Dr Christian Palmes
Bayer AG
Referent:innen
Dr Raluca Ilinca Schmitt
Bayer AG
Case Studies: Outlier Detection in Tablet Weights · Stability Testing (ICH Q1) · HPLC System Validation · pH Control in Continuous Production · Filtration Rate Optimization · Verification of Process Improvements
Prerequisites: Each participant should bring a laptop with a current version of Excel and Minitab installed. A time-limited free trial of Minitab is available from https://www.minitab.com. This program should be downloaded a few days before the start of the course and verified to work properly on the Laptop.
Remark: The number of participants is strictly limited due to the workshop Format.
Zielgruppe
This course is ideal for employees in development, quality control labs, process engineering, quality assurance /quality management, production, and validation departments who are currently applying or plan to apply quality statistics methods in their work. It is also suitable for GMP auditors, inspectors, and validation personnel who interact with statistical data or evaluate results in the context of quality and process performance.
Requirements: Basic math understanding and a genuine interest in understanding and applying quality statistics in practice.
Requirements: Basic math understanding and a genuine interest in understanding and applying quality statistics in practice.
Zielsetzung
Our quality statistics course offers a clear, hands-on introduction to key statistical methods used in process and quality improvement, with a strong focus on practical application in a pharmaceutical context. The course features six case studies presented in a click-through manner.
Statistical concepts are taught at a practical level to ensure participants understand the methods, interpret Minitab outputs correctly, and draw sound, data-driven conclusions.
Statistical concepts are taught at a practical level to ensure participants understand the methods, interpret Minitab outputs correctly, and draw sound, data-driven conclusions.
- Day 1: Introduction to Statistics and Minitab, Correlation and Regression Analysis, Hypothesis Testing
- Day 2: Measurement System Analysis, Gage R&R, Statistical Process Control and Process Capability, Design of Experiments
This training enables participants to enhance process understanding, justify parameter selections scientifically, optimize analytical workflows, and maintain robust quality throughout the product LifeCycle.
Background
Quality statistics is a fundamental discipline in GMP like Quality by Design (QbD) and continuous improvement frameworks such as Six Sigma. It provides the analytical foundation for understanding, monitoring, and improving process performance and product quality. Statistical methods enable organizations to make data-driven decisions, reduce variability, and keep processes capable of meeting specifications.
In practice, quality statistics cover a broad range of methods, from descriptive and inferential statistics to advanced tools such as control charts, process capability analysis, measurement system analysis, regression modeling, and design of experiments. These methods are essential for identifying sources of variation, distinguishing between common and special causes, and quantifying the impact of process factors on critical quality attributes.
The application of quality statistics spans the product lifecycle – from development to manufacturing and continuous improvement. Its systematic use supports regulatory expectations for scientific and risk-based process understanding as described in ICH Q8, 9, 10, 11 and 14, forming a cornerstone of data-driven quality management in the pharmaceutical Industry.
Quality statistics is a fundamental discipline in GMP like Quality by Design (QbD) and continuous improvement frameworks such as Six Sigma. It provides the analytical foundation for understanding, monitoring, and improving process performance and product quality. Statistical methods enable organizations to make data-driven decisions, reduce variability, and keep processes capable of meeting specifications.
In practice, quality statistics cover a broad range of methods, from descriptive and inferential statistics to advanced tools such as control charts, process capability analysis, measurement system analysis, regression modeling, and design of experiments. These methods are essential for identifying sources of variation, distinguishing between common and special causes, and quantifying the impact of process factors on critical quality attributes.
The application of quality statistics spans the product lifecycle – from development to manufacturing and continuous improvement. Its systematic use supports regulatory expectations for scientific and risk-based process understanding as described in ICH Q8, 9, 10, 11 and 14, forming a cornerstone of data-driven quality management in the pharmaceutical Industry.
