Table of Contents
An Intro to Pharma 4.0: Implementing Industry 4.0 in Highly Regulated Industries
Pharmaceutical and biotech manufacturers face a number of unique challenges in the digital era.
While new technologies have multiplied opportunities for process improvements, regulatory oversight has slowed adoption relative to other industries. Stringent requirements for documentation, data integrity, and process validation all create an environment where compliance can outweigh continuous improvement.
Nevertheless, manufacturers who act smartly and decisively can benefit. There are more tools for improving quality and efficiency than ever before. Many even promise to make compliance an automatic, seamless part of the quality process.
This guide provides a comprehensive overview of digital manufacturing for the pharmaceutical industry.
Throughout, we’ll review use-cases, technologies, and strategies for applying digital technology that you can use in your operations.
This is your roadmap for building digital capabilities in highly regulated industries.
Chapter One: What is Pharma 4.0?
Pharma 4.0 is a framework for adapting digital strategies to the unique contexts of pharmaceutical manufacturing.
In practical terms, it means more connectivity, more productivity, simplified compliance, and the marshaling of production information to respond to problems as they emerge.
The term was coined by the International Society for Pharmaceutical Engineers to envision a digitally mature pharmaceutical industry.
The ISPE’s plan is holistic, outlining priorities for the business, IT, and manufacturing throughout a drug product’s lifecycle.
Their conviction is that digitalization will help organizations achieve “business goals by operating faster, reducing costs, and being more competitive and agile”.
More than just an approach to digital technologies, Pharma 4.0 is also a means of transforming the manufacturing workforce. From connecting workers to more human-centric workflows, to shifts in company culture, humans are at the core of Pharma 4.0.
“[To] Manufacture pharmaceutical products with maximum product and process understanding, data integrity by design, efficiency and optimal resource allocation on the basis of full digital data transparency–to the benefit of the patient.” -ISPE
Many of the key points in the holistic model, however, are directly applicable to manufacturing.
For example, the pharma-specific maturity model anticipates:
- The elimination of data silos with better communication across the lifecycle of drugs
- A lower-touch relationship with regulatory bodies as data collection and sharing improves
- The elimination of paper-based processes
- A shift to risk-based regulation
- Improved agility, connectivity, and productivity–even in highly regulated facilities
Pharma 4.0 envisions a manufacturing paradigm that allows manufacturers to change and iterate, that connects resources and workers, and that ultimately produces more quality product with better patient outcomes.
Chapter Two: Steps to Pharma 4.0
Broadly speaking, there are six stages of digital maturity. With the least mature being elementary computerization and the most mature being self-regulating, intelligent facilities, these stages outline a path that all manufacturers can follow.
- Computerization – the first stage of maturity is simply to introduce digital technology to automate simple manual processes. The goal is to find repetitive tasks that would be better performed by computers and create the basis for digital infrastructure.
- Connectivity – Here, manufacturing expands IT infrastructure and lays the foundation to integrate IT, manufacturing, and business functions.
- Visibility – This is the area where many manufacturers will start to see substantial improvements. Connected people, machines, and processes create a substantial digital record of production that can be used to make real-time, data-driven decisions
- Transparency – With more data, new insights about complex systems become available. Advanced analytics find opportunities for improvements that were previously invisible.
- Predictability – Detail production records enable manufacturers to correct problems before they happen.
- Adaptability – This is the final stage of maturity. Here, systems anticipate problems and initiate the proper action by themselves. At their most advanced, these are autonomous, self-correcting systems.
We’re far from a reality in which pharmaceutical manufacturing lines detect problems and self-correct.
Still, this trajectory from a baseline of digitization and connectivity to sophisticated, predictive systems is one that manufacturers can take steps to achieve now. Indeed, with the right strategy, that future might not be so far away.
Pharmaceutical manufacturers can realize significant gains by finding small opportunities for digitization and beginning there.
Bringing Industry 4.0 To Pharma
Outlining a strategy for digital transformation isn’t a trivial task. Nor is finding small, scalable opportunities for improvement.
Now, with a destination in mind, the question becomes: How do we get there?
The answer is adopting an agile approach, privileging a steady evolution rather than a rapid revolution.
Chapter Three: Industry 4.0 Fundamentals
While Industry 4.0 is often defined as a suite of technologies converging on the modern shop floor, there are a few concepts that tie them all together.
The first is the Industrial Internet of Things. More than a technology, IIoT refers to the networking of disparate items, sensors, and people across a manufacturing facility. This connectivity creates a more holistic picture of manufacturing processes and helps to eliminate silos.
The other is cyber-physical systems (CPS). CPS are networks that combine human and machine inputs to create better communication and support between the different actors in a factory. In simpler terms, CPS are connected systems that help support humans on the shop floor by contextualizing their activity across the digital and physical domains of manufacturing.
