Statistical methods in evaluation and monitoring of product quality as per Annex 15

The scope of the training covers the guidelines of Annex 15, concerning the life-cycle approach to validation, with emphasis on the use of statistical methods of data analysis. The course combines practical knowledge of specific issues related to the pharmaceutical industry with knowledge of methods of data analysis, which are presented using data from the industry. Statistical methods are discussed theoretically and then developed in the form of exercises.

Who should attend?

• Anyone who is involved in process validation. We invite you if you do not yet know anything about data analysis and statistics used in technological process validation lifecycle. If you already know something, but you need to organize your knowledge and go to practice. Also if you already know the statistics, but you need a tool with which you can perform your analyses quickly and easily. This course is the foundation on which you can further build knowledge and skills in data analysis

What will you learn?

• You will get to know or systematize the basic concepts of statistical data analysis
• You will go through the stages of technological process validation
• You will learn numerical and graphical methods of data analysis
• You will get to know process stability and capability assessment
• You will receive practical tips on how to avoid errors in data analysis and interpretation
• You will learn how to plan statistical control of the technological process

Training programme:

1. Introduction
   • What is the modern definition of quality?
   • What are the basic requirements for the implementation of validation life cycle?
   • What are the conditions and criteria for the transition between the life cycle stages of validation?
   • What product/process parameters to include in the statistical process control program?
   • What is the typical test plan for process validation / ongoing process verification?
   • How to deal with difficult cases of unstable and/or incapable processes?
   • How to detect OOT results during ongoing process verification?
   • How to implement the principle of continuous improvement based on statistical analysis results?
2. Population and sampling
   • What is a general population / random samples?
   • What are the properties of the general population / random sample?
   • What are the types of random sampling?
3. Statistical description
   • What is the average value of the dataset?
   • What is the dispersion of the data set?
   • Whether the distribution is unimodal or multimodal?
   • Whether the distribution is symmetrical or asymmetrical?
   • Are there outliers/extreme values?
   • What is the confidence/prediction interval?
4. Analysis of process stability
   • What is the purpose of the process stability analysis?
   • What is the difference between special and common causes?
   • What is the difference between the first type error and the second type error?
   • Which control charts to use for process stability analysis
   • What are the basic principles of the use of control charts?
   • What are the process stability criteria?
   • When and what additional configuration tests to use?
   • How to set control limits for ongoing process monitoring?
   • In what cases should the set control limits be changed?
   • When a change in the limits is justified?
   • What if the points are outside the control limits?
   • What if the data have a different distribution than normal?
5. Analysis of process capability
   • What is the purpose of the process capability analysis?
   • What are the basic principles of process capability analysis?
   • How to determine basic process capability indicators?
   • What is the difference between Cp / Cpk and Pp / Pk indicators?
   • What conditions need to be met in order for capacity indicators to be reliable?
   • What mistakes can be made in determining process capability indicators?
   • When a process can be considered predictable and capable of meeting the acceptance criteria?
   • How to categorize a process based on statistical analysis results?
   • What action to take in the case of unstable and/or incapable processes?

Training hours: 8:15 AM – 3:30 PM

The training includes:

• comprehensive training materials
• certificate of participation
• coffee breaks and lunch (for on-site training)

Training types:

• online or on-site
• the format is indicated with the training date

For online trainings:

• live sessions via MS Teams
• real-time interaction with the instructor

Prerequisites:

• computer skills in a Windows environment

Price: 620 EUR net

Price for academic Statistica users with an active StatSoft Polska support agreement (-15%)*: 527 EUR net