Decoding Pharma 4.0: Bringing Industrial IoT to Pharma

Get Started with Pharma 4.0 Smart Manufacturing

Many pharmaceutical companies today find themselves in a similar situation to what they experienced in the early 2000s. They know that tools, methods, and technologies exist to help them eliminate waste, volatility, and unnecessarily difficult procedures (while simultaneously increasing profit margins and product quality). But given that Lean was difficult for pharma companies to successfully implement, how can Pharma 4.0 and smart manufacturing solutions offer different results? 

Compared to other industries, the pharma industry was a relatively late adopter of Lean production methodologies. Pharma profit margins “were at historic highs” in the 1990s and many companies focused their “money and resources on R&D rather than operations.” The landscape started shifting in the 2000s and early 2010s as the patents for many brand-name drugs expired. Additionally both government regulations and society pressured “pharmaceutical companies to reduce costs and improve quality” as globalization spiked the demand for accessible pharmaceuticals. 

Many pharma companies found themselves in a difficult situation: after years competing on new product development, their operations were not optimized to compete on price. The Lean methodologies that brought groundbreaking changes to the automotive, computer hardware, and healthcare industries weren’t realized in the pharma industry. In pharma, Lean was often implemented in small, isolated instances rather than widespread across the entire pharma landscape. 

Even with the historical challenges that pharmaceutical companies had with Lean, there are still plenty of opportunities to implement Pharma 4.0 tools successfully.

What is IIoT?

In its simplest form, an Industrial Internet of Things (IIoT) platform aggregates real-time data from hardware, software systems, sensors, and other data points into a centralized environment. This centralized data hub can usually be accessed by a wide group of users, bridging the gap between systems, people, and machines. Oftentimes, this centralized system lives on a cloud, but it can also exist also on-prem.

IIoT platforms can help manufacturers improve decision-making by improving connectivity, control, forecasting, and data analysis. Manufacturers typically seek an IIoT platform when they are looking to gain insights into the factors that impact quality control, downtime, production (output), and waste. An IIoT platform can also bring cross-departmental visibility into what’s going on in your facility.

What is Quality 4.0?
Given the emphasis on pharma product quality, pharma companies may be familiar with the term Quality 4.0. According to ASQ, “Quality 4.0 is a term that references the future of quality and organizational excellence within the context of Industry 4.0.” In other words, Quality 4.0 is the specific application of Industry 4.0 technologies to enhance quality management practices. 

Industry 4.0 utilizes digital technologies—such as an IIoT platform—to meet changing requirements by adjusting or implementing new processe, made possible by data. As such, it is important to collect and centralize the most important data at your organization. The value of data may not be immediately clear when you first start your digital transformation journey. When you can contextualize production data, it is useful for a wide variety of use cases including predictive maintenance, product optimizations or reducing waste. 

No matter which cloud platform you use—on-prem, public cloud, or a private cloud—the biggest opportunity is the ability to directly transform your raw data into information. Once your data is aggregated from multiple sources, an IIoT platform immediately benefits teams by providing instant visibility into your processes. In the future, you also have the opportunity to leverage the power of Machine Learning, AI, and Big Data discoveries. 

Digital transformation is a marathon, not a sprint. Some data may help you make immediate improvements to measuring the status quo or predicting excesses. Other data will reveal its value in the long term as part of continuous improvement initiatives.

Why Should Pharmaceutical Companies Embrace an IIoT Solution?

An IIoT platform can help pharma companies address one of their biggest challenges today: a lack of connectivity. Pharma companies have plenty of data on their processes but many don’t have the capacity to connect to their data or access it remotely. This lack of connectivity makes it extremely difficult to optimize processes, improve quality across multiple manufacturing sites, or implement a global Pharma 4.0 plan. 

In Sparta System’s “2018 Pharma Quality Outlook, “73% of respondents said maintaining compliance was a top quality objective.” In the same report, though, nearly one-third of respondents saw data analysis and reporting capabilities as a major obstacle to meeting quality objectives. It is extremely difficult to have ambitious organizational goals around quality and compliance if quality teams do not have an effective way to view, analyze, or implement company-wide process changes using data.

This contradiction between company goals and available tools probably sounds familiar. Conflicting priorities between operations and senior management is widely accepted as the reason for a “lack of successful implementation and success of virtually every type of business improvement initiative.” As noted in our white paper, “The Five Pillars of Digital Transformation,” the most successful corporate goals and initiatives are those that are driven by top management: not individual teams. And yet, corporate leadership often asks teams to take on new initiatives in isolation without providing an overarching framework that supports new methods or technologies.

Quality teams can help make the cost-savings changes that upper management wants to see, but only if they are given the right tools, training, and strategies to make those decisions. It is impossible for quality teams to improve production processes unless they have access to the right data. Braincube’s IIoT Platform can allow teams to remotely connect to multiple structured data sets simultaneously instead of just a single production process. A more holistic view of your production process gives your operations and quality teams the right tools to identify variables that lead to reduced costs and improved product quality. 

