Umetrics Suite Blog

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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Using Data Analytics to Accelerate COVID-19 Vaccine Development

July 23, 2020

In the midst of a global COVID-19 pandemic, a top priority for many pharma and biopharma companies is to get a vaccine developed, produced and delivered to the public as quickly as possible. Ushering a vaccine through rigorous testing protocols and regulatory approvals is not an easy (or quick) effort, but incorporating advanced data analytics could help accelerate the process. Data analytics has proven effective in speeding vaccine development both by enabling more efficient Design of Experiments (DOE) and by creating rapid-scale production rollout processes.

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MSU Uses Data Analytics to Uncover Cost Savings and Reduce Power Plant Emissions

June 2, 2020

Looking for ways to improve the efficiency of its power plant operations while reducing costs and environmental emissions, the Department of Power and Water at Michigan State University (MSU) began a study using multivariate data analytics that led to some surprising findings. The results have implications that could help other operators of large-scale power facilities reduce their carbon footprint and improve power plant operations.

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Meeting Common Challenges in Balancing Emissions and Boiler Efficiency

May 28, 2020

Finding the right balance between efficient power output from boilers and other energy producing equipment while also reducing environmental emissions is an important objective for power plant operators. Governments and environmental agencies around the world establish emission standards as part of air pollution regulations, but finding the right way to meet the standards can vary greatly depending on location, equipment and other operating factors.

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How Pulp and Paper Companies Are Reducing Production Costs Using Multivariate Data Analysis

April 23, 2020

While many other industries have implemented multivariate data analysis software for process optimization and control, it is still not very common in the pulp and paper industry. However, multivariate data analysis has a very promising potential for both cost reductions and quality improvements in pulp and paper mills. No capital investments are needed, the implementation can be done remotely, and the software typically requires no permits.

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From Emissions to Fuel Efficiency: What Is Your Power Plant Data Hiding?

October 28, 2019

Optimizing the function of boilers, turbines and other capital equipment used to generate power requires a careful balance of fuel, heat, pressure, operator proficiency and many other variables. Managing the process on a day-to-day, or minute-to-minute basis, is like performing a skilled and well-orchestrated dance—partly based on data, but also based on operator expertise. Yet, adding more accurate information to the equation can potentially save millions of dollars, cut emissions significantly and even expand the working life of your equipment. 

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How to Increase Yield in the Electronics Industry With Real-Time Data Analytics

October 21, 2019

There is a strong demand for devices such as mobile phones, tablets and large screen TVs all over the globe. The business is competitive, which puts pressure on prices. At the same time, production costs are fairly high due to complex production processes. Consequently, a high yield becomes paramount for good profit margins. Multivariate data analysis (MVDA) is being employed by an increasing number of manufacturing companies to increase yield, and the electronics industry is no exception. This article provides examples of where and how real-time data analytics can be used in the electronics industry.

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Multivariate vs Univariate Analysis in the Pharma Industry: Analyzing Complex Data

June 18, 2019

The pharmaceutical industry, including R&D, manufacturing and also product sales and use, creates a lot of data. The question is, what can we do to understand our data better, get more out of it, and unlock its potential in the most rational way possible to get to the knowledge we need? And how can we gain control over our research, or the processes needed to generate a stable, reliable product that consistently meets regulatory requirements? The answer is Multivariate Data Analysis.

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Get the Most out of Unstructured Data With Deep Learning

May 23, 2019

The potential for Artificial Intelligence (AI) is enormous and the applications seemingly unlimited. One subset of AI, deep learning, offers the promise of efficiently solving a large range of challenges involving unstructured data by harnessing neural networks to save time and money, and even perform seemingly impossible tasks.

Deep learning has revolutionized the fields of artificial intelligence, computer vision, speech recognition, and more in recent years. Deep learning can draw information from unstructured data such as images or text in a way that was unthinkable a decade ago. In industries like Pharma and Biopharma, deep learning can help all the way from understanding how cells work using live cell imaging to monitoring manufacturing using audio.

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Detecting and Preventing Food Fraud Using Data Analytics

May 14, 2019

Whether it’s fake olive oil, coffee bulked up with husks and twigs, or honey tainted with antibiotics, food fraud is a growing problem worldwide. The Australian research organization CSIRO states that the economic damage alone from food fraud has reached $35 billion (in US dollars) in 2018. The underlying cause is nearly always financial gain and economic pressures to save money by using inferior (or mislabeled) products. Predictive analytics is one tool manufacturers are using to combat food fraud.

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Latest version of SIMCA focuses on improved user experience

May 7, 2019

SIMCA 16 offers improved ribbons, tours, wizards, data merging, multiblock analysis and more.

SIMCA is a multivariate data analytics tool that helps users make sense of complex data by transforming numbers and statistics into visual information for easy interpretation and understanding. Across many industries ranging from pharmaceuticals and chemicals to food and beverage manufacturers to academia, SIMCA helps production managers and researchers a like make better decisions in order to take action quickly and with confidence.

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Interpretation for the use of multivariate models within the FDA draft guidance for continuous manufacturing

April 24, 2019

Recently the FDA issued a new draft guidance for continuous manufacturing of small molecule drugs. With these draft guidelines the FDA wants to engage more pharmaceutical manufacturers to shift from traditional batch/start-stop processing to continuous manufacturing. The main advantages associated with these processes are more room for modularity, automation and flexibility due to a smaller footprint, but also more consistent quality of the drug product. Of course the main incentive for the FDA to promote this way of processing is that it believes that this will have a positive impact on drug prices and prevent drug shortages.

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