OR WAIT null SECS
Technological developments in real-time supply chain operations provide biologics manufacturers with capabilities that go beyond supply chain visibility to tangibly address security and quality challenges.
The COVID-19 pandemic saw the global biopharma supply chain thrust into center stage amid a perfect storm of high-profile disruptions, logistical challenges, labor shortages, geopolitical instability, and shortages of certain key ingredients, drugs, and equipment. These challenges compounded the legacy supply chain challenges biopharmaceutical manufacturers were already facing, such as temperature control failures resulting in spoilage, counterfeit drugs, and the black and gray markets for therapeutics.
This paper seeks to quantify some of the major biologics supply chain challenges and how they can be resolved by resilient digital operations. When properly deployed, such an approach will improve overall supply chain visibility, enhance security, and assist with the forecasting and planning around problematic scenarios. These improvements translate to greater ease in reporting the information demanded under the Drug Supply Chain Security Act (DSCSA) and greater assurance that drug quality and security are safeguarded.
According to the International Air Transport Association’s (IATA’s) Center of Excellence for Independent Validators in Pharmaceutical Logistics, losses from the deliveries of vaccines exposed to temperatures outside their recommended range cost the industry approximately $34 billion annually (1). That’s only one example of the significant waste stemming from misaligned logistics networks and limited visibility, automation, and control in pharmaceutical supply chain networks.
Another study published in July 2022 by Forrester Consulting (2) on behalf of Rockwell Automation surveyed more than 300 global supply chain decision makers across a variety of industries. The report found that of the companies polled, “87% said counterfeiting is problematic for their company, and nearly half (47%) said their company loses between 11% and 60% of sales income each year to counterfeiting” (2). Furthermore, “89% said gray-market diversion is problematic for their company with 56% reporting that their company loses up to 60% of sales income each year to gray-market diversion” (2).
Looking at the development and distribution of COVID-19 vaccines as one example, the problems have been persistent and significant. On a global scale, the World Health Organization estimates that up to 50% (3) of vaccines are wasted every year. What’s more, the Centers for Disease Control and Prevention reported that at least 15 million doses (4) of the COVID-19 vaccine were wasted in just a six-month period in 2021. That’s a conservative estimate that doesn’t even cover all places that handle, store, and administer vaccines. In addition, there are cases where vaccines don’t pass quality inspection to begin with—including an account in The New York Times (5) of nearly 400 million doses scrapped by a manufacturer due to poor quality control. Much of this waste can be attributed to shortcomings in logistics to support an unbroken cold chain. Finally, data published by McKinsey (6) suggests that the pharmaceutical industry stands to lose an average of 24% of one year’s EBITDA (earnings before interest, taxes, depreciation, and amortization) every 10 years due to supply chain disruptions.
Clearly, none of this is good business, nor is it sustainable in the long term. The supply chain challenges for biopharmaceutical manufacturers cost a great deal of pain, both financially and in terms of reputation. Therein lies the urgency to solve them. Recognizing the magnitude of the issue, regulatory agencies are demanding more accountability. The DSCSA, for instance—first introduced by FDA in 2013—is being updated to add more stringent requirements related to drug delivery, distribution, and disposal. Large-molecule drugs/biologics have specific parameters around manufacturing, storage, and transportation. Any deviation from those parameters can result in adverse impacts, such as significant batch loss due to temperature control problems, and so forth. To protect patients, the DSCSA sets out the critical requirements needed to build a comprehensive digitized system for tracking and identifying prescription drugs on sale in the United States, phased in over a 10-year period.
Historically, bio/pharmaceutical supply chains, like those of other industries, were somewhat siloed, which resulted in a lack of visibility across the full supply chain journey of drugs and therapeutics—from development to patient and every step in between. This lack of visibility manifested in poor planning, inaccurate predictions, and delayed decision-making, all of which increased risk, led to waste, and eroded value for the organization (as detailed above).
Regulations in the biopharmaceutical industry, such as the DSCSA, are becoming more stringent to address the legacy issues relating to therapeutics. Advances in supply chain technology can help biopharmaceutical companies meet these expanded requirements. The introduction of ‘big data,’ more robust and secure instantaneous communication, the industrial internet of things (IIoT), artificial intelligence (AI), and machine learning (ML)—allied to advances in logistics, sensor technologies, and private secure networks—have spurred a number of important technological advances relating to real-time supply chain visibility.
While having real-time visibility was a significant step forward in the ability to better secure drugs in the supply chain, technological innovations can be deployed that further minimize the risk of losses and maximize the return on investment of supply chain investments. Developing and deploying a ‘real-time-all-the-time’ model to the supply chain has been a priority that enables biopharmaceutical manufacturers to go beyond visibility, fully remove historic data silos, and create completely digitized end-to-end supply chain ecosystems that can meaningfully tackle both new and legacy challenges.
