Umetrics Suite Blog

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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Is Your Company Ready for Digital Transformation and Biopharma 4.0?

May 19, 2020

From employing artificial intelligence (AI) to identify drug candidates to using big data to support continuous process manufacturing, the prospects for digital transformation in the biopharma industry are huge. Yet, biopharma and life sciences lag behind many other industries when it comes to digital transformation.

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Process Optimizations That Help Chemical Manufacturers Weather the Corona Crisis

April 30, 2020

In the midst of a global crisis, many industrial manufacturing operations— including those in the chemical industry— are faced with shortages of supplies and equipment, or staff reductions, and finding it difficult to keep operations working as normal. Are there process improvements or tools that can be used to manage production more efficiently during this time of COVID-19 (and moving forward)?

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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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GSK Applies Raman Spectroscopy as Process Analytical Technology (PAT) for Bioreactor

March 31, 2020

A team at Glaxo Smith Kline, GSK, has carried out several studies using Raman spectroscopy and multivariate data analytics in order to monitor upstream cell culture processes. The studies show that Raman spectroscopy is a valuable analytical tool for enabling real-time monitoring and control of production bioreactors and that improved control can lead to improved product quality. Below is a summary of the studies.

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Scientists Use Data Analytics to Uncover the Differences Between Coronavirus Strains

March 19, 2020

An important step on the road to creating treatments for  illnesses like  COVID-19, which has caused the recent global pandemic, may start with understanding the similarities and differences between the various strains of coronavirus known to exist today. Making sense of large and complex sets of data, especially those that require novel interpretation, calls for a powerful analytics toolset to speed up the process. 

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Avoid Costly and Dangerous Process Deviations by Using Real-Time Data Analytics

March 5, 2020

Out of control processes in pharma manufacturing are not something to take lightly. If your production runs are seeing frequent deviations, leading to expensive batch losses or frequent rework, it’s time to take a look at ways to correct any process deviations in a more expedient manner. Uncorrected deviations or processes that vary from approved process parameters can lead to costly and dangerous mistakes.

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Correcting the Most Common Causes of Pharma Process Deviations

February 27, 2020

Keeping your pharmaceutical manufacturing processes under control is important not only to ensure a quality product, but also for regulatory compliance. Process or raw material deviations can affect the downstream quality of a product and could mean tossing out an entire batch or end product if process corrections aren’t made soon enough — or if you can’t document that a correction was made before it affected your critical quality attributes.

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Seven Common Causes of Pharma Process Deviations

February 5, 2020

For pharmaceutical manufacturers, a process deviation may not only mean a bad batch that affects a downstream process, it can also risk a regulatory violation that leads to fines or expensive market setback, or worse, it could endanger the health of the patient.

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Scientists Used DOE to Optimize a New Assay for Diagnosing Rare Kidney Disease

January 23, 2020

A new diagnostic method for detecting a rare kidney stone disease has recently been developed at the University of Iceland. Instead of using urine microscopy, which has certain disadvantages, the diagnostic method is based on mass spectrometry of plasma samples. Preliminary clinical data shows very promising results both in terms of detecting the disease and therapeutic drug monitoring. Design of Experiments (DOE) was used as a chemometric approach to optimize the assay. Below is a summary of the assay development and optimization.

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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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