How is digitalization improving pharmaceutical manufacturing?

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  • Nov 24,21
Digitization in pharmaceutical industry practices can bring numerous benefits. However, for digitization to have the best outcomes, company leaders must take the time to determine what challenges exist and how tech could overcome them, says Emily Newton.
How is digitalization improving pharmaceutical manufacturing?

A push towards increased digitization in pharmaceutical industry practices can bring numerous benefits that boost profits, increase efficiency, and reduce errors during manufacturing and beyond. Here’s a fascinating look at what pharmaceutical technology can do.

Providing better visibility
Many efforts to apply technology in pharmaceutical operations include big data and Internet of Things (IoT) sensors. Then, people in a plant can see precisely what’s happening within the factory.

That advantage can help them address equipment abnormalities before the problems cause production stoppages. The combination of sensors and data analysis software also enables monitoring output and pinpointing bottlenecks or seeing where the need for process improvement exists.

Besides getting more details about current situations, digital technologies allow assessing future impacts and mitigating them. One study suggested pharmaceutical companies could lose 38% of a year’s earnings from a decade of supply chain shocks. However, digital models reveal a company’s vulnerabilities and help leaders prepare for the future to prevent adverse outcomes.

Giving enhanced process control and productivity
Pharmaceutical technology often includes automation. Figuring out the best processes to automate is not straightforward, but it can bring numerous advantages. Automated machines excel with repetitive tasks. For example, pharmaceutical companies often use parts washers to clean various components. Those machines have several automated cycles that run with limited human intervention, giving people more time for other duties.

There’s also an ongoing trend of using robots to achieve digitization in pharmaceutical industry tasks. The results of a recent poll suggest that those machines will remain relevant in the sector for a while. More specifically, 50% of those polled believed it would take more than five years for robotics implementation in the pharmaceutical industry to peak.

Packaging is one common use case for pharmaceutical robots. For example, these machines may open and fill bottles, fill the containers, place products onto pallets, and more. Some robots are specially designed to handle vials or other unusually shaped packaging, too.

Accelerating drug development and distribution management
Scientists are understandably interested in using artificial intelligence (AI) to reveal the most promising new drugs. Research and development is an early phase of pharmaceutical manufacturing, but a critical one. For example, AI might pinpoint the drug formulations most likely to succeed in clinical trials. It could also show whether medications used to treat certain diseases might also work well for unrelated conditions.

Perhaps that’s why four pharmaceutical companies collaborated to found a new AI innovation lab to pursue drug development and discovery. The blockchain is another digital technology gaining attention in recent years. For example, a team at the University of Copenhagen created a blockchain platform to benefit both manufacturers and patients who receive the respective medications.

One feature of the platform allows a patient to scan a code and verify that their medication is not counterfeit. The person can also choose which data to provide about themselves so that AI can determine the optimal dosage schedule for them. Also, the tool could give manufacturers an alert if someone tries to register a unique medication code on the system more than once.

Assisting with operational changes and improvements
Technology in pharmaceutical industry processes often includes digital twins, which are virtual representations of real-life assets. For example, a company may have a model of a piece of equipment, a single part, or an entire facility. The hope is that digital twins can help pharmaceutical manufacturers assess the impact of process alterations before moving ahead with them.

In one case study, a pharmaceutical company utilized a digital twin to simulate chemical mixing processes. That approach allowed them to test several variations to optimize the outcome. Besides cutting costs and minimizing waste, digital twins could help bring new products to the market faster, benefiting patients and providers, as well as the drugmakers. Additionally, if a process does not turn out as expected, the digital twin can pinpoint where and when things went wrong.

When decision-makers want to bring new equipment into a facility, start producing a new drug, or make other substantial changes, the pharmaceutical technology provided by digital twins is instrumental in helping them figure out the best ways to do those things with minimal disruptions. Plus, a digital twin can give insights into all parts of the supply chain so that companies can meet expectations and minimize delays.

Digitization in pharmaceutical industry practices brings competitiveness
These examples highlight why digitization makes sense for entities in the pharmaceutical sector. Strategies and technologies like those described here can help companies pursue continuous improvement and steer clear of many of the issues that could otherwise disrupt production or harm profitability potential.

However, for digitization to have the best outcomes, company leaders must take the time to determine what challenges exist and how tech could overcome them. Plus, giving people at a production facility enough time to get used to new digital tools or processes will increase the likelihood of such investments paying off quickly and over time.

About the author:
Emily Newton is a tech and industrial journalist and the Editor-in-Chief of Revolutionized Magazine. Subscribe to the Revolutionized newsletter for more content from Emily.

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