Lyophilization 4.0

Lyophilization 4.0

January 5, 2019

The term ‘Industry 4.0’ was first coined by the German federal government in a national strategy to promote the computerization of manufacturing. The basic principle is that by connecting machines and systems, we can create intelligent networks along the value chain that control each other.

It sounds great, doesn’t it? A vision of the future with efficient, self-automated manufacturing processes that monitor themselves, so they never go wrong!

 

Pharma 4.0 represents the fourth industrial revolution in the pharmaceutical context. Digitization, an important component of Pharma 4.0, will connect everything, creating new levels of transparency and speed for a digitalized plant floor. This will enable faster decision-making and provide in-line and in-time control over business, operations, and quality. It will also require higher levels of security, since connected systems heighten vulnerability.

Adopting Pharma 4.0 involves a commitment and adequate resource allocation by the IT department to ensure necessary connections are made and maintained, and to avoid any IT snags that could cause expensive production outages. Modern information and communication technologies like cyber-physical systems, big data analytics, and cloud computing, will help early detection of defects and production failures, enabling their prevention and increasing productivity, quality, and agility benefits that have significant competitive value.

 

What about Lyophilization 4.0?

Since time ago the industrial lyophilization process had been running under the same parameters due to the usage of only 70% of process data, high economical margins, and old standards.

 

In this day and age, technology is available at a reasonable cost which makes it possible to unlock the potential of all the data related to the lyophilization process in a holistic approach (maintenance, process, and quality). At the same time, the new market circumstances (new competitors, patent expirations, and production flexibility - no more blockbuster) force the manufacturers to optimize its process. On the top of all this, the increase of warning letters from FDA shows a clear trend that data integrity issues are becoming crucial in the new environment.

 

 

 

All the above mentioned has a technical solution ahead of the mindset shift of the manufacturers. Cloud technologies allow us to break data silos between different systems and vendors (ERP, LIMS, …).  When you have all the data in the same space, it is possible to discover the first insights for process optimization crunching all the data and deciding which one has dependencies, casualties, and in which grade thanks to the AI algorithms.

 

All that makes no sense for the pharma manufacturing environment if it is not possible to ensure management of GMP data in a cloud-based big data environment. That’s why Bigfinite’s cloud-based platform was built from the ground up to support GMP operations and related regulation such as 21 CFR part 11 and the newest Data Integrity Guidelines. The technology provides inherent mechanisms that comply with ALCOA++ principles by design. Bigfinite has developed a technological solution that captures data from any manufacturing source and transports it to a managed cloud-based storage (data lake) in a compliant way that maintains data integrity. In addition, the patented solution uses state of the art core-technologies such as Industrial Internet of Things (IIoT) and Cloud Computing technology to facilitate GMP compliance and Qualification-as-a-Service (QaaS). QaaS is the ability to perform risk analysis using AI to predict the state of qualification of the system.

 

Once that is done, it is possible to apply targeted solutions to solve manufacturing challenges as: Condition Based Maintenance, Smart Golden Batch and Real Time Reject.

 

Condition Based Maintenance: The main goal in this type of solution is to detect anomalies in the ‘normal’ behavior of the asset and according to pattern recognition, make a prediction about when the device is going to fail and for which reason. That way, the maintenance engineer can act accordingly to fix the issue at the right moment (not too in advance - over cost, or too late - disaster).

 

Smart Golden Batch: The Smart Golden Batch solution identifies correlations between current real-time batch data and historical batch information using AI and big data tools. When an extraordinary batch occurs, the solution retains the values of the set of critical parameters (CQA, CPP) and its time range then compares it to real-time data and to historical data. Thus, the similarity percentage between the current batch and the extraordinary one is continuously shown.

 

Real Time Reject: The ability to run AI models on the edge allows users to reduce the false positive samples of vials at the inspection line after the freeze dryer. The models can first be trained outside the platform, then imported to the platform to ensure the certification, and lastly downloaded to the edge again to have the requested response time.

 

Takeaways bulleted:

  • No more digital silos. With the current technologies, the holistic approach to a freeze drying process is possible. Having all the data in the same regulated space improves the manufacturing process, crunching data from different data silos that never interacted before.

  • Pharma engineers using latest IT technologies. More than 30 years of experience in pharma manufacturing leads into templates that target specific manufacturing challenges. In particular, for freeze drying processes, would make sense to use ‘Condition Based Maintenance’, ‘Smart Golden Batch’, and ‘Real Time Release’.

  • Uniqueness: GMP compliance platform. Bigfinite is the only platform ensuring data integrity from the data acquisition point up to the virtual private cloud and its management.

 

 

 

 

 

 

 

 

 

 

 

 

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