Seminar Nr. 9094
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Tel.: 06221 / 84 44 0 E-Mail: email@example.com
Dr Christopher Burgess, Burgess Analytical Consultancy
Dr Rainer Gnibl, GMP Inspector for EMA
Dr Andreas König, Aenova Holding
Katja Kotter, Vetter Pharma-Fertigung
Based on real examples you will learn how you can implement and improve your Quality Reviews and use them more efficiently.
Use this opportunity to discuss the challenges with your colleagues and the speakers and learn how you can work successfully with these useful tools.
In times of permanent change, increasing complexity and pressure for permanent improvement, it becomes more and more important to meet internal and external GMP requirements and expectations while keeping an eye on the economic and operational situation. It is of utmost importance to collect and evaluate the right data, to define correct and efficient actions and to control their implementation.
Both parts of the EU-GMP Guideline require the Product Quality Review (PQR). The aim of this requirement is to verify
the consistency and appropriateness of the existing process,
the adequacy of current specifications for starting material and finished product
and to identify product and process improvements.
The FDA 21CFR 211 requires an Annual Product Review (APR) to evaluate annually the quality standards of each drug product.
Quality Reviews will help you with this approach and are necessary and compulsory quality management tools.
All relevant guidance do also consider a Management Review to be an appropriate instrument to assess adequacy and effectiveness of quality systems.
All these different reviews could result in a tremendous work load or they can be performed in an efficient way with useful results – depending on how they are organised. Therefore it is very important to understand the
requirements and the idea behind it and to see how these tools can be used more efficiently.
This Education Course is designed for managers, supervisors and all other staff members in the pharmaceutical
industry who are involved in preparing and compiling Quality Reviews.
an example for a PQR SOP with Annexes
an example for a Management Review SOP
real PQR examples
extracts from real Management Reviews
Quality Reviews in the Context of FDA, EU and ICH
Requirements and Expectations
ICH Q10 and FDA Quality System Guide
The role of ICH Q9
Harmonisation and ISO 9001:2008
The role of the Qualified Person
Are the requirements the same for APIs & drug products?
Quality Review Management
Reviews of individual Quality Systems (Deviations, Complaints, Changes…)
Quality Management Review
Scope, participants, and frequency
Planning and execution
Content, results, and actions
PQR and APR
How to combine PQR and APR in an efficient way
Well-proven PQR/APR designs
Interface to Regulatory Affairs
Certainties (PQR/APR in Custom Manufacturing, how to deal with limited numbers of batches …)
Set up of efficient PQRs and APRs
How to profit from existing QA Systems in
PQR/APR and vice versa
Ongoing data collection
The Application of statistical Tools in Data Review
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?
Documenting the outcomes; are we in control?
Quality Reviews from an Inspector’s View
Regulatory frame for EU-PQR
Technical terms and aims of EU-PQR
Critical technical terms of EU-PQR
Comparison EU-PQR and US-APQR (Annual Product Quality Review)
Practical implementation and inspection
PQR and contract manufacturing
Quality Reviews in Contract Manufacturing
Customer QMRs - content, scope, frequency, organisation
Interface with Business Management Reviews
Assessment of data, trending and decision making
„Face to Face“ or telecon?
Workshop: Evaluation of given PQR Examples
Evaluate with other delegates the content and lay-out
of given PQR examples and discuss it with the speakers
What is useful?
What is ambiguous?
What could be improved?
Workshop: What are the data telling us?
A step wise case study on analysing and interpreting process performance data