This fourth stage, which is currently evolving before our own eyes, is the one that is becoming commonly referred to as Industry 4.0. It would even seem that Industry 4.0 is developing into subsets to support various vertical industries with one of the first being the pharmaceutical industry. The new buzzword for this that appears to be gaining some traction is Pharma 4.0.
The term ‘Industrie 4.0’ was first coined by the German federal government in a national strategy to promote the computerization of manufacturing. It represents the fourth industrial revolution on the way to an internet of things, data, and services. Decentralized intelligence helps to create intelligent object networking and independent process management, with the interaction of the real and virtual worlds representing a crucial new aspect of the manufacturing and production process.
The basic principle is that by connecting machines and systems, we can create intelligent networks along the value chain that control each other. For example, machines would be able to predict failures and trigger maintenance processes autonomously, or self-organize logistics that react to changes in production. Industry 4.0 technologies include many of today’s buzz-words, like big data, advanced analytics, virtual reality, the cloud, internet of things (IoT), and machine-to-machine communication (M2M). In the past decade, these technologies have swept across the globe, as manufacturers across the world recognize the value of Industry 4.0.
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.
The Diagnosis Before the Prescription
There are few people that would fault the vision, but a problem is emerging in the way that the principles of this industrial revolution are being implemented. The potential for Pharma 4.0 is so huge, and so wide, that a lot of pharmaceutical companies rushing to adopt the technology haven’t first paused to figure out the root goals that they are trying to achieve, and what main problems they are trying to solve.
If these two questions are not answered before embarking on the path to Pharma 4.0, the route to follow is unclear, and many companies are losing their way. The key technologies required for digital transformation cause radical changes in the business processes of any company, and those changes need to be discussed and understood before they are undertaken.
For example, key stakeholders in the business need to consider the company’s culture and how to help employees (at all levels) to deal with change. This involves overcoming a general reluctance to change that is typical of the human makeup, as well as training employees to ensure they are qualified to use the upgraded plant. Reassurances over continued employment once digitization is achieved need to be made or, if the upgrades are likely to lead to redundancies, the company’s management needs to decide whether people can be redeployed in the new system (as is often the case), or whether they will need to be let go.
Pharma 4.0: Navigating the Landscape
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. However, as more databases move on to—or connect with—the cloud, security issues are commonly cited as a barrier to fully embracing the new technology, and it’s important to ensure that all databases are protected sufficiently.
Some software technologies necessitate the moving and/or duplication of historian data or other data sources. This creates its own problems, both in terms of external data security and internal validation of the data. If a validated database is duplicated, does it need to be re-validated? These additional drains on IT and other resourcing need to be considered and discussed—sometimes an alternative approach is available that avoids these issues, but still allows the company to move forward with digitization.
New technology needs to be reliable and stable for critical M2M, and it needs to meet any applicable regulations to the industry sector concerned.
Of course, the economic benefits of this considerable investment need to be justified, and an expected return on investment (ROI) for each stage should be estimated. Investments need to be prioritized to ensure that those providing the greatest ROI are implemented first, and all changes need to be based on strategic plans to place the company at an advantage, or at the very least maintain a current favorable market position, in the future.
Continuous Process Verification
Pharmaceuticals represent one of the most regulated industries, and thus, provide a good opportunity to demonstrate an optimal approach for digitization. Every aspect of a pharmaceutical product’s development, testing, manufacturing, packaging, marketing, storage, distribution, and use is subject to scrutiny—at every stage, data is captured, analyzed, and reported.
Pharmaceutical companies often adopt Continuous Process Verification (CPV), through which all data generated during product manufacturing can be continuously assessed and validated against regulatory guidelines, to ensure they stay within the parameters documented when those processes were validated. Hundreds—sometimes thousands—of variables must be monitored to verify that they remain within the specifications established for this process. This is an ideal application for Industry 4.0 technology.
There are four key ways in which digitization can contribute to CPV.
Analytics: Statistical process control (SPC) techniques develop the data collection plan and statistical methods and procedures used in measuring and evaluating process stability and process capability.
Risk-based real-time approach: To verify a process that produces material which meets all critical quality attributes and control strategy requirements.
In-line, on-line, or at-line controls: To monitor process performance and product quality.
Quality attributes: Of incoming materials, in-process materials, and finished products
Sometimes pharmaceutical companies find challenges related to consistent product quality. Data analytics technology can often be utilized to address such issues to improve the quality of their product, manufacturing processes, and profitability.
Analytics is Key
One pharmaceutical company was having problems with sub-standard raw materials that were not being detected until a batch of product had been completed. Data analytics technology was used to provide a single dashboard view of the process, from incoming raw materials to outgoing product (Figure 2). The dashboard clearly showed critical parameters with real-time reporting of any issues likely to affect the product under manufacture. A simple green/red dashboard enabled operators to quickly and easily see which parameters required attention, so any issues could be dealt with before they affected product quality or caused shut-down. Underlying the success of this project, a clear goal had been set, addressed, and completed, setting the company on its path to Industry 4.0 in a productive way.
Other benefits of digitization include the continual assurance of process control, and the ability of data analytics to quickly detect any deviations from expected parameter limits. This automatic monitoring and control enable pharmaceutical companies to offer continuous data that are validated against regulatory guidelines, helping them to comply with the rigorous requirements associated with their industry sector.
The technology also automatically generates annual reports, or reports required for site inspections by regulatory authorities, potentially saving hundreds of man-hours every year.
The Path to a Digital Transformation
Our world is becoming increasingly digitized, and this can be a good thing—improved efficiency, enhanced quality, and better company compliance with ever-increasing, data-related regulatory requirements. However, before embarking on the journey to Industry 4.0, companies need to pause and consider the objectives of the exercise and set clear goals that will guide them on the way to the successful implementation of novel technologies. There is no shortage of technologies, but choosing the one that is going to have the greatest positive impact on your company, in the area that you most need it, is an obvious crucial decision.
Determining how to approach your technology choices can be resolved by creating a step-by-step process with specific milestones for each activity. This should be a team effort with relevant constituent participation. The first step is to identify the problems you hope to solve and what challenges are in the way. Second, identify the team. Who has the technical expertise to identify the parameters of importance? How is the IT going to help access key data sources?
Then take a look at the people and technologies involved. What talent and technologies are needed? For example, if looking to maximize existing technologies and data sources, what platforms are compatible with current equipment and will be scalable going forward? Finally, it’s recommended to begin with a pilot project and then refine its implementation, which will speed roll out to other sites. All of these steps can help avoid potential problems and set your company on its path to Pharma 4.0 to create a valuable and industrious new era of manufacturing.
