OOT Forum 2015 & Post Conference OOS Workshop

OOT Forum 2015 & Post Conference OOS Workshop

Barcelona, Spain

Course No 9359


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Dr Christopher Burgess, Chairman of the Analytical QC Working Group
Dr Milan Crnogorac, Roche, Switzerland
Dr Lori McCaig, Genentech/Roche, USA
Dr Peter Rauenbuehler, Genentech/Roche, USA
Dr Bernd Renger, Member of the Analytical QC Working Group, Germany
Dr Lance Smallshaw, UCB Biopharma, Belgium
Dr Bianca Teodorescu, UCB Biopharma, Belgium
Stephen Young, Head of Analytical Science Inspection, Enforcement and Standards Division, MHRA, UK


The ECA Working Group on Analytical Quality Control was founded in 2010 in order to generate a harmonised SOP on managing analytical deviations within the laboratory including OOS, OOE and OOT results.

Version 2 of the ECA OOS SOP is already available for all ECA members since 2013.

Given the complexity of the topic, it was decided that the handling of OOT and OOE results should be addressed in a separate guideline SOP, since there is both a lack of knowledge in the industry and a lack of guidance for trend analysis from the regulators in spite of increased regulatory interest in this area.

In 2013 the ECA’s QC Working Group decided to address these issues by developing a new guideline aimed at QC and other quality groups to encourage the application of a consistent and scientifically sound approach to trend analysis as part of a QMS for assuring data integrity.

There were initially three core components:

Recommended approaches for detecting out of expectation (OOE) data within an analytical sequence which are based on the known process capability of the analytical procedure used.
Recommended approaches to detecting out of trend (OOT) data between analytical sequences where no trend is expected. These are based on standard Statistical Process Control methodology and
Recommended approaches for detecting out of trend (OOT) data between analytical sequences where a trend is expected as is the case for Stability Testing.

From this foundation the current guideline was developed by an international team to provide a harmonised approach to trending.

At this ECA OOT Forum in Barcelona version 1 of our guideline will be presented and participants will have the opportunity to review and discuss the contents and technical aspects of the guidance document as well as looking at the scope and application of the proposed methods within industry .

The ECA QC Working Group’s goal is to have a basic global framework for OOT/OOE within R&D, production and QC laboratories which is acceptable to the authorities and adaptable for individual companies.

Target Group

This conference is intended for technical and managerial personnel dealing with out-of-trend or out-of expectation results, including R&D, production, analytical laboratories, contract laboratories, and Quality Assurance/Quality Control personnel.

ECA OOS Workshop on 4 December 2015, 08.30 - 16.00 h


OOS: US/FDA and European Regulatory Expectations
OOS Results in R&D Laboratories

ECA Analytical Quality Control Working Group - OOS SOP Version 02

Strategies not to generate OOS results

Laboratory OOS results scenarios in QC and Development will be presented and evaluated in workshop groups

Speakers: Dr Christopher Burgess, Dr Bernd Renger



Introduction to ECA’s Analytical QC Working Group and the OOT Process
Overview of ECA’s Analytical QC Working Group
Data quality management in the Laboratory
Structure of the OOT/OOE guideline generation process
Importance of a Technical Glossary
Overview of the contents of the OOT/OOE Guideline
Aims and objectives for this Forum
Dr Christopher Burgess

Regulatory Importance of Trend Analysis under the EU GMPs
Regulatory concern for the control of processes
Overview of the cited regulatory references
Challenges for implementation and inspection
- within the industry
- for the inspectorate
Stephen Young

The Statistical Tool Box; Basics of Selection
What is a trend?
What is a control chart?
Data types
Data distributions
Statistical control
Common cause variation
Special cause variation
Process stability versus process capability
Dr Christopher Burgess


Recommendations for Process Control of Variables (OOT1)
Overview of the control of Continuous Data Monitoring for manufactured batches and for analytical test samples
The basis for Statistical Process Control (SPC)
Proposal for Control Charts for Individuals
Proposal for Control Charts for Subgroups
Proposal for Control Charts for post mortem investigations
Lance Smallshaw

Example Applications for Variables I - SPC
Importance of individuals and means
Example of SPC for continuous individual data; a Moving Range (MR) Shewhart Chart
Setting the control limits
Example of SPC for continuous data for subgroups; Xbar and R
Process Capability
What if data are not normally distributed?
Dr Bianca Teodorescu

Example Applications for Variables II - Cusum for Investigations
Theory and application of Cusum analysis
Cusum versus EWMA charts
Example of a post mortem Cusum investigation
Dr Bianca Teodorescu


Recommended methods: Trending for Process Control of Attributes (OOT 2)
Basic differences between attributes and variables
Control charts for attributes
Applications for attribute data
Dr Christopher Burgess

Examples for Trending for Process Control of Attributes (OOT 2)
Theory and application of n and np charts
Theory and application of C and U charts
Example of np charting
Dr Milan Crnogorac


Trending for Stability Data I; a simplified Linear Regression Approach
Challenges for trending stability data
Simplified linear regression approach
Assumptions and limitations
Minimum data requirements
Theory and calculation of prediction intervals
Worked example illustrated using Excel
Comparison with SAS JMP; why aren’t the numbers exactly the same?
Dr Peter Rauenbuehler

Trending for Stability Data II; a more advanced Random Coefficients Regression Model
Why is it sometimes necessary?
Basics of the RCR model
Advantages and disadvantages over the simplified linear regression approach
Evaluation of stability data
Examples of its application using statistical packages
Dr Lori A. McCaig


Recommendations on: Out of Expectation Results (OOE)
Definitions for OOE
Unexpected variation in replicate determinations
Unexpected results in a Single Test or a Small Set of Tests
What level of investigation is necessary and appropriate for OOE results?
Dr Bernd Renger


WORKSHOP: Next Steps; Implementation Strategy
Review output from the 6th GMP Conference Workshop on
OOT & OOE, Heidelberg, June 2015
Detailed review of the sections of Analysis & Testing and Stability Testing
Mapping the tools to the identified tasks
Inputs to version 2 of the OOT/OOE Guideline SOP
Dr Christopher Burgess

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