Fundamental Tools in Statistics for GMP Compliance
|Event Date/Time: May 10, 2010||End Date/Time: May 11, 2010|
|Registration Date: Mar 11, 2010|
Introduction and basic overview of Common Statistical Tools
Fundamental Tools in Statistics
Statistical Process Control - Pareto chart
Control chart diagnostics
Design a statistically sound sampling Plan
Applying statistics to specification Setting
T-test (one-sample, two-sample and paired)
Tolerance intervals and confidence intervals
Capability analysis - Cp, Cpk, Pp and Ppk
Implementing Design of Experiments (DOE)
Interpreting a normal probability plot
Comparing confidence interval of parameters to p-value
Method Validation â€“ ICH Q2R1 â€“ Accuracy, Linearity, and Precision
Statistics for Annual Product Review (APR) and how to present data
Case Study Sessions
Participants will be divided into groups of 4 to work on each case study and they will lead the discussion on the â€œreport outâ€ for each case study.
CASE STUDY (1): Interpreting data and calculating summary statistics
CASE STUDY (2): Setting Specifications and what would be the best approach?
CASE STUDY (3): â€œBake a Cakeâ€ - Using DOE, make the best cake using a three factor model
CASE STUDY (4): Using Excel to do Regression - Developing a simple linear model and checking for residual patterns.
CASE STUDY (5): Determining the accuracy and linearity of the assay by providing a data set.
CASE STUDY (5): Reviewing Control charts - Setting up a control chart from a data set and determining if the process is in control.
CASE STUDY (6): Developing Sampling Plans
About the Course
This two-day comprehensive hands-on workshop training offers a detailed introduction to the fundamental principles and concepts in statistical analysis used in pharmaceutical, biotech, and allied industries. The applied sessions are aimed at all life sciences scientific professionals involved in designing experiments and analyzing data.
The first part of the course covers classical and more recent techniques used to describe data with numerical and graphical tools. The various uses of these methods like statistical process control, outlier detection, and applying statistics in setting up specification are presented.
Using real-world, examples, the second part this course addresses, the principles underlying statistical testing and decision-making in the presence of uncertainty.
After completing this course the attendees will:
learn the statistical concepts underpinning Statistical Process Control
understand the effects of variation on processes and be able to use that understanding to make sound decisions
be able to set up a control chart from a data set and determine if the process is in control
be able to develop sampling plans
be able to determine the accuracy and linearity of the assay
develop a simple linear model and be able to check for residual patterns
Much much more
The hands-on case study workshops will provide the necessary foundations for more specialized expertise in any area of statistical data analysis as it applies to life sciences. The selected topics will cover basic assumptions of most statistical methods and/or have been demonstrated in research to be necessary components of one's general understanding of the "quantitative nature" of reality.
Participants will be required to bring their own laptop computer on which to run the analysis exercises.