BIOPHORUM Digital Plant Maturity Model : Time to move pharma manufacturing to the next level

Last month, together with the other active members of BioPhorum, we began working on the update of the ??Digital Plant Maturity Model??.

Initially published in 2018, the development of this Digital Plant Maturity Model aims to aid transformation in biopharmaceutical manufacturing. It is also a very powerful way to align pharma manufacturers, suppliers and the entire ecosystem (CMO, authorities….) on definitions, common vocabularies and concepts.

The concept of a ‘digital plant’ is a hot topic among biologics manufacturing companies today, however, before this DPMM effort, there was no consensus of what exactly this term means. Open questions, such as: How does a digital plant relate to initiatives such as ‘paperless plant’, ‘fully automated facility’, ‘factory of the future’, etc…? And what is its relationship to technology advances such as the Internet of Things and big data analytics? remained unanswered.

After 4 years of usage of this DPMM model, it is time to look into the mirror, and think about the future… and more than likely to also update the model.

At Dassault Systèmes, we believe that a “digital transformation” is needed in biomanufacturing, and going beyond that, we believe a “digital transformation” is needed across the entire industry. With the emphasis on the “transformation” part! Reaching the ultimate level of the digital plant (the “adaptive plant”), according to BioPhorum members, will not be possible without a proper transformation in the way pharma companies work and collaborate with their suppliers.

The five levels of digital plant maturity are:

1. Pre-digital Plant

2. Digital Silos

3. Connected Plant

4. Predictive Plant

5. Adaptive Plant

The Adaptive Plant level is achieved when you’ve implemented :

• Full end-to-end, value-chain integration from suppliers to patients
• Modular, mobile and collaborative manufacturing environment
• Advanced production technologies used as standard
• “Plug-n-play everything” from an instrument to a production scale or a CMO
• Zero system down-time (including upgrades) – continuous evolution
• In-line, real-time, continuous, closed loop, process verification and control with automated real-time quality release
• Self-aware, continuously adaptive, “autonomous” plant; exception conditions handled by remote experts
• Advanced simulation used across the value chain for modeling, testing and improvement of manufacturing and supporting business processes
• Trusted information insights freely and securely available. Pervasive use of adaptive analytics and self/machine learning across value chain

Since 2018, new concepts are now becoming a reality and should be absorbed into the model. One of these examples is the notion of complete modularity, allowing improved flexibility, known as the “ballroom concept”. The “ballroom concept” was originally defined in the International Society of Pharmaceutical Engineers (ISPE) as “A large manufacturing area that has no fixed equipment and minimal segregation due to the use of functionally closed systems.”

The “ballroom concept” includes placing the bioprocess equipment on wheels, rather than in permanently fixed positions and has been popularized by companies such as Cytiva.

Solution such as Made to Cure for BioPharma can help you achieve the agility this concept allows. It provides deep digital capabilities and visibility across the enterprise and facilitates data-driven decision making for therapeutics supply.?Connecting people with information and data enables quicker, more informed decisions, while infusing virtualization and simulation into manufacturing planning and operations helps ensure therapies are produced ‘As designed’ and ‘As registered’ in the most cost-effective and high-quality manner.

I would highlight three main business changes enabled by Made to Cure for BioPharma:

1) Design, optimize and commission manufacturing lines and processes before implementation

As pharmaceutical manufacturing lines transition towards small batch production of precision medicines, companies need to achieve end-to-end manufacturing line optimization to produce sustainably.

Companies must adopt a new paradigm to optimize their complex industrial plants, processes and products. This is possible with digitalized manufacturing, which enables effective collaboration between diverse stakeholders.

With Made to Cure for Biopharma, engineers can model, optimize and commission the production line through a virtual experience before the actual product introduction. It allows engineers to quickly understand and implement engineering changes as well as adapt the production line on-demand to accelerate new product introduction (NPI) without additional costs or delays.

