Environmental Monitoring Data - Trending, Analysis and AI - Live Online Training
From traditional SPC to Artificial Intelligence (AI)
17-19 November 2026
Course No. 22730
Regulations, Infra Structure and Efficient EM Programmes | From Charting and Trending to Data Variability and Risk Management | Automation, Digitalisation and Use of Artifical Intelligence
Target Group
Environmental Monitoring personnel in facilities of pharmaceuticals, biopharmaceuticals and medical devices
Microbiologists
Quality Assurance / Regulatory Affairs personnel
Production Managers / QC Managers
Senior Management
Objectives
This Live Online Training will 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
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.
A prior knowledge of control charts is an advantage.
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 behaviour, detecting a trend or shift in contamination levels, monitoring excursion rates and contamination recovery rates, while conducting an ongoing risk analysis. According to the recent revision of EU Annex 1 (Draft 2020/2021), results from monitoring should be considered when reviewing batch documentation for finished product release. Therefore, this course is aimed at providing empirical tools for charting and trending EM data.
Programme
Environmental Monitoring: Introduction, Regulations and Practical Aspects
Overview of current regulations, Draft EU Annex 1
Practical aspects of environmental monitoring
How to set up a structured EM program to gain strong data and handle big data amounts
Industry best practices
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
Overview of Control Charts of Attributes (Microbial Counts)
Demonstration of contamination recovery rates per USP <1116>
Overview of Control Charts of Individual Microbial Counts
Moving range (mR)
Control charts of individual data (XmR)
Calculation of control limits
Trending Tool Applications
Trending tool examples from industries
Data collection tools
Investigation and risk assessment for negative trends
Overview 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
The three-way chart
Examples of three-way charts
Demonstration of Building Control Charts of Real-Life Microbial Counts in Classified Rooms (with StatGraphics®)
Interactive Case Studies In this case study, Michael Schiffer will deepen and discuss in detail the contents of previous lectures using practical examples.
How to Minimize False Alarms in Environmental Monitoring Data Part1: Adjusting SPC rules to pharmaceutical process data
Why traditional SPC rules are rarely met for microbial data
State of control versus state of statistical control
Practical SPC rules
Part 2: Detecting variation and trends in control charts
Examples: Control charts of real-life EM data
Data Strategies and Environmental Monitoring – MODA System
Data requirements for the evaluation and selection of an electronic system
How to maximise the value of your data
Trend analysis tools and tips
Setting alert and action limits
Data integrity issues
Data Management and Digitalization by Novatek International
Digitalization of environmental monitoring processes
Global EM
Risk-based environmental monitoring
Addressing EU cGMP / Annex 1 /data integrity requirements
Smart trending and reporting using AI
Strategy for Monitoring a State of Control under Ongoing Process Verification Plan
Phase 1 and Phase 2 in process monitoring
Is your EM process under a state of control?
Trending and continued process verification
Real-time continuous LIF monitoring of viable and inert particles
Leveraging AI for Smarter Cleanroom Data Analysis – Introduction and Practical Applications
Introduction to AI in cleanroom operations, environmental monitoring, and aseptic processing.
How AI enhances trend analysis, real-time data interpretation, and contamination prediction.
Practical applications of AI in data-driven risk assessment, process optimization, and quality control.
Live Demo & Case Studies – AI in Microbiological Data Analysis
Step-by-step walkthrough of AI-driven microbial trend analysis.
How AI detects variations, predicts contamination risks, and reduces false alarms.
Interactive discussion on applying AI solutions in participants’ cleanroom environments.
The Future of AI in Cleanroom Monitoring – Tools, Implementation Strategies & What’s Next
Overview of AI-powered cleanroom monitoring solutions and emerging technologies.
How to integrate AI into existing environmental monitoring programs without disrupting compliance.
Future trends: AI + IoT for continuous monitoring, predictive contamination control, and process automation.
Final discussion: What’s next for AI in regulatory compliance and GMP environments?
Further Information
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 events 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.
Fees (per delegate plus VAT) ECA Members € 2,290 APIC Members € 2,390 Non-ECA Members € 2,490 EU GMP Inspectorates € 1,245 The conference fee is payable in advance after receipt of invoice.
Presentations/Certificate The presentations will be made available to you prior to the Live Online Training as PDF files. After the event, you will automatically receive your certificate of participation.
Conference language The official conference language will be English.
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