2023-2024 / GBIO0014-2

In silico medicine


30h Th, 30h Pr

Number of credits

 Master of Science (MSc) in Biomedical Engineering5 crédits 


Thomas Desaive

Language(s) of instruction

French language

Organisation and examination

Teaching in the second semester


Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

The course is an introduction to in silico medicine, namely the use of mathematical modeling and numerical simulations in the understanding, diagnosis, treatment or prevention of diseases . It is divided in two parts. The first part will provide the fundamental principles of good modeling methodology applied to physiology and medicine. The second part will present case-studies relating concepts to clinical applications.

More specically, the course will cover the following topics.

Part I: Introduction

  • Physiological complexity and the need for models
  • Models and the modeling process
  • Modeling the data and the system
  • Model identification
  • Model verification and validation
Part II : Applications

  • Cardiovascular system (arterial and cardiac)
  • Respiratory system
  • Endocrine system (glucose-insulin models)
  • Drug delivery (pharmacokinetic and pharmacodynamic modeling)
  • Medical devices

Learning outcomes of the learning unit

This course aims to provide the student with insight into how mathematical models and numerical simulations can be applied to physiology and medicine.

The student will learn how to develop good modeling methodologies. He will understand how models allow to explore dynamic effects of pathophysiological processes. From numerous examples from different physiological systems, the student will also learn how mathematical models enable the estimation of physiological parameters that are nor directly measurable, which can be important in the development of new diagnostic strategies.

This course contributes to the learning outcomes I.1, I.2, II.1, II.2, III.1, III.2, IV.1, V.1, V.2, VI.2, VII.4, VII.5 of the MSc in biomedical engineering.

Prerequisite knowledge and skills

  • Mathematical background of a bachelor in engineering
  • Notions of signal and system analysis
  • Notions of physiology

Planned learning activities and teaching methods

  • Lectures on theoretical concepts
  • Small group project

Mode of delivery (face to face, distance learning, hybrid learning)

Face-to-face course

Additional information:

Lectures will taught face-to-face. Project will be carried out remotely.

Recommended or required readings

Slides (PPT) are available

Reference: Cobelli, C., & Carson, E. (2019). Introduction to modeling in physiology and medicine (2nd edition). Academic Press.

Exam(s) in session

Any session

- In-person

written exam ( open-ended questions )

Written work / report

Additional information:

The evaluation is divided as follows:

  • Written exam (60%)
  • Project (40%)
The project is mandatory to access the exam.


Work placement(s)

Organisational remarks and main changes to the course


Thomas Desaive

Association of one or more MOOCs

There is no MOOC associated with this course.