Cart 0
Batch Process Modelling using MVDA - 2 days course - USA

Batch Process Modelling using MVDA - 2 days course - USA

Batch Process Modelling using MVDA

This course is for those who want to model bioprocesses using SIMCA. Basic understanding of SIMCA or multivariate statistics is beneficial but not needed.

Using the latest multivariate techniques, participants will learn how to build multivariate process models, from defining the process to the real-time application in SIMCA-online.

The course is composed of lectures, demonstrations and computer exercises in software SIMCA and SIMCA-online, based on real-life datasets.


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 online process data. Multivariate data tables are translated into interpretable figures and plots which simplifies the process monitoring as well as analysis of process deviations. Participants are encouraged to bring their own data.


    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, investigations of deviation and scale-up of processes.


    • 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 contains many practical hints to make modelling easy

    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.


    1st day
    9:00 to 17:00

    Focus on setting the basis for powerful and robust process models.

    After the first day the attendee should know what batch modeling is and how to set the basis for process models.

    • Values, Objectives and Possibilities for Multivariate Batch modeling and monitoring
    • Basic understanding of the multivariate techniques used
    • How get an strong data basis for robust models

    Demos and Exercises

    2nd day
    9:00 to 17:00

    Focus on implementing process models.

    After the second day the attendees should know how to build process models and how to validate them as well how to translate the model into SIMCA-online.

    • Continue to build process models
    • What to consider when building models
    • Understand how to set-up a SIMCA-online configuration and workspace
    • Demo and Exercises


      Please note that at some course locations you are required to bring your own computer for the exercises. Instructions on how to install the program will be included in the final course information.

      Included in the course fee (+ VAT) is coffee, lunch and course documentation.

      Cancellations received later than two weeks before the course starts 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.

      Course participant(s) can be substituted by the registering company as long as Sartorius Stedim Data Analytics AB is notified.

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

      Share this Product

      More from this collection