Category: Courses

The last iteration of this course took place on 9th and 10th of September 2025 at the Faculty of Pharmaceutical Sciences, with a new iteration is on the way in 2026!

COURSE OVERVIEW

The DOE training is hands-on and designed for individuals who want to actively engage in Experimental Design and gain a better understanding of the statistical analysis of experimental data. The course emphasizes the Optimal Design of Experiments, matching the experimental design to the problem while considering all experimental boundary conditions and constraints. Optimal DOE is computer-aided, meaning experiment runs and regression models are generated by computer algorithms; the software package used is JMP. The topics are illustrated through case studies and examples from industrial R&D, making the training particularly relevant for professionals in that field.

The course is divided into two modules, each lasting one full day. The basic module begins by covering the necessary theory, including basic training in linear multiple regression analysis for analyzing experimental data and establishing statistical process models needed for parameter screening and optimization. Additionally, the JMP software package will be introduced, and simple cases will be reviewed to describe the basic DOE approach. The advanced module covers more complex examples with specific experimental conditions. In each of the case studies, the goal is to improve the performance of a process or product through efficient exploration and optimization.

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Target audience

The target audience is professionals or students in chemical, pharmaceutical & healthcare sciences and engineering.

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COURSE PROGRAMME

A detailed overview of the different modules can be found in the following document.

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Registrations are open for this course, please follow the ‘REGISTER HERE’ link above. If you have any questions please email Mark Gontsarik (mark.gontsarik@ugent.be).

The last iteration of this course took place from 17th to 18th of June 2025 at the Faculty of Pharmaceutical Sciences, with a new iteration is on the way in 2026!

COURSE OVERVIEW

Interested in expanding your knowledge of Good Automated Manufacturing Practice (GAMP), Computerized System Validation, Regulations, and more? Experts from QbD Group will be instructing a 2-day training that will do exactly that. Check the information on the course below to decide if it suits your needs!

Production systems for the pharmaceutical and food industries have to comply with ever-stricter legislation. This training not only offers you theoretical knowledge of the basic aspects of GAMP – with a focus on the detailed life cycle – but also offers multiple practical exercises.

Additionally, a test will be provided so that you can check if you can apply your gained knowledge.The course begins with an introduction to GAMP principles and gradually builds to more complex examples and exercises.

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Target Audience

The target audience are professionals or students in chemical, pharmaceutical & healthcare sciences and engineering.

• No prior knowledge needed
• Practical learning approach
• Ideal for more in-depth practitioners, who want to get more examples and use cases included as part of the training

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Course has a 2-day programme:

Day 1

The following will be addressed:

Introduction to GAMP

Detailed Lifecycle

Regulations (21 Cfr part 11; Annex 11)

Extended Exercises on Validation, Specifications, Risk Assessment

Day 2

The following will be addressed:

Detailed Lifecycle and Verification Reporting

Operational Phase

Extended Exercises on Test Execution and Report, Validation, Requirements Matrix

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COURSE PROGRAMME

An overview of the course programme can be found in the following document.

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Registrations are open for this course, please follow the ‘REGISTER HERE’ link above. If you have any questions please email Mark Gontsarik (mark.gontsarik@ugent.be).

The last iteration of this course took place from 7th to 9th of May 2025 at the Faculty of Pharmaceutical Sciences, with a new iteration is on the way in 2026!

COURSE OVERVIEW

The Sustainable Systems Engineering (STEN) group offers a comprehensive training programme in Sustainability and Life Cycle Assessment (LCA), with a focus on the pharmaceutical industry. The programme consists of three modules: foundational concepts, practical skills, and industry-specific applications.

The foundational module covers principles of sustainability assessment and the LCA methodology. The practical module provides hands-on experience with LCA software, while the advanced module focuses on applying LCA in the pharmaceutical sector, including case studies and modeling challenges. Through lectures, case studies, and interactive sessions, participants gain essential knowledge and skills to perform sustainability assessments, with an emphasis on practical applications and critical thinking about sustainability in the pharmaceutical field. Moreover, practical expertise in the LCA process empowers decision-makers to fully comprehend the insights derived from the analysis, enabling them to make more informed and sustainable choices.

