Statistical Methods for Process Validation
Course Description
This course is specifically designed to meet the analytical needs of those individuals working within FDA regulated industries. A key component of pharmaceutical, medical device and biotechnology product development is to perform process validation and qualification studies. The basic concepts, requirements and statistical methods for process validation are presented.
Audience
This course is required for all scientists, engineering and quality professionals who actively work on process sciences, process development and process validation.
Prerequisites:
ESDA and DOE are recommended prior to taking this course.
16 Hours
Contact Information
Email
paulette@pyyoungassociates.com
Phone
1 (650) 967-2700
Address
P.O. Box 2103
Sunnyvale, CA 94087-0103
Course Objectives
Upon completion of the course the participants will be able to:
- Design, analyze and report validation studies
- Select appropriate analytical tools for process validation
- Define process controls and reviews for continued process verification • Determine sample size for validation studies
- Determine sources of process and material variation
- Establish process capability and design margin
- Report on process validation and qualification performance
- Apply JMP to validation data analysis and reporting
Course Outline:
Process Qualification and Validation Introduction
Process Validation and Drug Quality
General Approach to Process Validation
Statutory and Regulatory Requirements for Process Validation
Process Validation Recommendations
Stage 1: Process Design
Building and Capturing Process Knowledge and Understanding
Establishing a Strategy for Process Control
Stage 2: Process Qualification
Design of a Facility and Qualification of Utilities and Equipment
Process Performance Qualification
PAT during Qualification
PPQ Protocol
PPQ Protocol Execution and Report
Stage 3: Continued Process Verification
Establishing a Monitoring Program
Data Analysis Trending and ongoing Capability Monitoring
Deviations/Investigations and CAPA
Change Control
Complaints
CPV Data Review and Reporting
Analytical Tools for Process Validation
DOE design space
DOE, CPP and PAR analysis
POV and Sample Size during PV
Process Capability and Design Margin
Control Charts during Validation
ANOVA and ANOM
Equivalence Testing