A Systematic Approach to Implementing Statistical Methodologies

Focusing exclusively on qualification efforts without understanding the manufacturing process and associated variations may not lead to adequate assurance of quality.

In Guidance for Industry Process Validation: General Principle and Practices, process validation is defined as, “”…the collection and evaluation of data, from the process design stage through commercial production..” The guidance further delineates the ‘process design stage through commercial production’ into three distinct stages of the product lifecycle:

Stage 1: Process Design: The commercial manufacturing process is defined during this stage based on knowledge gained through development and scale-up activities.

Stage 2: Process Qualification: During this stage, the process design is evaluated to determine if the process is capable of reproducible commercial manufacturing.

Stage 3: Continued Process Verification: Ongoing assurance is gained during routine production that the process remains in a state of control.

The first stage of process validation is process design. The Process Validation guidance document states, “A successful validation program depends on information and knowledge from product and process development. This knowledge and understanding is the basis for establishing an approach to control of a manufacturing process that results in products with desired quality attributes:

Manufactures should:

  • Understand the sources of variation
  • Detect the presence and degree of variation
  • Understand the impact of variation on the process and ultimately on product attributes
  • Control the variation in a manner commensurate with the risk it represents to the process and product.”

The second stage of process validation is process qualification. Although stage 2 has two elements, this course will focus on recommendations for the second element, PPQ. PPQ “combines the actual facility, utilities, equipment (each now qualified), and the trained personnel with the commercial manufacturing process, control procedures, and components to produce commercial batches.” Additionally, the process validation guidance document that “Each manufacturer should judge whether it has gained sufficient understanding to provide a high degree of assurance in its manufacturing process to justify commercial distribution of the product. Focusing exclusively on qualification efforts without understanding the manufacturing process and associated variations may not lead to adequate assurance of quality.”

The third stage of process validation is continued process verification. The process validation guidance document defines the need for this stage: “After establishing and confirming the process, manufacturers must maintain the process in a state of control over the life of the process, even as materials, equipment, production environment, personnel, and manufacturing procedures change.” Manufacturers should use ongoing programs to collect and analyze product and process data to evaluate the state of control of the process. These programs may identify process or product problems or opportunities for process improvements that can be evaluated and implemented through some of the activities described in Stages 1 and 2.”

This course focuses on how to establish a systematic approach to implementing statistical methodologies into a process validation program consistent with the FDA guidance. It begins with a primer on statistics, focusing on methods that will be applied in each remaining chapter. Next, it teaches the application of statistics for setting specifications and assessing measurement systems (assays), two foundational requirements for process validation. Lastly, the course applies statistic through the three stages of process validation defined by requirements in the process validation regulatory guidance documents. Methods taught through all three stages are recommended by regulatory guidance documents; references to the specific citations in the guidance documents are provided.

Areas covered by the Instructor:

  • Apply statistics to set specifications and validate measurement systems (assays)
  • Develop appropriate sample plans based on confidence and power
  • Implement suitable statistical methods into a process validation program for each of the three stages
  • 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)
  • 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
  • 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.

Who will benefit by this:

  • Process Scientist/Engineer
  • Design Engineer
  • Product Development Engineer
  • Regulatory/Compliance Professional
  • Design Controls Engineer
  • Six Sigma Green Belt
  • Six Sigma Black Belt
  • Continuous Improvement Manager

Click and register for 2 day seminar

Author: GlobalCompliancePanel-Training

GlobalCompliancePanel is an online training gateway delivering high quality regulatory & compliance trainings in a simple, cost effective and in a user friendly format.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s