Additionally, the funds saved by implementing Pharma 4.0 practices at the operational level can help drive the C-Suite’s top-of-mind goals (for example, improving price margins or investing in more R&D). In this sense, every level of your organization benefits from having a centralized, structured, remote data hub. 

Braincube helps to prove by data what we should do. This enables us to increase our productivity or quality.

Jean-Christophe Glez, Powder Development Engineer at Aubert and Duval

Pharma 4.0 goes beyond a set of tools: it’s a holistic approach to transforming the way your entire organization operates. Unlike Lean practices, which may be mistakenly implemented in specific departments instead of across the organization, an IIoT platform is designed to give every user access to the data they need to perform their role. (Like any corporate initiative, though, it is vital that upper management reinforces the value of Industry 4.0 tools and technologies if company culture shifts are to be successful.) 

An IIoT platform provides more than just data connectivity and analytics. Effective reporting tools, such as Braincube’s Dashboard app, make it easy to quickly generate reports for meetings or cross-departmental brainstorming sessions. Democratizing your company’s entire data set helps everyone see the same information. This reinforces data-driven decision-making and gets everyone speaking the same language from the same validated data sets. You can also easily track KPIs, expedite daily tasks, and provide updates to upper management with just a few clicks.

The Role of Digital Twins in Pharma 4.0

There are many types of Digital Twins: they can be built by asset, by process, or even by human. Ideally, a Digital Twin gives you a look into your process so that you can improve.

A Digital Twin built by Braincube is a contextualized data model of one of your production lines.  We extract data from your existing systems (ERP, Historian, etc.), create a time-based association for each variable, and build a dynamic model that follows the end-to-end flow of materials. This allows you to move from time-based association analysis into production-based analysis. As your organization advances along your journey to digital transformation, A Digital Twin will continue serving as the backbone of advanced analysis and automated process optimization by providing you with structured, cleansed data for analysis. 

Since Braincube’s Digital Twins are built by product, batch, or serial number, teams get product/batch traceability of every single variable that went into creating each individual product—from raw material to finished good. This contextualized data set is built using data, input from SMEs, and Braincube’s Digital Transformation Map (which has been used by hundreds of companies to transform their data into information). 

This makes it possible to understand the impact of each production step, which is especially beneficial for batch-produced products like pharmaceuticals. You can also track partially-built products that may come from other sites in your supply chain, which can help improve your margins by isolating damaged products before it’s too late.

Merging Quality and Compliance with Pharma 4.0

The same Quality 4.0 tools also make it easier for pharma companies to remain compliant. Reporting tools can help quality teams identify batch variability and uncover which process variables have the greatest impact on product quality. Using an IIoT platform, engineers and technical leads can push recipe or process changes out to operation teams. 

Just as government regulations and compliance drive the pharma industry, it also plays a major role in the aeronautics industry. Aubert & Duval, part of Eramet Group, manufactures metal parts for aircrafts. After the alloys are melted and forged, they undergo a series of processes that usually take place at different facilities across several weeks or months. At each step of the production process, the parts can be split across several machines or may follow the same line. Either way, traceability of each individual product is required by aeronautics regulations (under the EN9100 standard for aerospace safety and reliability).

These safety standards mean that the biggest challenge is linking the thousands of production parameters for a defined product, ranging from the first step of raw material up to the delivery of the final product. Aubert & Duval adopted Braincube to increase the traceability of their complex and long production cycle.

Braincube built a contextualized data model (Digital Twin) to integrate and analyze all the production data scattered in various systems, at various plants. Using the structured Braincube databases, the Aubert & Duval team can now analyze previous, current, or future production conditions—using millions of pieces of data—at a moment’s notice.

The solutions drawn up by the technical teams were quickly transferred to operators. As a result, huge improvements emerged everywhere: a 32% increase in the stability of operative standards; an 18% decrease in defects on a reference product; and an increased yield of 1.3.

32% increase

in the stability of operative standards

18% decrease

in defects on a reference product

1.3

increase production yield

Improved product traceability makes it easier to adhere to regulatory requirements or adjust to changing compliance guidelines. It also makes it easier to apply deep insights from your production processes, which can help your teams or report on achieve improved product quality.

Summary

There are tremendous opportunities for pharmaceutical companies to leverage Pharma 4.0 and the promises of industrial transformation. However, realizing these opportunities requires meticulous planning, strategy and implementation. It’s important not to overlook the human teams that will be responsible for the successful rollout of a new technology and strategy.

Building a holistic strategy for Pharma 4.0 is critical in driving progress forwards. Pharma companies want to avoid the disappointment many experienced with Lean stalling. With so many IIoT vendors and solutions crowding the marketplace, it’s beneficial to build a Digital Transformation Roadmap that considers the enterprise need for data consumption and optimization, while also empowering end users.

In many ways, pharma leads the world in innovation and quality control. Even so, there is still untapped potential from making use of the right production data to further optimize, understand, and improve processes using Pharma 4.0 tools and strategies.


See IIoT in Action

Read case studies from Chemical, Food, and Pharma companies using Braincube’s IIoT Platform.

Transform your data.
Accelerate your performance.

Speak with an expert