Lab Data Integrity Master Class - Live Online Training
19-21 September 2023
Course No. 21215
Speakers
Dr. Bob McDowall
R.D. McDowall Ltd.
Dr. Markus Dathe
F. Hoffmann-La Roche
Dr. Christopher Burgess
Burgess Analytical Consultancy
All times mentioned are CEST.
Objectives
The objectives of this Laboratory Data Integrity Master Class are:
Identify areas where Data Integrity can be compromised
Provide a methodology to assess your current processes and identify Data Integrity risks that attendees can use in their own laboratories
To take attendees on a journey through the analytical process to identify area of Data Integrity risk and to develop both short-term remediation and, more importantly, long-term Solutions
Move from principles and requirements into Data Integrity best practice scenarios
Note, this Live Online Training assumes that attendees already understand the principles for Laboratory Data Integrity and the contents of regulatory guidance documents as these aspects will not be covered.
Background
Data Integrity has become the major regulatory concern with Regulatory Agencies who have issued several guidances that focus on computerised systems, data governance and Data Integrity audits and investigations. Manual processes are discussed but focus on uncontrolled blank forms and the control measures. The analytical process is not covered in any Data Integrity guidance. This is surprising as sample management and sample preparation are primarily manual, paper based and error prone.
The WHO regulatory guidance document notes: The use of hybrid systems is discouraged Replacement of hybrid systems should be a priority
PIC/S Guidance PI-041, section 5.3.2 states: Manufacturers and analytical laboratories should design and operate a [quality management] system which provides an acceptable state of control based on the data integrity risk, and which is fully documented with supporting rationale.
These guidance documents push laboratories and pharmaceutical companies towards implementing automated systems as technical controls are superior to procedural controls for ensuring Data Integrity.
This Live Online Training will provide attendees with tools for:
Understanding your process
Identifying process risks
Assessing Data Integrity criticality
Developing practical mitigation strategies
Target Group
This Laboratory Data Integrity Master Class is directed at
Managers and scientists from QC and Analytical Development Laboratories
Quality Assurance personnel responsible for Data Integrity
CRO and CMO laboratory and QA personnel
Auditors responsible for laboratory quality and Data Integrity
Technical Requirements
We use WebEx for our live online training courses and webinars. At https://www.gmp-compliance.org/training/online-training-technical-information you will find all the information you need to participate in our trainings and you can check if your system meets the necessary requirements to participate. If the installation of browser extensions is not possible due to your rights in the IT system, please contact your IT department. WebEx is a standard nowadays and the necessary installation is fast and easy.
Structure of the course: presentation / Workshop combinations
Workshop 1: Regulatory Citations – What Would You Do?
Inspection findings can hit everybody – be prepared for Data Integrity
What do the agencies expect: Case Studies from recent citations and appropriate reaction?
What helps, what not?
How to prevent that specific finding? How to fix the issue?
How Poor is your Process? Data Process Mapping and Analysis
More than Data Integrity: the benefits of mapping
Process flow and data flow: strengths and weaknesses
Tools for mapping and the best time to use them
Parts of a complete flowchart (sample process)
Shortcuts to get to the finish more quickly
Priority of risks - create your “quick wins”
Analytical Process 1: Sampling
Importance of sampling in the analytical process
Regulatory requirements for sampling
Sample management procedures and flows to ensure traceability
Is the laboratory sample representative of the batch or lot?
Tools and techniques for sampling
Workshop 2: Sampling and Data Integrity
Case study scenarios for a variety of sampling and sample management activities will be presented for evaluation and critique by groups
The objective of the evaluation is to ensure that scientifically sound methodologies are employed and Data Integrity maintained throughout the sample management procedure
Analytical Process 2: Sample Preparation
Scope of sample preparation in the analytical process
How is sample preparation typically documented?
Data Integrity issues with sample preparation
Ways of improving sample preparation data integrity
Workshop 3: Sample Preparation
Attendees are presented with a sample preparation scenario where Data Integrity issues have been identified during an internal audit
Identify what, if any, short term remediation is required and what would be options for long term solution
How would the long term solutions be justified?
Analytical Process 3: Instrumental Analysis
Scope of instrumental analysis in the analytical process
Risk based strategies for classification for Data Integrity
Criticality and lifecycle of instruments
Role of Audit Trail Review (ATR) in the Instrumental Analysis
What do we expect from the suppliers?
Workshop 4: Instrumental Analysis
Develop risk-based strategies on case studies
Participants are encouraged to present their own examples
Risk identification on examples and ATR implementation
Analytical Process 4: Data Interpretation
Scope of data evaluation in the analytical process
‘Fitness for purpose’ of analytical data
Acceptance criteria and procedure mapping
Statistical tools for the detection of imprecision and bias
Quality Metrics for Laboratory Analysis
Regulatory expectation for Data Integrity metrics
Benefits and limitations in Data Integrity metrics
Example metrics for governance
Example metrics for operations
Finding ideas for new metrics
Forensic Auditing of Laboratory Data
Uncovering file deletions - what is forensic auditing?
When do you use forensic auditing?
Tools for forensic auditing
Pros and cons of forensic auditing
Workshop 5: Data Interpretation
Case study scenarios
The objective of the evaluation is to determine if scientifically sound methodologies are employed and Data Integrity maintained throughout the data evaluation procedure
Analytical Process 5: Calculation of the Reportable Result
Scope of calculating the reportable result in the analytical process
Automation vs manual intervention in calculations
Benefits of converting to auto-integration
Importing factors from other systems: benefits and risks
Workshop 6: Calculation of the Reportable Result
Procedural controls for calculations (chromatography SOP)
Testing into compliance and other practices to avoid
Use of metrics to provide quality oversight of calculations
Analytical Process 6: Second Person Review
Scope of a second person review in the analytical process
Electronic, hybrid and paper-based processes
Options for Second Person Review
What do the inspectors expect?
Role of data and records definition
Workshop 7: Second Person Review
Data are not records - find the difference. Explain it! Defend it!
Falsification detection and prevention
Where and how is Audit Trail Review performed
Short term remediation and long term solutions for
paper-based and hybrid systems
Developing and Maintaining an Open Culture in a Regulated Laboratory
Defining “culture” in a practical way
Opportunity, means and motive in the lab
Getting People to cheat is easy!
What you said versus what they heard
Changing your Organization’s Perspective
Workshop 8: Pulling it all Together
Attendees will be presented with a laboratory scenario containing Data Integrity issues.
Using the principles learnt in the course, participants must identify the Data Integrity issues and propose long term solutions
What would be the order of implementing your options and why?
This course is part of the GMP Certification Programme "ECA Certified Data Integrity Manager" Learn more
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