Prague, Czech Republic
Seminar Nr. 15172
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Tel.: 06221 / 84 44 0 E-Mail: email@example.com
Dr Christopher Burgess, Burgess Analytical Consultancy, UK
Trevor Coomber, Pharmaceutical Development Consultant, UK
Dr Xaver Schratt, LPU Labor für Pharma- und Umweltanalytik GmbH, Germany
The objectives of this Education Course are
to offer practical solutions for determining the validation characteristics
to learn how to deal with measurement uncertainty and to understand its impact on analytical methods validation
to discuss the scope of validation necessary to obtain approval by the Registration Authorities (EMA, FDA, MHRA, etc.)
to become familiar with the statistical parameters to be applied
to understand the qualification of laboratory equipment as a precondition of reliable analytical testing
to outline the documentation (SOPs, Validation Protocols and Reports, etc.) which you should have in your lab.
In order to improve the understanding and practical application of the contents of the lectures, workshops will be part of the training course.
Guideline Q2(R1) lists all characteristics to be considered during validation and describes the method of determining the various validation characteristics. Reliable analytical results do not only require validated test procedures but also the use of analytical equipment qualified for its intended purpose. In order to obtain the FDA investigator‘s approval, the qualification of all critical laboratory equipment should be performed in standard IQ/OQ/PQ format. Furthermore, measurement uncertainty is of key importance in analytical instruments qualification as well as in analytical methods validation and transfer. Therefore it is absolutely essential that measurement uncertainty is well understood by everybody who is responsible for generating and evaluating analytical results in GMP controlled laboratories.
This interactive Education Course will be of particular interest to Laboratory Managers, Supervisors and Analysts in pharmaceutical quality control departments who have responsibility for the validation of analytical test procedures. Furthermore, this Course is designed for personnel from Quality Assurance, Regulatory Affairs and Contract Laboratories.
Each participant gets a brochure containing over 200 pages of examples and validation protocols on analytical methods validation for free.
Validation in Context
Components of data quality
Integrated Approach to Qualification and Validation
Basics of Measurement Uncertainty
Why is measurement uncertainty important?
Relationship between uncertainty and confidence
Uncertainty of measurement
What is a measurand
Error sources in analysis and testing
Analytical Instrument Qualification
Validation Master Plan
Definition of DQ, IQ, OQ and PQ
Examples of protocols and documents
Measurement Uncertainty in Calibration and Qualification of Analytical Instruments
Qualification, Calibration & Validation
Propagation of Errors
Measurement uncertainty of a CRM
Detection and quantitation limits
Noise & drift
New Developments in Instrument Qualification - The USP Proposals
Statistical Aspects of Analytical Methods Validation
The use (and misuse?) of statistics to support validation data
Basic theory of the common statistical techniques
Merits, pitfalls and underlying assumptions of particular tests
The meaning behind
Standard deviation - F-test - t-test
ANOVA - Correlation Coefficient
Exploration of more sophisticated statistical techniques such as interval hypothesis testing and experimental design
Practical Determination of: Robustness Leading to System Suitability Tests
Method development cycle
Analytical process capability
Selecting factors and levels
HPLC experimental design example
Impact on system suitability tests
Method Validation During the Development Lifeycle
Product Development Life Cycle
Sources of Guidance
Screening and Early Safety Studies
Phase 1 Volunteer Studies
Phase 2 Clinical trials
Validation for MAA/NDA Planning and Execution
Analytical validation according to USP
FDA Guidances for method validation
Validation for MAA/NDA Documentation
Validation documentation for registration
Other Sources of Guidance
Error budgets and reportable values
What is a reportable value?
OOS, OOE & OOT
Method performance and process capability
ICH precision approach
Measurement Uncertainty approach combined sources of variation
Transfer of Analytical Test Procedures
Analytical significance vs statistical significance
Acceptance criteria setting