Course Overview

This course presents the theory and methods of design of experiment
approach and assess the big data treatment with supervised and non
supervised methods. It gives access to the bases of quality by design
in pharmaceutical industry.

Learning Achievement

Competence

Course prerequisites

- Hold a bachelor or master of pharmacy or analytical chemistry with
bases in analytical Chemistry and statistics 
- English level: B2 
- Computer with excel application and internet connection

Grading Philosophy

Module 1: 
- Oral presentation of a scientific article about QbD  /   15 min 
/   1/3 weight of overall mark 

Modules 2 & 3: 

- Written exam: theoretical aspects and application of design of
experiments; data analysis  /  1h30  / 1/3 weight of overall mark
 Module 4: 

- Continuous Assessment during the practical class (QCM, QROC, …) 
/  1h (4*15min)  /  1/3 weight of overall mark  RULES AND
PROTOCOL FOR FAILURE

- Overall mark > 10/20  - Module mark > 7.5/20

Course schedule

Module 1: Quality by design 
- Reminder of quality assurance and introduction of QbD in
pharmaceutical industry  - Methodology of QbD applied to analytical
method development  - Quality of mathematical models and
statistics  - Establishment of a design space and assessment by
quality risk management with Monte Carlo studies  Module 2: Design of
experiments 

- Introduction (multivariate / monovariate approach, definition of
different notions, mathematical models)  - Two-level factorial
designs  - Two-level fractional factorial designs   - Other
screening designs  - Order of experiments and notion of Blocking 
- Response Surface Designs 7 Module 3: Data Analysis 

- Identify methods for data analysis and processing  - Principle of
classification and clustering  - Identify the different methods for
classifying data (distance)  - Build a classification step by step 
- Practical cases of ascending hierarchical classification  Module
4: Chemometry 

- Practical work on labtop of data analysis and generalities and basis
of chemometrics  - Unsupervised methods (PCA, clustering, ...)  -
Pre-treatment methods  - Supervised methods of quantification (i.e.
PLS)

Course type

- Lectures and tutorials in remote (zoom and moodle)  - Face to face lectures and tutorials (in Bordeaux, faculty of pharmacy)  - Face to face lab work (in Bordeaux, faculty of pharmacy) - 61 hours = 47 contact hours (14 lectures, 15 tutorials, 12 lab work, 6 exams); 14 self-study hours (2h private reading, 2h writing assessment, 6h exam preparation, 4h group work preparation) - face to face teaching: 12h lectures, 12h Tutorials, 2 days practice  -  Distance-based or blended learning,3 h lectures and 1h tutorials

Online Course Requirement

Instructor

Other information

- Maximum number of students: 30 
- Selection procedure: Online application + Interview
- Selection criteria: bases in analytical chemistry and statistics

Duration: 14h lectures, 15h tutorials and 12h laptop work

Language of instruction: English
Mode of delivery: Face-to-face teaching and distance-based

Site for Inquiry