Duration
25h Th, 10h Pr
Number of credits
| Master in biomedicine (120 ECTS) | 3 crédits |
Lecturer
Language(s) of instruction
English language
Organisation and examination
Teaching in the second semester
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
Recent advances in clinical research and multi-OMICs techniques have led to the discovery of a large number of biomarkers. These biomarkers are of major interest for the development of personalized medicine. They are indicators of disease progression, physiological changes or response to treatment. They represent therefore a strategic perspective for new drug development by pharmaceutical industries. However, the path from discovery to full validation of each biomarker remains long, expensive and selective. Only few companion disease markers have so far been approved by federal agencies such as the US Food and Drug Administration (FDA). As a result, some biomarkers remain only described through scientific communications and publications while they never reach their official approval. Nevertheless, they can still be used as biological, pathogenic or treatment response indicators.
This course will provide several tools to learn about the development of robust biomarkers from discovery to validation and to be critical about biomarkers highlighted in the literature.
Learning outcomes of the learning unit
The purposes of this course will be to define the concept of a biomarker and of parameters assessing the validity of a marker as a clinical indicator for the presence or absence of a disease. We will discuss the main recommendations for biomarker evaluation as well as diagnostic performance indices and ROC curves. From multi-OMIC approaches, we will determine the methodology needed to go from the discovery to clinical validation of biomarkers. We will also determine how to quantify the added value of a biomarker or how to integrate biomarkers into a diagnostic approach. These theoretical notions will be illustrated by the description of different biomarkers used in clinical diagnosis or therapeutic efficacy. Finally, we will also determine how to analyze biomarkers highlighted in the literature and what criteria to use to determine the robustness of a potential marker.
Prerequisite knowledge and skills
The student must have basic knowledge in statistics as well as in biochemistry concerning the genome, epigenome, transcriptome and proteome.
Planned learning activities and teaching methods
This lecture will be supported by powerpoint slides illustrating theoretical aspects of biomarkers from their discovery to validation.External speakers will present biomarkers currently used in clinical biology and explain how to transfer a biomarker from research to clinical laboratory.
Journal club: A collective analysis of the same article will be first detailed by all students.
Practical work: An interactive seminar prepared by each student on a biomarker extracted from the literature will enable the student to demonstrate that the biomarker meets criteria as described by STARDs (STAndards for Reporting of Diagnostic Accuracy).
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face course
Additional information:
The course will be given in English as a face-to-face lecture.
Recommended or required readings
Exam(s) in session
Any session
- In-person
written exam ( open-ended questions ) AND oral exam
Other : Presentation of the scientific publication will occur during one of the last lectures
Additional information:
Students competence will be evaluated by passing a written examination on theoretical aspects of biomarkers but also on presentations given by external orators.
Students will also be evaluated on the oral presentation of a scientific publication related to the discovery or the use of biomarkers.
Work placement(s)
Organisational remarks and main changes to the course
The use of a calculator in class will be necessary to assess the robustness of a biomarker in clinical diagnosis.
Contacts
Dominique de Seny
ddeseny@uliege.be