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Tag: pharma manufacturing

2019 Xavier University AI Summit Reflections – Two Industries Ready for Change

Now that the dust has settled from the Xavier University AI Summit and our team is back to business, we’ve had time to process some of the highlights and key takeaways from the exciting event.  In the past few years, there has been a significant increase in the implementation of digital technologies into various industries that subsequently impacted the way we live, travel, and do business.  From driverless cars to 24/7 customer support chatbots, innovation and technology continue to spiral upward and as we’ve entered the 4th industrial revolution, and healthcare + biopharma should be no exception.  The Xavier University AI Summit is a great event that brings together a range of relevant stakeholders with common focus on artificial intelligence (AI).

Where are Pharma Companies in the Age of Artificial Intelligence?

They say good things come to those who wait; we say good things come to those who wait but only the things left by the visionaries before them.  The pharmaceutical industry has long been known to lag in the adoption of new technology due to strong regulations. Even though regulators have recently begun to open up to several new ‘big data’ or pharma 4.0 technologies - the question remains, if pharma companies are doing the same?  In 2016, the European Pharmacopoeia 9.0 in Chapter 5.21 announced that neural networks (NN) and support vector machines (SVM) are valid chemometric techniques for processing analytical data sets. 

Data Scientist 4.0 – Bridging the World of Manufacturing and Data

Since the announcement of the 4th Industrial Revolution in 2011, multitudes of emerging technologies have transpired around “Industry 4.0”. Technologies such as digital twins, Industrial Internet of Things (IIoT), and cyber-physical systems have come into the scene as core elements, providing the necessary ingredients for a paradigm shift in manufacturing. Technologies around predictive analytics and artificial intelligence are pioneering new approaches with many use cases including predictive maintenance, autonomous process optimization, and pattern recognition - used to identify potential failures in real-time. Because of this, data science is becoming an invaluable discipline for our industry in order to transform information into knowledge.
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