What they are is less important than what they do.
CPS helps people make better decisions, find new opportunities for improvement, optimize the allocation of resources, and improve quality by creating more responsive working systems. With, CPS, humans work hand-in-hand with digital manufacturing systems.
Together, IIoT and CPS enable a bottom-up approach to pharmaceutical manufacturing. Hierarchical control models require more information before implementing changes. With IIoT and CPS, control is emergent.
By emergent, we mean new patterns emerge as digital systems operation. Specifically, the increased quantity and quality of information enables manufacturers to identify local problems in real-time, and to adapt their improvements accordingly.
Accepting emergence means accepting that we can’t have all of the answers prior to letting the system run and sampling its output. Working with emergence is key to creating value through evolution, not revolution.
Data Integrity by Design
Data integrity is one of the areas where Pharma 4.0 can contribute the most. Indeed, the ISPE outlines “Data Integrity by Design” as the desired outcome of digital maturity.
Nevertheless, documentation in the pharmaceutical industry is often paper-based and error-prone. Lack of standardization leads to data loss between research, validation, and production stages, and masks areas for process improvement. During manufacturing, engineers record machine states, batch information, and production schedules in paper forms. These logs are prone to transcription error, are labor-intensive to keep, and difficult to reference. Often, mistakes are caught too late, at the end of a process.
With Pharma 4.0 solutions they are caught in real-time. This makes it possible to manufacture with a Right the First Time approach and saves time in exception handling.
Chapter Four: Finding localized, scalable problems
The trick to implementing these concepts in practice is learning how to see pharmaceutical manufacturing problems from a different perspective.
Traditionally, changes have been large, and solutions comprehensive. This required marshaling a significant amount of organizational resources and energy around large, multi-year projects.
With Pharma 4.0, improvement projects need not be massive, costly endeavors.
It’s better to think in terms of localizable solutions that can be implemented quickly and scaled as necessary.
Many manufacturers, for example, might want to improve quality, decrease process variability, improve data integrity, and simplify complex processes like line clearance and machine changeovers. Trying to solve each of these problems with a single, top-down solution can lead to reduced efficacy in each area.
Modern Pharma 4.0 solutions work within broader quality management and manufacturing execution systems to give manufacturers a faster, more flexible means of approaching improvements. They can be configured and deployed quickly, and iterated as processes and target improvements change. What’s more, they automatically collect data while they run, helping to provide the holistic physical/digital picture of production necessary for the largest steps forward.
Chapter Five: Use Cases
Let’s look at some ways that manufacturers are already creating value with Pharma 4.0 solutions.
Electronic Log Book
Electronic logbooks automatically document relevant production information, streamlining a manual process while dramatically improving data integrity. These logbooks can compile and integrate information from machines and operators, expanding process visibility. Further, electronic logs can integrate photos, notes, reason codes, device history records, and locations providing a more holistic record of production than paper-based forms.
Electronic logbooks ensure that information is attributable, legible, contemporaneous, original, and accurate (ALCOA).
Because these logs are digital, they can be easily accessed to prove compliance.
Many line clearance processes are complex, time-intensive changeovers. With paper-based processes, workers may spend a significant amount of time looking for the next step or validating the execution of the previous one and less time progressing through the procedure.
Interactive, digital line clearance applications can make line clearance easier to navigate. Digital, IoT-enabled work instructions guide users through SOPs, increasing efficiency ensuring that work is performed correctly and validated automatically. The applications record how long each step of the process takes, improving process visibility, and enabling engineers to locate areas for process improvement. Because these apps are collecting and communicating data in real-time, engineers can view process status as work unfolds, leading to reduced downtime and more effective scheduling.
Electronic Batch Record
Batch record reviews require aggregating and reviewing a substantial quantity of manufacturing data and process documentation.
Much of the labor spent in the review process comes from identifying incorrect or illegible entries, and correcting records so that all production information is available for a given batch.
With electronic batch records, manufacturers can make data collection and validation a continuous, seamless part of the manufacturing process. Information about manufacturing processes is automatically collected as operators and machines work, and all data is thereby attributable, legible, contemporaneous, original, and accurate.
When it’s time for a batch record review, the necessary information is accessible and easy to read. Manufacturers can spend more time ensuring the quality of a product and less time correcting transcription errors. With more data available, it’s easier to flag items to review by exception.
In pharmaceutical manufacturing, the greatest barrier to process improvement isn’t always regulatory constraints. In many cases, it can be a lack of process visibility.
With IoT devices and human-centric manufacturing applications, manufacturers can break complex processes into their constituent steps, creating a granular, picture of how workers perform on the line. The applications let engineers track individual operators' performance at each step. This lets them identify situations in which more training may be necessary. It also helps engineers differentiate between poor operator performance and poor process design.