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Target Audience

This training is ideal for professionals, researchers, and PhD students in pharma, as well as for environmental sciences, engineering, and related fields who wish to enhance their understanding and application of sustainability assessment methodologies

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Course has a 3-day programme, split into 3 modules:

Module 1: Theoretical framework of Life Cycle Assessment (1 day)
Module 2: Practical case studies (1 day)
Module 3: Advanced module on LCA in pharma sector (1 day)

MODULE 1: Theoretical framework of Life Cycle Assessment

The following will be addressed:

Introduction to Sustainability and Life Cycle Thinking

Integrating environmental, social, and economic aspects: LCSA and S-LCA

Principles and framework of Life Cycle Assessment (ISO 14040 series)

Goal and Scope in LCA, Life Cycle Inventory, Life Cycle Assessment, and Interpretation

MODULE 2: Practical case studies

The following will be addressed:

LCA software tools

Introduction to specialized software: OpenLCA

Use and explanation of the different databases

Practical case studies in OpenLCA

Analyzing and interpreting results

MODULE 3: Advanced module on LCA in pharma sector

The following will be addressed:

Green Chemistry and process level assessment metrics

Conducting LCA in pharma sector
LCA tailored to pharmaceuticals
Challenges (data collection, methodological choices, accounting for ecotoxicity, etc.)
Concrete case studies

Beyond LCA of classical drug products & environmental sustainability assessment

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COURSE PROGRAMME

An overview of the different modules can be found in the following document.

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Registrations are open for this course, please follow the ‘REGISTER HERE’ link above. If you have any questions please email Mark Gontsarik (mark.gontsarik@ugent.be).

COURSE OVERVIEW

Towards Continuous Lyophilization course provides a comprehensive introduction to pharmaceutical freeze-drying through an engaging mix of theoretical and hands-on training.
This course equips trainees with a solid understanding of the essential principles, covering the entire process from starting materials to the finished product.
This includes:

• formulation aspects
• getting to know the equipment
• learning to understand the first-principles of lyophilization
  • including both heat and mass transfer mechanisms during freeze-drying

After that,  the most important PAT tools which are commonly used in the field will be covered. Additionally, a novel continuous freeze-drying technology will be explored in detail. Finally, tour of the lab will be provided, along with interactive sessions on modeling and data analysis.

By the end of the course, participants will have a solid understanding of the key principles and processes involved in pharmaceutical freeze-drying. They will gain practical knowledge to design and optimize freeze-drying processes, select appropriate PAT tools, and troubleshoot common issues.

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Theoretical

Introduction to Lyophilization

• Fundamentals of freeze-drying
• Detailed overview of the freeze-drying process
• Equipment and components used in freeze-drying

Lyophilization Formulations

• Purpose and composition of freeze-drying formulations
• Critical properties of freeze-dried materials
• Characterization methods for lyophilized products

Modeling the Freeze-Drying Process

• Introduction to modeling
• Modeling of freeze-drying and applications
• Design space for freeze-drying

Process Analytical Technology (PAT) in Freeze-Drying

• Importance of PAT in freeze-drying
• Key PAT tools and their application

Continuous Freeze-Drying

• Advantages and innovations of continuous freeze-drying
• Limitations of traditional batch freeze-drying

Practical

Tour of the CESPE Freeze-Drying Lab

• Batch freeze-dryers
• Continuous freeze-dryers
• Sample characterization lab

Interactive Modelling Session

• Hands-on experience in constructing a design space for freeze-drying

Data Analysis Workshop

• Interpretation and analysis of common freeze-drying data

COURSE PROGRAMME

A detailed overview of the programme can be found in the following document.

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If you are interested in taking this course, please email Mark Gontsarik (mark.gontsarik@ugent.be).

