The pharmaceutical industry considers Applied Statistics for FDA Process Validation to be of very high importance. In 2011, the FDA set out this guidance for the industry. as part of this guidance, called “Process Validation: General Principles and Practices”, which sets the framework for Process Validation in the pharmaceutical industry, any organization in the pharmaceutical industry has to set up a three-stage process.
These are the three stages:
I. Process Design
II. Process Qualification, and
III. Continued Process Verification.
Stage 1, or what is called the Process Design stage, is the stage in which the commercial manufacturing process is defined. This definition is based on knowledge gained through development and scale-up activities.
Stage 2, called the Process Qualification, is the stage in which an evaluation is made of the process design to determine if the process is capable of reproducible commercial manufacturing.
Stage 3, the Continued Process Verification, is meant for giving ongoing assurance during routine production to ensure that the process remains in a state of control.
A seminar on the ways implementing Applied Statistics for FDA Process Validation
GlobalCompliancePanel, a leading provider of professional trainings for the regulatory compliance areas, will be organizing a two-day seminar in which the ways of using Applied Statistics for FDA Process Validation will be taught. Richard Burdick, Emeritus Professor of Statistics, Arizona State University (ASU) and former Quality Engineering Director for Amgen, Inc., will be the Director of this seminar on applied statistics for FDA Process Validation.
In order to learn Applied Statistics for FDA Process Validation in-depth, please register by visiting Applied Statistics for FDA Process Validation. This course has been pre-approved by RAPS as eligible for up to 12 credits towards a participant’s RAC recertification upon full completion.
A detailed and methodical approach to implementing statistical methodologies
This two-day course on Applied Statistics for FDA Process Validation will focus on the ways by which a systematic approach to implementing statistical methodologies into a process validation program consistent with the FDA guidance can be established.
Beginning with a primer on statistics, Dr. Burdick will explain how the methods of Applied Statistics for FDA Process Validation seminar can be applied in each remaining chapter.
Dr. Burdick will next move on to explaining the two fundamental requirements for Process Validation, namely the application of statistics for setting specifications and assessing measurement systems (assays).
He well then show how to apply statistics through the three stages of process validation as defined by requirements in the process validation regulatory guidance documents.
Given that the methods taught through all these three stages are recommended by regulatory guidance documents; this seminar on Applied Statistics for FDA Process Validation will provide references to the specific citations in the guidance documents.
This seminar on Applied Statistics for FDA Process Validation will lead participants into ways of establishing a systematic approach to implementing statistical methodologies into a process development and validation program that is consistent with the FDA guidance.
All-round learning related to Applied Statistics for FDA Process Validation
Dr. Burdick will teach participants how to:
o Assess measurement systems (assays)
o Use Design of Experiments (DOE)
o Develop a control plan as part of a risk management strategy, and
o Ensure process control/capability.
All concepts at this Applied Statistics for FDA Process Validation seminar are taught within the three-stage product cycle framework defined by requirements in the process validation regulatory guidance documents.
Although established for the pharmaceutical industry, this seminar on Applied Statistics for FDA Process Validation also provides a useful framework for other related industries.
In this important learning on Applied Statistics for FDA Process Validation; Dr. Burdick will cover the following areas:
o Apply statistics to set specifications and validate measurement systems (assays)
o Develop appropriate sample plans based on confidence and power
o Implement suitable statistical methods into a process validation program for each of the three stages
o Stage 1, Process Design: utilize risk management tools to identify and prioritize potential critical process parameters; and define critical process parameters and operating spaces for the commercial manufacturing process using design of experiments (DOE)
o Stage 2, Process Qualification: assess scale effects while incorporating large (pilot and/or commercial) scale data; develop process performance qualification (PPQ) acceptance criteria by characterizing intra and inter-batch variability using process design data and batch homogeneity studies; and develop an appropriate sampling plan for PPQ
o Stage 3, Continued Process Verification: develop a control plan as part of a risk management strategy; collect and analyze product and process data; and ensure your process is in (statistical) control and capable.