Driving Pharma/Biotech Capacity With Smart Manufacturing
By Laks Pernenkil, Deloitte
In pharmaceutical manufacturing, managing constraints to keep production flowing is a perpetual and complex challenge. When one limitation or challenge is addressed, another emerges elsewhere in the network for different reasons. Facing issues around regulations, market dynamics, sudden stoppage of pipeline products, or a striking increase in product approvals, how the enterprise reacts and the tactics it uses can yield varying, sometimes suboptimal outcomes. This can impact not just production and competitiveness but, more urgently, the supply of pharma products that support patient health outcomes.
Today, there are some common strategies for resolving constraints, and they raise different considerations for cost, time to value, and time to remediation. Facing a range of challenging issues, it is time for pharmaceutical manufacturers to consider a new approach to capacity management, one that can not only resolve today’s challenges but also position the enterprise to drive innovation and resilience in the future.
Traditional Strategies For Constraint Resolution
In the past, addressing constraints in pharmaceutical manufacturing has largely followed three common strategies.
One approach is to make the financial investment and commitment to build a new facility. This could take the shape of building a new greenfield site (often requiring more than a year to complete, under the best conditions), or it could take the shape of retrofitting a brownfield site, which may be accomplished in a somewhat shorter time frame, often nine to 12 months. The brownfield path is a time- and resource-intensive solution, and while the outcomes support improved constraint management, manufacturers may not have the time, funding, or organizational buy-in to take this approach, particularly as constraints continue to pop up and disappear across manufacturing networks.
Another common approach is replacing antiquated lines or trains of equipment. Depending on the active ingredient or pharmaceutical drug being manufactured, companies may integrate more modern equipment and systems to maximize capacity. The challenge in this case is that replacing equipment requires adjustments to processes, training, facility layout, and all the considerations that come with upgrading the line, and these investments need to deliver the return and value expectations to make economic sense. In addition, an important consideration for replacing active lines is the amount of time the line will be out of commission, which puts supply pressures on products manufactured in that line or train of equipment.
A third approach is continuous improvement in releasing capacity and driving manufacturing efficiencies. This is the ongoing process of identifying waste and capacity constraints and taking corrective action in the infrastructure and surrounding processes. While these continuous improvement strategies are sound in theory, one common challenge in practice is that this can lead to a mix of misaligned or poorly augmented management processes, which could ultimately reduce capacity, put strains on efficiencies, and drive down uptime.
While these three traditional approaches have their merits, they are not devoid of risks and challenges. In addition, the management culture, strength of governance processes, and return on investment expectations drive the success or failure of these strategies. To remain competitive and impact the bottom line, manufacturers need an approach to constraint management that is sustainable and enables faster resolution. Fortunately, there is a better way.
A Smart Manufacturing Approach
A productive way to consider capacity management is through the lens of smart manufacturing. By using a constellation of advanced technologies (e.g., sensors, machine analytics, digital twins, predictive quality, next generation automation, and supply and demand control tower), manufacturers can marshal their digital capabilities to solve for and actively manage capacity. A smart manufacturing approach can be leveraged in three vital ways to address capacity improvement.
- Sense and react – Most pharmaceutical manufacturers create terabytes of rich data that is not always used to its greatest potential. With sensors and enabling infrastructure in a smart manufacturing setting, manufacturers can digitize analog data and leverage artificial intelligence (AI) and machine learning (ML) to sense issues or constraints in real time and either make (or even autonomously take) remediation actions to resolve the constraints as they emerge. This also supports monitoring for cybersecurity threats (another potential constraint), as anomalous data from connected assets and throughout the tech stack can be monitored for vulnerabilities or compromise. When biopharma manufacturers bring these diverse inputs and leverage advances in digital technologies to respond to external and internal drivers of change, they can effectively address capacity constraints in their network.
- Capture and retain knowledge – Across the manufacturing network, there is often a great deal of implicit and explicit knowledge in human capital, in the way the processes are executed, and in data and untapped information in systems and tools. Biopharma companies can capture this knowledge by leveraging smart manufacturing capabilities. For example, infrared video analytics of operator movements, combined with AI/ML algorithms, can help capture how to best perform an operation to maintain consistency. For another example, lab analysts using interactive eXtended reality (XR) tools can capture how best to execute a lab quality test and update standard operating procedures. In these cases, smart manufacturing technologies enable the capture and digitization of implicit and explicit knowledge. As generative AI capabilities start to be tested in manufacturing for process optimization, improvement in maintenance intelligence, and even factory design and layout optimization, solutions to day-to-day constraints can be easily queried, leading to improvement in overall plant throughput.
- Optimize and transform – One of the most powerful advantages of smart manufacturing technologies is the capacity to use digital twins to experiment with and optimize products, processes, the workforce, and the supply chain in a digital space. In this, digitized constraint scenarios can run and fail, giving the enterprise the ability to identify the optimal solution before deploying it to the plant network. This is a fundamentally different way of arriving at the most effective solution before executing it. An additional benefit is that when smart manufacturing technologies are adopted, the enterprise is positioned to drive end-to-end performance and lead-time improvement in bringing molecules to market faster and cheaper by using digital twin technology to innovate and iterate in the digital space before physical action is taken.
With these capabilities, emerging capacity constraints are identified and solved in near real time, knowledge is digitized and accessible, and resolutions are perfected before deployment. The result is an agile, adaptive plant network that approaches capacity management with the full power of smart manufacturing technologies and processes. The benefits cascade beyond just solving for constraints. More broadly, a smart manufacturing approach can prepare the business to manage future complex challenges as they emerge, access and compete in new markets, and lead the future of pharmaceutical manufacturing.
Adopting a combined traditional continuous improvement approach enabled by smart manufacturing technologies is a clear path for assurance of supply. The journey to smart manufacturing operations requires an organizational and cultural shift from legacy linear thinking with experience-based decision-making to knowledge-rich, complex systems thinking with multiple simulated scenarios informing the best path for constraint resolution. The transformation road map can be complex, requiring best-in-class platforms, AI capabilities that make enterprise data actionable, a trained and culturally ready workforce, and manufacturing and business processes tuned to the new smart manufacturing approach. When adopting and deploying smart manufacturing technologies, the enterprise also will contend with aligning operational priorities, meeting regulatory compliance challenges while delivering transformative change in the way manufacturing is performed. Successful companies have unambiguous senior operations leaders as sponsors and a clear vision for the future state that everyone is working to achieve.
To be sure, it can be daunting at the outset. However, as pharmaceutical companies capitalize on the benefits of smart manufacturing, they will discover that the advantages and value of this better way to maximize capacity and manage constraints is impactful when meeting the needs of the patients they serve.
Copyright © 2023 Deloitte Development LLC
About The Author:
Laks Pernenkil is a principal and practice leader of Deloitte’s U.S. Life Sciences Product and Supply Operations practice, leading end-to-end supply chain, manufacturing quality, and technical operations consulting services. He has more than 15 years of consulting and technical operations experience in the pharmaceutical, biologics, and medical device sectors. Pernenkil has a Ph.D. in chemical engineering practice from MIT and an MBA from MIT Sloan School of Management.