Webinar Elevate your Downstream Data

Elevate your Downstream Data Using DOE, MVDA and Machine Learning

Downstream process development in biopharmaceutical industry involves optimizing purification methods to ensure product quality, safety, and efficacy. Design of Experiments (DOE) and Machine Learning methods, including Multivariate Data Analysis (MVDA), are becoming increasingly important in downstream process development and process monitoring.

DOE is a statistical technique that optimizes resource utilization and extracts valuable information from experimental data. DOE empowers scientists to optimize downstream processes efficiently, leading to better product quality and reduced development costs. MVDA 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. MVDA is the key to unlocking the information residing in complex downstream process datasets.

The objective of this presentation is to set the scene for the new Learning Series on the use of Data Analytics in downstream applications. An introduction to the basic principles of DOE and MVDA is provided.

What You Will Learn:

Learn how DOE enables maximally informative experiments
Find out how MVDA extracts the golden nuggets in your data
Discover how Machine Learning methods can be used in process development and monitoring

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Presenter

The webinar is presented by Assoc. Prof., Dr., Lennart Eriksson, Principal Data Scientist at Sartorius Digital Solutions. Lennart has worked with DOE and MVDA for over three decades across various industrial segments. His special interest lies in teaching all aspects of DOE and MVDA, ranging from onboarding new practitioners all the way up to the expert level.