Programm
Day 1
Welcome and Setting Up the Scene
Welcome and Setting Up the Scene
- A short introduction round
- Objectives of the Training
Introduction to Statistics
- Population and sample
- Sources of variation
- Statistical measures (mean, median, quantile, range, variance, standard deviation)
- Probability (binomial distribution, normal distribution, skewness, z-values, independence)
Introduction to Minitab
- Graphical user interface: Project, worksheets, data types
- Graph menu: Histograms, scatterplots, customize plots
- Stat menu: Descriptive and inferential statistics
- Minitab help
Correlation and Regression Analysis
- Causality vs. correlation, spurious correlation
- Correlation coefficient: Definition, interpretation and visualization
- Regression Analysis: Method of least squares and R-2
Hypothesis Testing
- Null hypothesis (H0) vs. alternative hypothesis (H1)
- Type I and II errors, significance, power, p-value, confidence interval
- Sample size calculation
- t-test (mean), Grubbs-test (outlier) and Anderson-Darling test (normality)
Exercise: Hands-On Quality Statistics
- Case Study 1: Outlier detection in tablet weight control
- Case Study 2: Stability testing following ICH Q1 (regression analysis)
- Case Study 3: Statistical verification of process improvement (hypothesis testing)
Day 2
Measurement System Analysis and Gage R&R
Measurement System Analysis and Gage R&R
- Type 1 Gage Study
- Gage Linearity and Bias Study
- Crossed R&R study (random effects models)
Statistical Process Control and Process Capability
- Control charts: Xbar-S and I-MR chart, Nelson rules
- Process capability and performance (Cpk, Ppk)
- Calculation of out-of-spec probabilities
Design of Experiments
- DoE vs. OFAT (one factor at a time)
- Empirical models and prediction: Main effects and interaction effects
- Fisher’s key DoE principles: Randomization, replication and blocking
- Fractional factorial 2-level designs and design Resolution
Exercise: Hands-On Quality Statistics
- Case Study 4: HPLC system validation (Gage R&R)
- Case Study 5: pH control in continuous manufacturing (Statistical Process Control)
- Case Study 6: Filtration rate optimization (Design of Experiments)
Weitere Informationen
Venue
Barceló Hotel Hamburg
Ferdinandstrasse 15
20095 Hamburg
Tel. +49 (0) 40 22 63 62 0
Fax +49 (0)40 22 63 62 999
hamburg@barcelo.com
Barceló Hotel Hamburg
Ferdinandstrasse 15
20095 Hamburg
Tel. +49 (0) 40 22 63 62 0
Fax +49 (0)40 22 63 62 999
hamburg@barcelo.com
Accommodation
CONCEPT HEIDELBERG has reserved a limited number of rooms in the conference hotel. You will receive a room reservation form/POG when you have registered for the course. Reservation should be made directly with the hotel. Early reservation is recommended.
CONCEPT HEIDELBERG has reserved a limited number of rooms in the conference hotel. You will receive a room reservation form/POG when you have registered for the course. Reservation should be made directly with the hotel. Early reservation is recommended.
Social Event
On 19 May 2026, you are cordially invited to a social event. This is an excellent opportunity to share your experiences with colleagues from other companies in a relaxed atmosphere.
On 19 May 2026, you are cordially invited to a social event. This is an excellent opportunity to share your experiences with colleagues from other companies in a relaxed atmosphere.
Fees (per delegate, plus VAT)
ECA-Member: € 1890,-
Non ECA Member: € 2090,-
EU/GMP Inspectorates: € 1045,-
APIC Member Discount: € 1990,-
The conference fee is payable in advance after receipt of invoice and includes dinner on the first day, lunch on both days and all refreshments.
VAT is reclaimable.
ECA-Member: € 1890,-
Non ECA Member: € 2090,-
EU/GMP Inspectorates: € 1045,-
APIC Member Discount: € 1990,-
The conference fee is payable in advance after receipt of invoice and includes dinner on the first day, lunch on both days and all refreshments.
VAT is reclaimable.
Please Note:
The number of participants is strictly limited due to the workshop format.
The number of participants is strictly limited due to the workshop format.
Conference language
The official conference language will be English.
The official conference language will be English.
Presentations/Certificate
The presentations for this event will be available for you to download and print before and after the event. Please note that no printed materials will be handed out on site and that there will not be any opportunity to print the presentations on site.
After the event, you will automatically receive your certificate of participation.
Questions regarding content:
Mr Sven Pommeranz +49 (0) 6221 84 44 47,pommeranz@concept-heidelberg.de.
Questions regarding organisation:
Ms Manuela Luckhaupt, +49 (0) 6221 84 44 66, luckhaupt@concept-heidelberg.de.
Datum & Uhrzeiten
Tue, 19 May 2026, 09.00 - 17.15 h
Wed, 20 May 2026, 08.30 - 17.00 h
All times mentioned are CEST.
Wed, 20 May 2026, 08.30 - 17.00 h
All times mentioned are CEST.
Teilnahmegebühr
| ECA-Member*: | € 1890,- |
| Non ECA Member*: | € 2090,- |
| EU/GMP Inspectorates*: | € 1045,- |
| APIC Member Discount*: | € 1990,- |
Alle Preise zzgl. MwSt. Wichtige Hinweise zur Umsatzsteuer.
* auch unkompliziert per Kreditkarte bezahlbar
Aufzeichnung/weitere Termine nicht verfügbar
Aufzeichnung/weitere Termine nicht verfügbar
This course is part of the GMP Certification Programme "ECA Certified Validation Manager"
Haben Sie noch Fragen?
Wir stehen Ihnen für weitere Auskünfte gerne zur Verfügung.
E-Mail: info@concept-heidelberg.de
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