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Cultural Resistance… Who are the Real Enablers?

Cultural Resistance… Who are the Real Enablers?


Advanced analytics technologies in the pharmaceutical industry are accessible now more than ever and regulators have slowly become more accepting to these kinds of advances.  The introduction of machine learning, artificial intelligence, and big data technologies are disrupting our industry, and it’s time we change our mindset.  People are the real enablers of the paradigm shift and if we continue this pattern of cultural resistance, pharmaceutical companies cannot continue accelerating and will not remain competitive in the growing pharmaceutical market.

Technology in place

From the processing of big data to the kinds of cloud computing architectures (serverless and SaaS), the industry is evolving.  Technology has made it possible for most companies to afford remote computing power akin to NASA’s servers.  Additionally, tools running artificial intelligence (AI) models are becoming much more accessible.  Companies continue gaining access to these kinds of technologies and it is time they start leveraging them.  Why are companies still using basic statistics and only working with a few process variables?   


Regulators are becoming more open minded

Up to now, the fear of regulatory exposure was used as an excuse for companies to stay conservative and away from implementing new technologies.  But as the industry continues to shift, this is coming to end. There has been a real mindset shift in how agencies incorporate new technologies into their standards and guidelines. A recent example is from the European Pharmacopoeia, where they established artificial neural networks and support vector machines as chemometric methods applied to analytical data.

Also, the MHRA (Medicines and Healthcare products Regulatory Agency) established a GxP Data Integrity Guidance for cloud providers including Software-as-a-Service, Platform-as-a-Service, and Infrastructure-as-a-Service.

And the FDA (Food and Drugs Administration) has incorporated a cloud technology into their Emerging Technology Team recognizing that it will influence how quality systems will be assessed by FDA.



The need for change

There is a clear trend in the decrease in margins while regulatory pressures continue to increase. Additionally, there are no more blockbusters and the increase in personalized medicine will require more flexible production requirements. Taking into consideration all of these factors, most companies are not using 70% of their manufacturing data.  It’s clear that there is huge room for improvement.

There is also an increasing number of FDA Warning Letters for data integrity issues that reflect a clear lack of process knowledge and data management skills.

People, People, and People

There are several factors important in enabling Pharma 4.0 but one of the most crucial components in the paradigm shift is the people.  The workforce is used to working in such regulated and protected markets surviving in their comfort zone.  Nowadays, technologies allow us to work with big data in the cloud while ensuring data integrity and cloud technologies. 

At this point, we know the reason for changing, we have the technologies and tools in place and regulators aligned.  So why is the pharma industry so slow to adopt these new technologies? Because of the mindset of people. Pharma 4.0 will continue to stay as an industry hype in the marketing departments until we have a real mindset shift.

Melissa Villalobos

Sales and Marketing Coordinator

Bigfinite Announces Additions to Executive Team

Bigfinite, Inc. (Bigfinite), the leading manufacturing data analytics platform company for regulated industries, today announced that Brian Sweeney, Lawrence Baisch and Glenn Griffin have been added to the leadership team.
Crystal Black VP of Marketing

AI Algorithm Qualification

Pharmaceuticals and Biotech companies have no doubt that Artificial Intelligence (AI) is here to stay. Nonetheless, the opportunities AI technology offers are developing at a slow pace in a rather conservative manufacturing industry, aimed at managing production risks under controls that are subject to strong regulations. Fear of change? Risk aversion? Likely not.
Jordi Guitart VP of Artificial Intelligence

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Bigfinite, Inc. (Bigfinite), the leading manufacturing data analytics platform company for regulated industries, today announced that John Vitalie has been named Chief Executive Officer (CEO) and has been elected to the Board of Directors. David Merino has been named Chief Financial Officer (CFO) of Bigfinite.

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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).

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Bigfinite and NNE announced a strategic partner program agreement to collaborate around accelerating digital transformation within manufacturing operations at the world's leading pharmaceutical and biotech manufacturers. 

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. 

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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.