Umetrics Suite Blog

Lennart Eriksson

Lennart Eriksson
Sr Lecturer and Principal Data Scientist at Sartorius Stedim Data Analytics
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Recent Posts

OPLS vs PCA: Explaining Differences or Grouping Data? (Analyzing Omics Data)

August 25, 2020

OPLS and PCA are two commonly used techniques to analyze genomics, metabolomics and other Omics data.

Do you know when to use OPLS-DA and when to use PCA data analysis techniques to makes sense of your Omics data? Find out how to uncover the differences in your data with these classification and discriminant analysis methods.

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What Is Principal Component Analysis (PCA) and How Is It Used?

August 18, 2020

Principal component analysis, or PCA, is a statistical procedure that allows you to summarize the information content in large data tables by means of a smaller set of “summary indices” that can be more easily visualized and analyzed. The underlying data can be measurements describing properties of production samples, chemical compounds or reactions, process time points of a continuous process, batches from a batch process, biological individuals or trials of a DOE-protocol, for example.

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What is DOE? Design of Experiments Basics for Beginners

August 4, 2020

[This blog was a favorite last year, so we thought you'd like to see it again. Send us your comments or questions!]

Whether you work in engineering, R&D, or a science lab, understanding the basics of experimental design can help you achieve more statistically optimal results from your experiments or improve your output quality.

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Understanding the Relationship Between Data Science, Artificial Intelligence and Machine Learning

July 15, 2020

You’ve probably heard the terms artificial intelligence (AI), machine learning (ML) and deep learning (DL) being used in conjunction with digital transformation and data science. You may be wondering what the relationship is between these subjects. How are businesses in industries ranging from biopharma to chemicals to food & beverage incorporating AI, machine learning and data science to improve their processes? Let’s take a look at what these terms mean and how businesses are using them to make more strategic decisions and improve production processes.

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Using Multivariate Models in a Regulated Environment for Continuous Manufacturing of Pharmaceuticals

January 14, 2020

Continuous manufacturing is one of the key trends within the pharmaceutical industry, both for the production of ‘classical’ drugs as well as large molecules. Companies are looking for ways to shift from traditional batch processing to a continuous method of operation. The main advantages associated with these processes are more room for modularity, automation and flexibility due to a smaller footprint, as well as more consistent quality of the drug product.

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Data analytics techniques help researchers identify promising breast cancer biomarkers

March 12, 2019

Breast cancer is the most commonly diagnosed cancer amongst women worldwide and a leading cause of cancer related deaths among females. It’s the second most common type of cancer overall. According to the International Agency for Research on Cancer Research, there were more than 2 million new cases in 2018.

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Data analytics could help reduce falls and fear of falling among elderly people

January 7, 2019

Many elderly people are afraid of falling – and for good reasons. Falls can have serious consequences for the individual but also the fear of falling could have serious effects on health and independence. A new research project at Luleå University of Technology in Sweden has taken a closer look at fall-related concerns among elderly people, using multivariate data analysis, MVDA, with the ultimate goal of finding diagnostic and training methods that could help reduce falls. Results from the first studies have given some interesting answers.

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Uncovering the secrets to long-lasting bubbles: Using DOE to optimize a mixture design

December 18, 2018

What’s the secret formula for creating long-lasting bubbles? Is expert knowledge of liquid dynamics needed to optimize the mixture design and develop the best bubble solution? Or can we use design of experiments (DOE) and data analytics to draw conclusions? Let’s a take a look at a fun example of how DOE can be used to optimize a mixture design in order to achieve our goal: create long-lasting bubbles.

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Design of Experiments enables the optimization of transfection efficiency in line with QbD principles

November 29, 2018

Pressure to cut development costs and lower regulatory barriers while assuring product quality has stimulated the pharmaceutical industry to apply Quality by Design (QbD) to manage risk and gain process and product understanding. As a result, QbD is being widely promoted by regulatory authorities such as the Food and Drug Administration, and the International Conference on Harmonization.

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Racing to the breaking point with multivariate data analysis

October 23, 2018

On the west coast of southern Sweden, facing the expanse of the ocean, is the beautiful city of Gothenburg. Surrounded by a string of islands, this city has been the home for sailors and merchants, seafaring and shipping, since ancient times. One of the islands to the north of Gothenburg is the picturesque island of Tjörn. Once every year, Tjörn is the location for one of the most famous sailing races in Sweden – “Tjörn Runt” or “Around Tjörn”.

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Are differences in technician performance affecting your product’s quality?

October 9, 2018

In a manufacturing setting where consistent quality matters, variability in how individual technicians and operators perform their jobs can be frustrating for managers. Companies need a way to achieve consistent quality, without reducing the capacity for innovation and improvement.

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How to use data analytics to understand consumer preferences

July 12, 2018

Product development and innovation are important elements for the survival of many companies. Whether introducing a new food flavor or adding new product features, understanding consumer preferences can help guide both design and production decisions. The right decisions can make a product launch more successful, and ultimately more profitable.

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