COURSE OVERVIEW

The Spectroscopic Modelling Using Python training is a hands-on course for building custom spectroscopic models using Python. Techniques like NIR and Raman spectroscopy are powerful tools for non-destructively evaluating chemical and physical sample properties, but proper data processing is key to unlocking their full potential.

This course will be given by experts from elegent, a spin-off company from Ghent University offering modelling services for the pharmaceutical and food industries. 

This course covers essential steps for creating reliable models, introducing key Python modules and demonstrating their use through a pharmaceutical manufacturing case study. Participants will gain a thorough understanding of both theoretical concepts and their practical application in Python.

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Target Audience

The target audience is professionals or students in chemical, pharmaceutical & healthcare sciences and engineering.

Please note that a basic understanding of the Python programming language is required. Basic understanding of spectroscopy is recommended.

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COURSE PROGRAMME

A detailed overview of the course can be found in the following document.

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Registrations are open for this course, please follow the ‘REGISTER HERE’ link above. If you have any questions please email Mark Gontsarik (mark.gontsarik@ugent.be).

COURSE OVERVIEW

The Efficient Data Processing training is a hands-on course designed to help participants accelerate their data workflows. Processing large, complex datasets often takes significantly more time than data collection, but this course demonstrates how Python can streamline these tasks for faster analysis and interpretation. This course will be given by experts from elegent, a spin-off company from Ghent University offering modelling services for the pharmaceutical and food industries. 

Through case studies focused on pharmaceutical R&D manufacturing, participants will learn to clean and transform data using Python modules like numpy, pandas, and scikit-learn, along with visualization tools such as matplotlib, seaborn, and plotly. The training integrates theoretical background with practical application, making it especially relevant for scientists and academics in R&D.

By eliminating repetitive tasks, optimizing workflows, and enabling visual analysis of experiments, this course equips participants with tools to enhance efficiency in data processing.

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Target Audience

The target audience is professionals or students in chemical, pharmaceutical & healthcare sciences and engineering.

Please note that a basic understanding of the Python programming language is required.

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COURSE PROGRAMME

A detailed overview of the different modules can be found in the following document.

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Registrations are open for this course, please follow the ‘REGISTER HERE’ link above. If you have any questions please email Mark Gontsarik (mark.gontsarik@ugent.be).

COURSE OVERVIEW

This course focusses on giving a basic introduction about the implementation of PAT tools in the (bio)pharmaceutical industry.
This course is given in an interactive manner (both theoretical and hands-on) and can be divided into two separate modules:

Module 1: Basic course: Introduction to PAT (1-day module)
&
Module 2: Basic data-analysis and modeling (1.5-day module)

Requirements
Basic understanding of spectroscopy and (bio)pharmaceutical processes
&
Basic understanding of coding and programming (python)

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MODULE 1: BASIC COURSE: INTRODUCTION TO PAT

Theoretical

The trainee will get a general introduction to PAT and the common (non-)spectroscopic sensors, learning how, when and where these tools can provide a benefit.

Spectroscopic sensors
&
Non-spectroscopic sensors (Univariate/Multivariate)
&
Hyperspectral imaging
&
PAT in R&D/Process Validation/QbD
&
Regulatory aspects
&
Multivariate data-analysis

Practical

The trainee will get the chance to see how PAT tools can be used/implemented and how this translates in a practical approach to acquire relevant process information.
Some of the tools that will be demonstrated are:

NIR
&
Raman
&
FLIR

Target audience

People with no experience/expertise in the topic
&
People that want a refreshment on the basic principles

MODULE 2: BASIC DATA-ANALYSIS AND MODELING

Theory through practice

Using spectroscopic data, the teacher will go through different aspects of PAT and model development together with the attendee.

General introduction to Python
&
Data preparation and exploration
&
Introduction to modeling
&
Process control based on PAT

Target audience

People with no experience/expertise in the topic
&
People that want a refreshment on the basic principles

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COURSE PROGRAMME

A detailed overview of the different modules can be found in the following document.

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If you are interested in taking this course, please email Mark (mark.gontsarik@ugent.be).