Lab Data Integrity Conference

18-19 October 2017

Barcelona, Spain

Course No 16028

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Speakers

Gunnar Danielson, Mettler Toledo GmbH, Switzerland

Dr Markus Dathe, F. Hoffmann-La Roche, Switzerland

Travis Frick, GlaxoSmithKline Vaccines, Belgium

Dr Bob McDowall, ECA Data Integrity Working Group, R D McDowall Ltd

Dr Danilo Neri, PQE, Italy

Dr Siegfried Schmitt, PAREXEL International, UK

Dr Franz Schönfeld, GMP Inspector, Government of Upper Franconia, Germany

Objectives

Data integrity in the GMP analytical laboratory continues to be THE major global topic amongst both regulatory agencies, pharmaceutical companies and suppliers. Although the headlines are still gabbed by warning letters and non-compliances involving cases of falsification and fraud from a minority of organisations this is the tip of the iceberg. The majority of data integrity issues seen in warning letters and 483 observations are still due to poor data management practices where records created are not adequately documented, electronic records that are poorly protected or not protected at all and / or there is still a reliance on paper printouts from computerised systems as raw data.

Since 2015 there has been a tsunami of regulatory guidance and advice from MHRA, FDA, WHO, PIC/S, EMA and even the Chinese FDA. In addition, ECA have issued a draft guidance for comment and the April 2017 release of the GAMP guidance on Records and Data Integrity that is a companion to GAMP 5. Do these guidances say the same things or are there contradictions? How should laboratories and suppliers respond to the WHO suggestion that „replacement of
hybrid systems should be a priority“?

The second Laboratory Data Integrity conference is designed to present, from a practical
perspective, the following areas:

Laboratory data integrity where are we now?
Regulator talk
Review of the GAMP Guide on Records and Data Integrity
Scope of the Second person review
Instruments with integrated software – quo vadis?
Data integrity audits
Data integrity from research to manufacturing
Developing metrics for laboratory data integrity
Using data flow mapping to identify data integrity concerns
Instrument Supplier’s perspective of data integrity

In addition, there will be a Discussion Forum at the end of day 1 where all delegates will have the opportunity to ask specific questions to benefit from the speakers’ experiences in this field.

Target Group

The conference is intended for the technical and managerial personnel who deal with data integrity issues including analytical development and quality control analytical laboratories in pharmaceutical companies, contract research and manufacturing organisations. QA personnel responsible for quality oversight of data integrity work will also find the conference invaluable.

Programme

Introduction – Laboratory Data Integrity: Where Are We Now?

Overview of data integrity since October 2016 conference
Warning letter update
Regulatory guidance update
GAMP Guide on Records and Data Integrity

Regulatory Requirements and Expectations

Legal requirements, European and international guidelines and guidance documents
Case study: data integrity in the quality control lab and how it relates to the continuous
improvement process
Inspection findings

Mitigating Data Integrity Risks in Pharmaceutical Manufacturing

What is “data integrity”?
What is “metadata”?
What primary data integrity risks are associated with data systems (paper, electronic,
and hybrid)? How can these risks be mitigated?
How can manipulation of electronic records be detected?
What are the requirements of/best practices for validating a computer system/
electronic records?
What are the most important things for companies to do or recognize regarding
manufacturing data integrity?

Metrics for Laboratory Data Integrity

What are metrics?
Metrics will change throughout a data integrity programme: assessment and
remediation phases
Suggested metrics for routine chemical analysis

Case Study: Data Integrity from Research to Manufacturing: Balancing Analytical
Science and Regulatory Compliance

Patient safety, freedom of research and speed to market: the dilemma of development
DI in the development lifecycle – phase appropriate requirements
Is it just regulations or common sense?
The TITO principle and how to avoid it
Benefits of data integrity measures
Data ownership as a key prerequisite for DI compliance

Instruments with Integrated Software and Data Integrity

The new USP <1058> and the Lab Instrument classes
The class B and Data Integrity
The hubris of hybrids – paper complicates everything!
Criticality: how critical is critical?

Scope and Detail of a Second Person Review

US and EU regulatory requirements for second person review
Responsibilities and SOP for the review
Key requirement for the review: objective evidence
Paper record review
Hybrid system review problems
Electronic system set up – is the software up to the job?
Assays where second person review can be problematic

Using Data Flow Mapping to Identify Data Integrity Concerns

What is ‘Data Flow Mapping’?
How to execute ‘Data Flow Mapping’?
The benefits of ‘Data Flow Mapping’
Examples of ‘Data Flow Mapping’ detecting data integrity concerns

Data Integrity: An Instrument Suppliers Perspective

The extent to which all data are complete, consistent and accurate throughout the
data lifecycle“ – the lifecycle starts at the beginning – at the source of the data
It‘s about the controls throughout the whole process
Common misconceptions of benchtop instruments
Start with correct data – finish well.

Data Integrity Audits – An Analytical Perspective

What to expect when preparing an audit for data integrity
The analytical laboratory - from the clinical setting to the certified laboratory
(50 shades of grey?)
How to plan the audit (access to site, systems and records; length of audit, location
of audit, etc.)
Performing the audit (access to staff, access to systems and records - let the hunt begin!)
From black holes to compliant records - where to draw the line?
The audit report - explaining the unexplainable, the difficult and the obvious

Review of the GAMP Guide: Records and Data Integrity

Overview of the new guide
Review and Discussion of key sections of the Guide: Data governance framework
Data life cycle, Risk management, Management, development and operation appendices

Laboratory Control Systems: how to prevent Data Integrity violations

Strongly enforced Data Integrity Requirements in the latest 3 years by almost every
Regulated Agency in the latest guidances issued by MHRA, WHO, FDA and recently
by PIC/S.
Particularly importance in the laboratory environment where data created within the
analytical processes are relied upon to ensure the Product Quality
Requirement to implement every control measure oriented to prevent Data Integrity
violation either through automatic functionalities and interim manual procedures
Need to routinely monitor the effectiveness of these measures in pharmaceutical
companies

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