Why digital technologies are seeing lift-off in pharma

While the pharma industry has been slower to adopt digital technologies than other less-regulated sectors, many pharmaceutical companies making aggressive digital investments are finding their investments are paying dividends. Though comprehensive digital-based programs can cost roughly $50 million to $100 million annually for two to three years, according to McKinsey, they can lead to improved quality, increased efficiency and resilience, and empowered employees.

Integrating information technology (IT) with operational technology (OT) has emerged as a pivotal theme in the smart manufacturing domain. “Imagine IT and OT as circles overlaid with each other,” said Yvonne Duckworth, senior automation engineer at CRB Group. “That centerpiece of those two worlds together is one of the fundamentals for smart manufacturing.”

Neither IT nor OT is new. Harvard Business Review first used the term “information technology” in 1958 in an article forecasting what management would look like in the 1980s. The research and consulting firm Gartner coined the term “operational technology” in 2006 to refer to hardware or software used in industrial settings.

Traditionally, professionals working on IT and OT were cordoned off from each other. But in the pharma space, they have begun to work more closely with each other. “In the past five years or so, IT is now in all the project meetings,” Duckworth said.

The collaboration between IT and OT teams facilitates connectivity between disparate types of digital technologies. “It allows companies to put in smart manufacturing infrastructure,” Duckworth said. In addition, companies that have successfully brought the IT and OT domains together have more data and can thus make more data-driven decisions and deploy analytics for predictive purposes.

The consulting firm McKinsey recommends that pharma companies embed talent strategy in operations strategy, moving away from an HR-driven hiring strategy to one more focused on long-term digital maturity goals.

Additionally, synthesis IT/OT is enabling pharma companies deploying smart centers to move toward adaptive decision-making models, said Niranjan Kulkarni, senior director, consulting services at CRB. The two teams can work together to use intelligent devices to generate data for improved decision-making. “That’s the basis of smart manufacturing,” Kulkarni said.

As pharma companies work to continue bridging the gap between IT and OT, it can be invaluable to find professionals with expertise in both domains. “It is still hard to find IT/OT people, but they are out there,” Duckworth said. “It’s a unique skill set, but I’m seeing more of them now.”

Digital technologies’ deployment occurs in stages

One framework to chart industrial companies’ evolution from pre-digital to fully digitally enabled is BioPhorum’s five-stage model.

1. Level 1: pre-digital.
2. Level 2: digital siloes.
3. Level 3: connected plant.
4. Level 4: predictive plant.
5. Level 5: adaptive plant.

It is a significant transition to scale digital technologies from Level 2 to Level 3. “Based on the companies that we work with, more of the larger pharma companies are around Level 3,” Duckworth said. “They’re already connected. They already have their data stored and in place but want to move to Level 4, which is predictive.”

Some of the most ambitious companies are targeting Level 5, according to CRB’s most recent Horizons: Life Sciences report. “I think that shows a stronger appetite for some firms to want to get to that Level 5 autonomous level, even if it’s just one part of their facility,” Duckworth said.

ISPE and its members have also created a pharma-focused roadmap for Industry 4.0. “The ISPE Pharma 4.0 Special Interest Group recognized that other industries were moving faster than the pharma sector and identified a team to assist pharma companies in moving ahead and not just look at Industry 4.0 like an IT project,” Duckworth said. The goal is to use a holistic approach when deploying Industry 4.0/Pharma 4.0 concepts. The idea is to consider not just the technology but the impact of digital initiatives on the workforce, the organization at large, processes and culture.

AI and Big Data continue to gain ground in pharma

A growing number of pharma companies are using predictive analytics on the shop floor. Some companies installing new digitally-enabled equipment are aiming to reach Level 4 of the digital maturity model. “They can put additional sensors on equipment and be able to predict problems before a piece of equipment has a problem,” Duckworth said.

While many drug companies are working to make their plants more predictive in downstream processing, Big Data is also finding increased use upstream in drug discovery. To illustrate its promise, Kulkarni said to imagine a sheet of paper with millions of dots on it — each dot representing a drug candidate. “The models are now evolving, and humans are working closely with artificial intelligence as part of the deep learning process to narrow down a select pool of candidate molecules quickly,” Kulkarni said. As a result, the process can streamline the drug discovery process, winnowing a million candidates into a handful in a relatively short time. “It’s not only on the manufacturing side that you see the application of AI/ML,” Kulkarni said. “It applies upstream in the drug discovery process and anywhere between.”

Kulkarni observes that “artificial intelligence” is often used as a marketing buzzphrase. “Not everything is AI,” he said. “Pattern recognition, for instance, is not intelligence.”

Kulkarni sees three hierarchies in the AI domain — machine learning, neural networks and deep learning. A growing number of pharma companies are experimenting with deep learning, which allows machines to interact with humans. “Both of them are making decisions together, trying to allow each other to learn,” Kulkarni said. While deep learning has yet to be widely applied in smart manufacturing, it is gaining ground in drug discovery.