Environmental Monitoring Data Management

Environmental Monitoring Data Management

Barcelona, Spain

Course No 16183


Costs

Non-ECA Members: EUR 1790,--
ECA Members: EUR 1590,--
EU GMP Inspectorates: EUR 895,--
APIC Members (does not include ECA membership): EUR 1690,--

(All prices excl. VAT)

If you have any questions, please contact us:
Tel.: +49 (0)6221 / 84 44 0 E-Mail: info@gmp-compliance.org

Speakers

Dr Raphael Bar, BR Consulting

Michael Schiffer, Novartis Pharma Stein, Switzerland

Objectives

This practical course will first present the basic methodology of evaluating the Environmental Monitoring (EM) data using elementary Statistical Process Control (SPC) tools as well as empirical approaches to set microbial control limits for clean rooms. This course will address the following issues:

  • Overview of controlled rooms classifications, elements of an EM program and present EU and FDA regulations including the recent ISO 14664 changes.
  • How to organize and present an abundant amount of microbial data in meaningful graphs
  • How to draw useful Control Charts with this data, using the software program Minitab®17
  • To understand how action and alert control limits are set
  • How to demonstrate that the environmental microbial monitoring process is under a state of control
  • How to calculate and plot the newly proposed
  • Contamination Recovery Rates in USP Chapter <1116>
  • To detect a trend in the environmental microbial monitoring process
  • How to apply risk assessment in investigations

All above issues will be demonstrated on examples and case studies of microbial counts generated in controlled rooms of manufacturing facilities of sterile products.

Background

Regulatory agencies require from manufacturing companies of pharmaceuticals and biopharmaceuticals, particularly of sterile drug products, to maintain an environmental monitoring program, whereby particulates as well as microorganisms in either air samples (active and passive sampling) or in surfaces (contact plates) are routinely tested and monitored.

Thus, a multitude of environmental microbial data is generated on a routine basis and it is recorded in a manner permitting trend evaluation. But collecting EM data is only the first challenge. The following challenge for the responsible person in quality is charting, analyzing data, setting action and alert limits, interpreting the overall monitoring process behavior, detecting a trend or shift in contamination levels, monitoring excursion rates and contamination recovery rates, while conducting an on-going risk analysis. Therefore, this course is aimed at providing empirical tools for charting and trending EM data.

Target Group

  • Environmental Monitoring personnel in facilities of pharmaceuticals, biopharmaceuticals and medical devices
  • Microbiologists
  • Quality Assurance personnel
  • Regulatory Affairs personnel
  • Production Managers
  • QC Managers

PLEASE NOTE

A laptop with Excel© is needed for the practical exercises. Also, the “Minitab” software must be installed on this computer to solve exercises and generate control charts. You can download a 30 days trial version of thissoftware here:
https://www.minitab.com/en-us/products/minitab/

Programme

Introduction to charting and trending

  • QbD and trending
  • Run Chart vs. Shewhart Control Charts
  • Control charts of grouped data versus of individual data
  • Examples of microbial charts: grouped vs individual counts
  • Variables versus attributes charts
  • Poisson and Binomial control chart
  • Common cause variation vs. Special Cause (Assignable) variation
  • State of control
Overview of Environmental Monitoring: regulations and infra structures
  • Overview of current regulations:
  • Practical aspects of Environmental Monitoring
  • How to set up an structured EM program and gain strong data
  • Risk-based approach
  • Handling of big data amounts
  • EM program examples from Industrial clean rooms
Variability of data
  • Standard deviation of a sample and of population
  • Histogram
  • Standard deviations of the mean range
  • Relation between standard deviation and Range
  • Short-term variation versus global variation
  • Separating the signal from noise
Exercise: Calculation of within-group and global standard deviations

Control Charts of grouped data
  • Plotting Run chart and control chart (Process Behavior Chart)
  • Computation of three-sigma Control limits
  • Control charts of average, range and standard deviation
Brief acquaintance with Minitab 17
  • Basic structure of Minitab software
  • Drawing a Control Chart
Control Charts of individual microbial counts
  • Moving range (mR)
  • Control charts of individual data (XmR)
  • Calculation of control limits
  • The three-way chart
  • Examples of three-way charts
Exercises: Building control charts of microbial counts from passive and active air sampling with Minitab

Contamination Recovery Rates
  • Contamination recovery rates (USP approach <1116>)
  • Plotting recovery rates and excursion rates
  • Limits of rates versus actual values
  • Calculations of contamination recovery rates per USP <1116>
Distribution-free approach
  • Disadvantages of the distribution-based approach
  • Non-parametric percentile as control limit
  • Tolerance intervals limits
  • Shewhart approach for setting control limits
Exercises of percentile determination, plotting of Laney’s charts, Calculations of contamination recovery rates per USP <1116>

Trending Tool applications
  • Trending tool examples from industries
  • Data collection tools
  • Reaction and measures on negative trends
  • Responsibilities
General approach to microbial monitoring
  • Overall strategy for microbial monitoring
  • Plotting Contamination recovery rates
  • Laney’s charts
Exercises: Control charts of microbial counts of active air samples in area Grade B and contact plates in area Grade C; Determining Alert Limits with the methods of percentile and confidence intervals

Investigation and Risk Assessment
  • Case studies of evaluation of EM Data
  • Use of supportive data
Strategy for detecting a trend and for Continuous Improvement
  • Phase 1 and Phase 2 in process monitoring
  • Statistical Control of a process: Is your EM process predictable?
  • Nelson rules
  • Trending and continued process verification
  • Trending for Annual Product Review document
Example of detecting a shift in microbial counts

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