and other regulatory agencies. Jerry is considered an expert in most all aspects of the biopharmaceutical and medical device industry and has trained many FDA field inspectors on a variety of topics. None of his work has ever received a 483 but has corrected and prevented many along with Warning Letter remediation