Virtual Classroom Training

Bespoke interactive e-learning

This extensive training on Statistical DoE & Modelling using JMP will provide deep insights into statistics using JMP, linear models, response surface models and design of experiments. 

Type: Virtual Classroom Training

Duration: 3 Days (each divided into two 0.5-day sessions)

Who should attend?: Assay research Scientist, Process Development Scientists

Implement Quality by Design for your assays and process using JMP

Intro to basic statistics (using JMP) 

  • Import data within JMP 
  • Recognize different types of statistical variables 
  • Perform basic data visualization and analysis  
  • Perform simple statistical tests 
  • Edit lines/rows/observations of a data table 
  • Edit columns/variables of data a data table 
  • Manipulate data to obtain proper format for further analysis 
  • Refresh basics on data observations and statistics 
    • N.B.: This session is a prerequisite for all other 1-day sessions.

Linear models, response surface models 

  • Fit linear models 
  • Make diagnostic plots 
  • Make calibration 
  • Perform multiple linear regression models 
  • Feel the value of DoE 
  • Understand what it means 
  • Compute probability of success 
  • Estimate variance components
    • N.B.: This session is a prerequisite for Lesson 3: DoE.

Design of experiments (prerequisites: Lessons 1 and 2) 

  • Understand Doe concepts 
  • Plan an experiment 
  • Organize your work and anticipate 
  • Find the appropriate design 
  • Use the catalog of DoE 

Pierre Lebrun

Pierre Lebrun is Director Statistics at Pharmalex, which Belgium arm is dedicated to statistical expertise. During more than 14 years, Pierre specialized in quality-by-design aspects related to processes and assays, with a strong emphasis on the use of Bayesian statistics to improve knowledge during the process and assay validation stages. Pierre is also a recognized trainer in statistics for the pharmaceutical industry, including design of experiments, Bayesian statistics, statistical process control, and assay development and validation.

Pierre joined the USP panel in charge of the development of the USP 1220 chapter about a holistic approach to assay validation using the concept of the analytical procedure lifecycle. He also gives lecture on DoE at Liège university (Uliège, Belgium) and collaborates with the research team on new chemometrics and statistics methods for analytical development, validation and PAT. Pierre’s work in applied statistics can be found in 150+ international peer-reviewed papers, book chapters and conference proceedings on these subjects. Pierre Lebrun holds a master’s degree in computer sciences and economy, followed by a master in statistics at the university of Louvain-la-Neuve in Belgium. He completed his PhD in statistics from University of Liège.

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