Mathematics & Statistics - QP Module
Royaume-Uni, York
Course Overview :
There are many training courses on statistics and statistical analysis, but very few which focus specifically on the application of these techniques to pharmaceutical manufacture and control. This is one such course! Designed to meet the needs of the aspiring Qualified Person and other pharmaceutical professionals and taught by a combination of statisticians and pharmaceutical industry professionals, this highly participative 4 day course will teach you how to use statistical techniques to assess and monitor the reliability and accuracy of data you generate and the capability and reliability of the processes you work with. A statistics course like no other!
About This Course :
The pharmaceutical industry has historically underutilized statistical data analysis techniques that have been used extensively in many other industries to drive product and process improvement. It is still too often true to characterize the pharmaceutical industry as being data rich but information poor.
Recent developments in the GMP Guidelines that provide regulatory expectations around the globe are now seeking to drive pharmaceuticals to catch up with other industries by placing far greater emphasis on the trending of data; e.g. EU and US requirements for ongoing process verification as part of process validation, in Product Quality Reviews and ICH Q10. The ability to analyze and trend data is now an essential survival skill. This pharmaceutical training course will show you how to do this simply and effectively.
The provision of useful information is essential to the Qualified Person and other professionals.
This course is approved by the Royal Society of Chemistry as suitable for their members’ continuing professional development.
Key Learning Objectives :
To understand how to :
- Assess the reliability and accuracy of data and information arising from samples taken from a population using techniques such as:
- Basic statistics; mean, standard deviation, etc
- Histograms
- Box plots
- Confidence intervals
- Monitor and detect adverse trends before a process goes out of control using:
- Control charts; shewhart, mean and range, cusum and attribute charts
- Linear regression
- Assess the capability and reliability of a process
- Use, and know the limitations of, acceptance testing using ISO 2859 and ISO 3951
- Compare results using:
- T-tests
- Analysis of Variance (ANOVA)
- Interpret the interaction of process parameters via experimental design and multivariate analysis
- Maintain regulatory compliance