Skip to content Skip to navigation menu

Multivariate Data Analysis (MVDA) | Onsite Course

This course is for those who want to model bioprocesses using SIMCA®. A basic understanding of SIMCA® or multivariate statistics is beneficial but not needed. Participants will learn to build multivariate process models using the latest multivariate techniques, from defining the process to the real-time application in SIMCA®-online. The course comprises lectures, demonstrations, and computer exercises in software SIMCA® and SIMCA®-online, based on real-life datasets. We always strive to deliver outstanding training focusing on the participants and their learning capacity. The training is split into four sessions. One home exercise per session is included, and it is expected that the course delegates work on them outside the session time.

Course Duration: 2 Days

Start First Day: 9:00 am

End Last Day: 5:00 pm

Course Dates and Location:

Shanghai: October 20-21

Please add the course date to the My Request in the form so we can register you for the right course.

Item no.:  UT-300071-3

 

Course Objective

The objective of this course is to guide the attendees through their journey from a process data set to a multivariate monitoring model based on their process data. Multivariate data tables are translated into interpretable charts and plots, which simplifies the process monitoring and analysis of process deviations. Multivariate technology is the science of separating the signal from the noise in data with many variables and presenting the results in a simple graphical format. Quickly go from a complicated table of numbers to a simple plot of the essentials. The key to unlocking the information in your data lies in the correlations among the variables, not in the variables themselves.

Who Should Participate?

The course is intended for researchers, scientists, and engineers from all sectors of biopharma with a lot of process understanding but with no or limited statistical background. Typical applications include product development, process improvement/optimization, deviation investigations, and scale-up of processes.

Course Objective

The objective of this course is to guide the attendees through their journey from a process data set to a multivariate monitoring model based on their process data. Multivariate data tables are translated into interpretable charts and plots, which simplifies the process monitoring and analysis of process deviations. Multivariate technology is the science of separating the signal from the noise in data with many variables and presenting the results in a simple graphical format. Quickly go from a complicated table of numbers to a simple plot of the essentials. The key to unlocking the information in your data lies in the correlations among the variables, not in the variables themselves.

Who Should Participate?

The course is intended for researchers, scientists, and engineers working with the collection and interpretation of data. Methods are general and applicable in most fields, where the aim is to gain maximum information from the data. No prior knowledge of statistics is assumed.

Selected Course Content

  • Introduction to batch methodology and modelling concept
  • Raw data analysis: How to find reliable data
  • Background of statistical methods applied
  • Modeling of Batch evolution and Model interpretation
  • Transferring models into SIMCA-online
  • The course slides contain many practical hints to make modelling easy

Language Information

Seminars are given in the language stated. In-depth discussion, course material, and printed material are in English; hence knowledge of English is required.

Schedule

Day 1:

Introduction to MVDA

Introduction to Sartorius Data Analytics

  • The need for multivariate data analysis
  • Introduction to PCA
  • Principal Component Analysis (PCA) for overview of data tables
  • Software click-along demo
  • One home exercise

Data Preprocessing, PCA Applications

  • Variable scaling
  • Variable centering
  • Geometrical interpretation
  • Model evaluation
  • PCA applications – how does PCA bring value?
  • Software click-along demo
  • One home exercise

Day 2:

Introduction to OPLS, Visualization

  • Introduction to Orthogonal Partial Least Squares, OPLS
  • Regression models. Prediction of responses Y from parameters X
  • Model diagnostics and validation of a PLS and an OPLS model
  • Software click-along demo
  • One home exercise

OPLS Applications – how does OPLS bring value?

  • OPLS applications
  • Software click-along demo
  • One home exercise
  • Course debriefing and final Q&A

Course Material and Software

The electronic course material (course slides and exercises) and the SIMCA® course license will be emailed two weeks before the course starts. SIMCA® needs admin rights to be installed, so please get in touch with IT soonest. Sartorius cannot help you to install SIMCA®. We recommend you have two screens or one projector and one PC to follow the course and demos easily. However, this is not required.

Preparation

We recommend listening to “Analyzing batch process data, a step-by-step guide for the beginner” before the course start (watch recording).If you have any questions, please do not hesitate to send an email to: umetrics_academy@sartorius.com 

Cost and Conditions

The course fee is 1500€ per person.

Cancellations received later than two weeks before the course will not be refunded. For courses cancelled more than two weeks before the course starts, Sartorius Stedim Data Analytics AB will retain 10% of the course fee to cover administrative costs, and the rest of the amount will be refunded.

The registering company can substitute course participant(s) as long as Sartorius Stedim Data Analytics AB is notified.

Sartorius Stedim Data Analytics AB provides courses based on a sufficient number of registrants. Therefore, Sartorius Stedim Data Analytics AB reserves the right to cancel the course 14 days before the course start date if the number of registrants is too low. A full refund will be made to these registrants. A 10% discount will be made to any registrant(s) enrolling in the next available course.

Features

  • Display
    SIMCA®

Product Information

  • Brand
    SIMCA®