The aim of the course is to familiarise its participants with the guidelines of Annex 15 of the 2015 Good Manufacturing Practice, concerning an approach based on validation life cycle (process design, validation of a commercial manufacturing process, on-going process verification) and statistical data analysis methods applied at particular stages of a product life cycle.

Training description: Annex 15 of the Good Manufacturing Practice on the rules of qualification and validation was updated by the European Medicines Agency in 2015 by introduction of the ICH Q8, Q9 and Q10 guidelines at the International Conference on Harmonization. Validation has become an activity covering the entire product life cycle, starting from product and process development, through validation of a commercial manufacturing process, up to maintenance of the process control in routine production. Understanding of the process and the product through identification and variation control, risk management and the rule of constant improvement are basic concepts in the new approach towards qualification and validation. It is recommended to apply objective (statistical) measures in order to obtain an appropriate level of certainty that the process is under control during the entire lifecycle. Statistical data analysis methods used at particular stages of the product lifecycle enable us to build an integrated and systematised approach to collecting, analysing, storing and sharing data/information concerning products, manufacturing processes and components.
The aim of the course is to familiarise its participants with the Annex 15 guidelines referring to the approach based on a validation lifecycle, with a special focus on the use of statistical data analysis methods. The course combines practical knowledge on specific issues concerning the pharmaceutical industry with the knowledge of data analysis methods presented on the basis of data from the branch.

Every statistical issue will be first discussed theoretically, and then the participants’ knowledge will be developed during practical classes. After the course, the participants will be able to propose appropriate data visualisation and statistical evaluation techniques in a validation life cycle according to the requirements of Annex 15.

Requirements: ability to work with a computer in the Windows environment.

Training programme:

• Basic requirements concerning implementation of a validation lifecycle
• Basic requirements concerning Stage 1 of a process design
• Basic requirements concerning Stage 2 of process validation
• Basic requirements concerning Stage 3 of on-going process verification
• Conditions and criteria of transition between stages of a validation lifecycle
• How to document and report test results at every stage
• What is the typical content of a process validation / on-going process verification protocol and report
• How to create a program of statistical process control in a validation lifecycle
• Which product/process parameters should be included in a program of statistical process control
• Which statistical methods should be applied to product/process parameters analysis
• A typical test plan during process validation/on-going process verification
• Which conditions must be complied with in order for statistical methods and data analysis to be reliable
• When a process can be deemed as stable and capable to comply with the acceptance criteria process
• How to cope with difficult cases of unstable and/or incapable processes
• How to use statistical data analysis methods to justify analysis reduction
• How to detect OOC/OOT results during on-going process verification
• Which product/process assessment criteria should be defined during on-going process verification
• How to implement the rule of constant improvement on the basis of results of a statistical analysis
• Examples of a process validation/on-going process validation protocol and report

• Rules of sampling in the validation process
• Rules of selecting sample size in the validation process
• Statistical description of data
• Methods applied in process modelling
• Statistical interference
• Methods applied in a process model analysis
• Analysis of process stability with the use of Control charts
• Analysis of process capability
• Analyses batch equivalency