How does all of this translate on a practical level? Across the whole ecosystem of customers, suppliers, and transportation modalities, three fundamental actions have been identified that can go a long way toward maintaining drug substance and drug product integrity and security, supporting current good manufacturing practice compliance throughout the supply chain, and helping to meet regulatory standards. Together, these actions combine AI and ML with big data monitoring and analysis and deploy across entire supply chains like a net. This produces actionable intelligence to drive tangible improvements in real-time supply operations and help minimize the effect of disruption. The three actions are:
A digital twin is a virtual representation of the entire supply chain ecosystem—a virtual map of assets across operations and business processes constructed from vast amounts of accessible, real-time, ground truth data flowing across connected systems. Historically, digital twins were associated more with static analysis, but now the concept has been successfully operationalized to track many supply chain dependencies to mitigate risks, automate workflows and corrective action, and drive better supply chain resilience.
Mapping the entire biopharma supply chain ecosystem in this way (i.e., every component within the journey of a product) is the starting point of the ‘real-time-all-the-time’ supply chain model. Every constituent, regardless of which enterprise they reside in, can be added digitally. This digitization of the entire end-to-end supply chain means that organizations can see where inventory is at any point in its journey, whether that be at the container, pallet, box, or individual package or vial level, from manufacturer to the patient if necessary.
Deploying digital twins, all constituents can be constantly monitored at multiple levels via any number of agreed parameters specific to operations. Deep signal and data intelligence can be generated from any entity, system, or device and shared via interactive dashboards in real time. The systems used are designed to be data-agnostic, which means that data can be taken without problem from any connected device. The resulting ‘digital thread’ of connected data allows organizations to overcome data and organizational silos, within their own company and across every other organization involved in the supply chain, and truly understand how well the entire supply chain is performing on a minute-to-minute basis.
Embedding deep data and actionable intelligence into digital twin models further builds transparency and facilitates approved cross-organizational collaboration across all partners in the ecosystem. Any variance to set parameters or disruptions to plans can be identified and flagged quickly. Deviances can be proactively triaged to give the best possible chance to prevent escalation, thereby improving resilience.
The virtual nature of digital twins also empowers supply chain ecosystem partners to develop and run advanced, predictive scenario modeling. What this means is that organizations can virtually model and test ‘what-if’ scenarios where disruptions may occur with potential actions and outcomes outlined. As these are virtual simulations, they are cost-effective and safe and provide invaluable intelligence. Organizations can now prepare contingency plans for supply chain failures, disruptions, and supply-demand fluctuations to model and optimize operations.
Once a supply chain ecosystem is fully digitized through digital twin technology, that ecosystem can be scaled and extended as needed. Building a network of digital twins that is extensible as more components are added to the supply chain infrastructure can provide the visibility required to highlight duplicate dependencies and sources for any given element, regardless of whether a supplier is one or more levels removed from the core. With a network of digital twins, there is a common node where the risk of duplication of effort can be identified and removed. This extendibility is important, especially as it pertains to the ability to build a network of digital twins across key suppliers, map all the various dependencies and relationships in their supply chain, and pull everything into a single real-time, collaborative supply chain operational source. Production can be modeled, managed, and mitigated, both from a visibility perspective as well as extrapolating and predicting problems and challenges that can occur.
Moving forward, complete visibility and collaboration across supply chain partners and enterprises will be an absolute requirement, as it enables the identification and prevention of any potential problems that exist in several nodes out of the extended ecosystem. For example, the recent pandemic-generated bottlenecks in the port of Shanghai. It’s possible that some of the materials that a biopharmaceutical company might purchase could eventually pass through that port through a third-party logistics company that is several layers deep in the supply chain network. If that port is backed up, the supply chain becomes disrupted. Having visibility into that issue to drive contingency plans is operationally vital so that any disruption can be best managed and minimized.
The digital twin mode can also be deployed at small scale to meet new challenges related to transitioning very expensive specialized therapies from low-volume, white-glove products and services to high-volume supply chain operations. Biopharmaceutical companies often acquire smaller companies that deliver specialized therapies such as cell and gene therapies, so creating a digital representation of that company’s existing supply chain operations and then faithfully transitioning that to the acquiring organization (and usually eventually to higher-volume operations) using digital twins can ensure quality, compliance, assurance, and continued on-time delivery. Companies can even gain visibility into the ‘last mile’ to ensure that the therapies are delivered and used as prescribed.
Lastly, when there are biopharmaceutical mergers, acquisitions, and spin-out companies—and if an enterprise has its existing supply chain ecosystems digitized—those functions are much easier to transfer ownership. As each relationship is mapped, every aspect of the supply chain is cataloged, and a record of the activities throughout the supply chain is maintained; thus, another entity can take over and integrate operations quickly and easily.
‘Black swan’ events are unpredictable, and the biopharmaceutical supply chain challenges are a fact of business life. However, technological developments are finally enabling manufacturers to tackle drug security and inventory losses while optimizing operations through the complete digitization of the supply chain. Building digital twin ecosystems enable predictive modeling, real-time alerts, and the ability to convene stakeholders across enterprises in a collective effort to safeguard drug quality, integrity, and security and enable biopharma manufacturers to meet the stringent demands laid out by measures, such as the DSCSA.
Mahesh Veerina is the president and CEO of ParkourSC.
Volume 35, Number 10
When referring to this article, please cite it as M. Veerina, “Advances in Real-Time Supply Chain Operation Technology Can Address Drug Product Security Challenges,” BioPharm International 35 (10) (2022).