Over-the-counter cold and flu medications can be hard to come by during peak respiratory virus season, but in recent years that has been taken to a whole new level. Meanwhile, certain antibiotics and antivirals are also in limited supply, and there is the ongoing shortage of prescription drugs like Adderall. In fact, drug shortages increased by 30% last year, largely due to economic disruptions.
Faced with such industry headwinds, from complex production challenges to ever-increasing global demand, pharmaceutical processors require advancements in smart manufacturing solutions that improve efficiency, accelerate production and optimize performance throughout the manufacturing lifecycle.
However, many pharma processors lack an effective digital transformation plan — and this gap is contributing to challenges in efficiently producing and distributing medicines globally. As demand for vital medicine continues to grow, pharma processors must make better use of digitalized processes or risk never fully solving their production issues.
The choice could not be clearer — despite these challenges, the pharma industry is ready to rise to the occasion.
Making up for lost time: Pharma’s recent digital revolution
Pharma has historically lagged behind other industries when it comes to digital transformation. Then came the COVID-19 pandemic: The global health crisis put a spotlight on the speed of pharmaceutical development, production and distribution — and the technologies supporting these vital processes.
Faced with unprecedented global demand, pharma processors embraced digitalization, not only to keep core operations running but also to streamline processes and boost productivity. In a recent industry survey, 74% of pharma professionals said the health emergency accelerated the industry’s digital transformation, with more than a third reporting the pandemic fast-tracked progress by more than five years.
Recent digital innovations have spurred significant progress in smart manufacturing: the use of advanced technologies, data analytics and digital processes to enhance agility, efficiency and performance across production lines, factories and supply chains. Although progress has been significant across the pharma industry, there is still a lot of untapped potential.
For example, artificial intelligence (AI)-powered predictive maintenance technology enables pharma processors to proactively monitor production equipment and manage operational health. IoT sensors, algorithms and automated processes provide proactive insight into equipment usage and alerts of impending breakdowns. Some manufacturers have embraced this approach and are recognizing the ROI, reducing time, money and resources spent on unnecessary maintenance.
These measures allow engineers to more quickly and efficiently replace and repair components and avoid mechanical failures, unplanned downtime and production delays. The result is reduced manufacturing slowdowns, maintenance cost savings and prevented disruptions to the entire value chain.
There is no shortage of smart manufacturing initiatives capable of providing similar benefits, whether it is process design modeling, integrated workflows, data sharing, scheduling tools or supply chain planning optimization.
Together, these innovations open up opportunities to improve product quality and yield, visibility into manufacturing operations and process efficiency — reducing costs and time-to-market for vaccines and other medicines. However, despite recent progress around digital initiatives, pharma processors still have a long way to go to achieve smart manufacturing and fix long-standing challenges.
3 pitfalls pharma processors should avoid
Although more pharma processors are prioritizing digital strategies today, headwinds threaten to derail digital transformation plans and progress toward smarter manufacturing. AspenTech’s report, “Seizing New Opportunities: Pharma’s Roadmap for Smarter Manufacturing,” created in collaboration with FT Longitude, underscores common problems plaguing pharma manufacturers.
As manufacturers move forward with digital transformation journeys, here are the top three organizational pitfalls to avoid"
1. Succumbing to data silos
There is more data at manufacturers’ fingertips than ever. From insights that drive design and process optimization to better planning and decision-making throughout the production lifecycle, data analytics offers organizations vast possibilities and important opportunities.
But data insights and analytics need to be connected across functions and make information more accessible. Unfortunately, that is not the reality at around half of companies who say poor connectivity and data silos impede cross-functional collaboration — and the problem is even more pronounced among the largest pharma businesses.
The same challenges were reflected in AspenTech’s 2021 industry survey: Nearly half of pharma firms said business decisions were less informed by data their company already holds. To realize data’s full potential, focus on dismantling data silos, fostering collaboration and creating connections between data sources across the organization.
2. Allowing agility to go stagnant
The past few years have shown agility and innovation are not just a competitive advantage — they are a business necessity to adapt to disruptions and fast-changing markets. Yet companies still struggle to improve operational agility and sustain it over the long term. Even the most innovative companies fall victim to stagnation.
That is likely why operational efficiency and agility rank as the leading digital transformation goals for modern pharma companies, with streamlining product innovation as the runner-up. It is clear that agility is a major focus for manufacturers, but it is less clear how they can achieve it.
One way to start is by implementing continuous manufacturing and process intensification, in which a company manufactures products in a nonstop, end-to-end production line that eliminates hold times between batches, minimizing resource usage and increasing productivity. These improvements allow companies to capitalize on new revenue opportunities — including the growing market for biologics and cell and gene therapies — that require high levels of flexibility and manufacturing agility.
3. Putting AI on the back burner
In 2021, half of pharma companies recognized the value AI offers their organization. Yet a year later, less than one in three companies have prioritized AI and machine learning (ML), according to our findings.
It is a startling finding, especially given how many pharma companies are currently struggling with skills gaps and recruiting talent. AI and ML solutions actually help replace missing capabilities and address labor shortages by automating high-volume, low-complexity tasks instead of relying on manual inputs. Moreover, AI and ML are the basis for many other smart manufacturing initiatives, including predictive maintenance.
Contrary to most pharma companies surveyed, larger businesses (those with over $1 billion in annual revenue) rank AI as one of their top three digital transformation priorities. Even organizations that do not fall into that category need to prioritize investing in AI and ML as a long-term strategy. Putting off AI initiatives will only put businesses further behind their competitors — and likely cost them far more in the long run.
Pharma’s digital transformation is long overdue — but it is happening now. Recent economic and production issues demonstrate that these challenges will not go away anytime soon. And in the face of the ever-growing demand for pharmaceuticals, it is up to manufacturers to plan carefully for future needs.
Our research shows many challenges have been a thorn in the side of manufacturers long before the pandemic. However, the findings also reveal newfound urgency to solve these problems and to prioritize technology strategies that help. The pressure is on — are you ready to meet the challenge?
Heather Lawson is the senior industry marketing manager, pharma at Aspen Technology, Inc. She is a product marketer with experience across multiple industries, from electronics manufacturing to life sciences. She currently focuses on the pharmaceutical and biotechnology industries at AspenTech.
Aspen Technology, Inc.