In our experience, many of these changes are incremental and can yield significant gains in quality and efficiency without triggering an audit or requiring revalidation.
Clean Room Monitoring
IIoT makes it possible to respond to changes in environmental conditions as they develop. Connected sensors can detect when conditions may exceed established thresholds, and alert operators to take the proper action before interrupting production.
Training for Regulated Environments
Many manufacturing processes require a significant investment in training. Training can be slow, as manufacturers have a difficult time replicating “real-life” production scenarios in their training programs. This leads to additional costs sunk in training, and quality can suffer if operators aren’t trained effectively.
Using manufacturing apps, manufacturers can design Pharma-specific training applications to get employees on the line fast. Engineers can break multi-stage processes into their constituent parts with targeted modules, and embedded media like videos and images help convey information to different styles of learners. If it’s not possible to take workers off the line during reskilling periods, training applications can be configured to facilitate on-the-job training (OJT).
Further, manufacturers can simulate processes in production settings by running apps in an “offline” mode. Here, training modules walk employees through a process and collect data on their performance, while governed execution mode makes sure that learners don’t impact production.
Big Data Analytics
Manufacturers generate a truly massive quantity of data in the course of operations. Yet most of this data isn’t used as the basis for production insights. This is because it can be too unwieldy or unstructured to be valuable (also referred to as Data Rich, Information Poor, or “DRIP”).
One of the promises of Pharma 4.0 is the enhanced interpretation of the data collected throughout a product’s lifecycle. With advances in AI and machine learning, systems are better able to parse and find connections within large data sets.
Chapter Six: Case Studies
It helps to see how these individual use cases come together to create value on the shop floor. Let’s look at a case study to see how one manufacturer used Pharma 4.0 tools and concepts to foster continuous improvement in a highly regulated environment.
Case 1: Improving Process Visibility in an FDA Compliant Facility
This manufacturer faced a challenge shared by many pharmaceutical manufacturers. Because their production took place in segregated clean rooms, they were unable to communicate effectively during production. Projects were allocated to rooms, and the engineers used static, visual markers, like colored magnets, to display room status.
This manufacturer had a difficult time tracking the progress of jobs through rooms while still complying with FDA guidelines for process documentation.
This manufacturer used a number of Pharma 4.0 tools to address this issue.
Tulip offered a lightweight means of improving visibility within a validated facility. Working with Tulip partners who specialized in deploying technology in regulated environments, this manufacturer digitized processes using a no-code manufacturing application platform. Instead of using magnets to track room status, the manufacturer used no code databases and visual dashboards to monitor and display the status of each room in real-time. IPads were placed outside of each room, letting workers log room status, and creating a digital record of production immediately available for analysis.
When room status changed, the manufacturing application system immediately alerted the next team, reducing wasted time between processes.
While this manufacturer scanned all necessary documents for compliance purposes, the information wasn’t available to inform process improvements. With the new system, the information immediately helped to identify bottlenecks. Given that this facility lacked the space for additional equipment, optimizing production processes was essential for maximizing value.
In the end, this company was able to balance GMP compliance and continuous improvement.
Case 2: Digital SOPs Cleaning Complex Continuous Manufacturing Equipment
Another manufacturer used Pharma 4.0 techniques to improve complex equipment setup. This included the disassembly, cleaning, and assembly of individual parts of its manufacturing line. This complex piece of continuous manufacturing equipment consisted of 16000 individual parts, and each stage of the manufacturing line took two weeks to clear. Instructions for line clearance consisted of 30 SOPs packaged in an 80-page document, leading to slow execution times and difficult validation procedures.
This company used digital applications to guide operators through the setup of the line. The application lets workers route directly to subtasks, eliminating the need to locate and reference steps within the proper SOP. This made it easier for new employees to learn the necessary steps needed to disassemble, clean, and assemble individual parts of the organization’s manufacturing line.
These digital work instructions eliminated paper from the line, and helped to record execution and validation data in the course of the cleaning process.
These tools reduced the process from 10 to 2 days and simplified reporting.
Chapter Seven: Conclusions
The pharmaceutical manufacturing industry is evolving at a rapid speed.
While the FDA and manufacturers both envision a world in which compliance is a lower touch, collaborative exercise, balancing continuous improvement with compliance will remain essential for years to come.
The promise of Pharma 4.0 lies in its ability to unlock new potential for productivity and quality while making compliance a seamless part of the manufacturing process.
Manufacturers who take the necessary steps to embrace a digital future now stand to benefit from seamless compliance, but it need not stop there. By adopting a Pharma 4.0 strategy, manufacturers can increase connectivity, efficiency, and agility.
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