In a modern approach, it helps also to manage the definition, the configuration and the version of all the process steps, equipment, single use material and drugs in a modular way (it’s the PLM – Product Lifecycle Management approach, as introduced in ICH Q12, and popularized in flexible and digitized facilities)

2) Optimize global manufacturing operations with lean practices and production scheduling and execution

The main challenge for companies is to synchronize all manufacturing operations across the value network as they strive to consistently produce high-quality medicines to patients worldwide.

Made to Cure for Biopharma reinforces corporate unity by managing information from global manufacturing operations in one single environment. Streamlined forecasting, planning and scheduling are essential to driving manufacturing profitability. The solution supports this by providing the power of production flow synchronization and constraint-based, finite-capacity resource optimization.

Companies can also reduce inventory and lead time while increasing production by aligning raw materials and components with production, quality control and equipment maintenance processes to eliminate obsolete inventory.

3) Optimize product quality, yield and costs across the manufacturing value network

A proper, continued process verification is a crucial initiative for any pharmaceutical company to comply with regulatory authorities, monitor processes and maintain a consistent state of control while improving manufacturing productivity.

Made to Cure for Biopharma provides a real-time view of global manufacturing operations to maximize process performance and increase visibility into process operations, quality and compliance risks. The solution allows easy data access, automated aggregation and contextualization.

Companies can create a robust and sustainable commercial production process by monitoring and correcting the performance of critical production operations in real time through automated alerts. Real-time monitoring improves decision-making during batch production and establishes a data-driven culture for process-knowledge sharing and collaboration.

We’ve discussed with BioPhorum of all the advantages of an adaptive plant. Companies using solutions such as Made to Cure for BioPharma have observed the following benefits:

• 25% gain in production throughput
• 30% increase in production capacity through layout optimization
• Up to 60% increase in manufacturing efficiency
• Drive to zero batch failure and deviation
• Lower inventory by 35%
• 33% increase in on-time delivery and forecast accuracy
• 80% reduction in QC release activities’ time
• 80% reduction in human error

Conclusion: Virtual Twin and Sustainability

I could not end this article, without opening your eyes to the benefits of virtual twins, and refer to the excellent white paper written by my colleague Barbara Holtz. The whitepaper is titled: The Virtual Twin Experience of the Pharmaceutical Process. Like what it does for pharma processes, the Virtual Twin experience of the manufacturing process will add considerable value to any pharmaceutical or biotech organization by facilitating collaboration, risk analyses, change assessments, predictive simulations and support for many more activities. The value of the virtual twin in discrete manufacturing has been shown to include significant benefits such as: 34% product quality improvements, 30% reduced manufacturing costs, 28% reduced unplanned downtime, 25% increased throughput.

Last but not least, I see in that DPPM approach, a unique opportunity to tackle the big challenge we are facing now in the pharma industry: Target zero carbon emission and advance with a sustainable pharmaceutical manufacturing strategy. Current pharmaceutical sustainability approaches aren’t sufficient to meet high sustainability requirements, but there is a better way.

Pharmaceutical manufacturers need to adopt a new paradigm to optimize their complex industrial plants, processes and products. They need to digitalize their manufacturing because it is the only way to enable diverse stakeholders to come together and systematically determine, among many considerations:

1. Whether to construct new facilities or optimize existing ones
2. Where? therapies should be produced
3. If it's possible to increase resource efficiency and effect process improvements to lower costs
4. How to link patients to the product, process and factory

Instead,?sustainability?needs to be factored into pharmaceutical manufacturing?from the start. Another Dassault Systèmes colleague of mine, Arnaud CASTERAN, Senior Offer Marketing Manager at CATIA said “It’s in the early phases of the design that you factor in the environmental, social and business sustainability requirements to be able to optimize them”. And, to do so, pharmaceutical manufacturers need to transition to digitalized manufacturing to manufacture more sustainably. (click here to know more about it)

Arnaud also added, “All of these considerations can be factored into digitalized manufacturing with a process-based design so that pharmaceutical companies can produce what they expect from the start. The right science-based tools work seamlessly with digitalized manufacturing lines to enable the iterative loop that ensures pharmaceutical manufacturing can continue to manufacture sustainably from the first phase”.

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