Harnessing the Power of Omics With Multivariate Data Analysis (MVDA)


In the rapidly advancing fields of life sciences and pharma/biopharma, "Omics" serves as a foundational concept, encompassing genomics, proteomics, metabolomics, lipidomics, and more. These disciplines are pivotal for driving innovation and understanding complex biological systems. A significant challenge in Omics data analysis is the extraction of meaningful insights from large-scale, high-dimensional datasets. Treating these datasets holistically is essential at every stage, from pre-processing to interpretation, due to the vast number of variables involved, which surpass those in conventional analyses. 

Metabolomics, a crucial component of Omics, offers profound insights into cellular processes and disease mechanisms by evaluating metabolites. Through the analysis of small molecules, researchers can identify disease biomarkers and assess environmental impacts. The intricate nature of metabolomic data necessitates sophisticated analytics tools to discern patterns, integrate diverse data types, and develop predictive models. 

Omics studies produce data with numerous correlated variables, aiming to uncover relationships between entities such as disease versus control samples or pre- and post-treatment conditions. Multivariate Data Analysis (MVDA) provides a comprehensive toolbox to tackle these complex questions.

Join us for this informative webinar to explore MVDA tools, understand their applications, and learn about the types of information that can be extracted from Omics data. We will feature a demonstration of the SIMCA® software, designed for multivariate data analysis, which is particularly suited for analyzing intricate Omics datasets. SIMCA® offers an Omics skin, facilitating quick access to Omics-specific features. It is user-friendly, guided by the Analysis Wizard, and requires no extensive MVDA expertise.

 

What You Will Learn:

  1. Understand the complexity of Omics data
  2. Realize how MVDA facilitates interpreting Omics data
  3. See how SIMCA® and its Omics skin facilitates the analysis and interpretation of Omics data

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Presenters

This webinar is co-presented by Izabella Surowiec, Pär Jonsson and Lennart Eriksson.

Izabella Surowiec holds a PhD in analytical chemistry and has spent more than a decade of her early career working in the metabolomics area at different academic and industrial institutions. She joined Sartorius in 2018, where, as a Senior Process Analytical Technology (PAT) Scientist she contributed to the development of Sartorius BioPAT® solutions and expanding their applications towards new bioprocess areas. She has also been involved in identifying emerging innovative technologies and integrating these into Sartorius PAT portfolio. Currently she is supporting customers with her data analytics knowledge in improving their process development and manufacturing.

Pär Jonsson has been a Senior Research Scientist at Sartorius Corporate Research since 2022, based in Umeå, Sweden. He specializes in developing multivariate data analysis (MVDA) methods and is dedicated to discovering new applications for MVDA. Pär earned his PhD in Chemometrics from Umeå University in 2006, where he also served as an Associate Professor, teaching chemometrics courses. His research at Umeå University focused on developing and applying chemometric methods aimed at facilitating the early detection of diseases using metabolomics.

Lennart Eriksson is a Principal Data Scientist at Sartorius Digital Solutions. Lennart holds a PhD and an Associate Professorship in Chemometrics from Umeå University, Sweden. 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.