Statistics in clinical trials.

lstat2330  2024-2025  Louvain-la-Neuve

Statistics in clinical trials.
5.00 credits
22.5 h + 7.5 h
Q2
Language
French
Prerequisites
Concepts and tools equivalent to those taught in teaching units
LSTAT2014Eléments de probabilités et de statistique mathématique
LSTAT2120Linear models
Main themes
The following topics will be discussed: - International guidelines in clinical trials. - Phase 1: pharmacokinetics and pharmacodynamics. - Phase 1: dose determination: the continual reassessment method. - Phases 2 & 3: hypothesis tests in efficacy, superiority or equivalence trials. - Phases 2 & 3: power and sample size computation, randomisation and blinding. Application to sequential trials. - Phases 2 & 3: cross-over and factorial designs. - Phase 4: pharmacovigilance. Rare events and risk factors. - Reporting in clinical trials.
Learning outcomes

At the end of this learning unit, the student is able to :

1 Objectives The goal of this course is to propose a broad overview of the statistical aspects of phase 1, 2, 3 and 4 clinical trials.
 
Content
The following topics will be discussed: - International guidelines in clinical trials. - Phase 1: pharmacokinetics and pharmacodynamics. - Phase 1: dose determination: the continual reassessment method. - Phases 2 & 3: hypothesis tests in efficacy, superiority or equivalence trials. - Phases 2 & 3: power and sample size computation, randomisation and blinding. Application to sequential trials. - Phases 2 & 3: cross-over and factorial designs. - Phase 4: pharmacovigilance. Rare events and risk factors. - Reporting in clinical trials.
Teaching methods
The course consists of lectures and discussion of documents distributed during the course.
Practical works are also organised. They aim to: - deepen concepts introduced during the course, - analyse real data using tools presented during the course.
Depending on the evolution of the situation, the course will be given either in presential or remotely.
Evaluation methods
Closed-book written exam. 
Depending on the evolution of the situation, the written exam could be replaced by a closed-book oral exam organised remotely. 
Other information
Prerequisites: Bases of probability and descriptive and inferential statistics, basic knowledge of SAS and R.
Online resources
All necessary resources will be made available via Moodle.
Bibliography
Redmond, C. K. and Colton T. (2001), Biostatistics ub Clinical Trials, Wiley.
Fleiss J. (1986), The Design and Analysis of Clinical Experiments. Wiley.
Teaching materials
  • transparents sur moodle
Faculty or entity


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Biomedicine

Master [120] in Biomedical Engineering

Master [120] in Statistics: Biostatistics

Master [60] in Biomedicine

Master [120] in Mathematics

Master [120] in Statistics: General

Master [120] in Chemistry and Bioindustries

Master [120] in Computer Science and Engineering

Master [120] in Computer Science

Approfondissement en statistique et sciences des données

Master [120] in Mathematical Engineering

Mineure en statistique et science des données

Minor in Statistics, Actuarial Sciences and Data Sciences

Certificat d'université : Statistique et science des données (15/30 crédits)

Master [120] in Agricultural Bioengineering