Pre-Course Session: Statistical Process Evaluation and Reporting - Live Online

Pre-Course Session: Statistical Process Evaluation and Reporting - Live Online

Seminar Nr. 19466

All times mentioned are CET.

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Rückfragen unter:
Tel.: 06221 / 84 44 0 E-Mail: info@concept-heidelberg.de

Sprecher

Dr Rainer Gnibl, GMP Inspector for EMA
Prof Edwin van den Heuvel, University of Technology Eindhoven
Dr Andreas König, Quality König
Dr Jens-Uwe Rengers, JeRo Consulting
Aline Zillig, Kite Pharma

Zielsetzung

This pre-course session will provide you with recommendations, tools and examples to apply statistical principles in your day-to-day business and it will help you to meet future challenges.

You will gain understanding of the consequences of appropriate and inappropriate performance parameters and a sound evaluation of data also by working with statistical simulation tools.

Zielgruppe

This Education Course is designed for managers, supervisors and all other staff members in the pharmaceutical and API industry who are involved in preparing and compiling Quality Reviews and Metrics.

Technical Requirements

For our online training, we use Cisco WebEx, one of the leading suppliers of online meetings. At http://www.webex.com/test-meeting.html you can check if your system meets the necessary requirements for the participation at a WebEx meeting and at the same time install the necessary plug-in. Please just enter your name and email address for the test. If the installation is not possible because of your rights for the computer system, please contact your IT department. WebEx is a standard nowadays and the necessary installation is fast and easy.

Programm

The Application of Statistical Tools in Data Review
  • Introduction
    - Ongoing/data collection and management
    - Interpretation, comparison and presentation of data
    - Describing process capability and Performance
    - Control Charts; what is a trend and how to deal with it?
    - Quality Metrics
    - Documenting the outcomes; are we in control?
  • Quality Review Summary Report
    - Descriptive statistics
    - Outlier detection
    - Normality testing
  • Quality Review Performance
    - Control Charts
    - Capability indices
  • Case study on analysing and interpreting process performance data

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