The clinical trial supply chain is an intricate, multi-faceted process critical to ensuring that trials progress smoothly and deliver reliable results. However, traditional supply chain management approaches – marked by fragmented communication, processes, and a lack of real-time visibility – are increasingly being recognised as inadequate for the challenges of modern clinical trials.
“Today’s clinical trials are increasingly heavily regulated, global and complex,” explains Kelly Archer, managing partner at 4C Associates, a commercial, supply chain and operations consultancy, talking through some of the primary challenges in clinical supply chain management that companies are facing.
The stakes are high, as supply chain inefficiencies can lead to delays, increased costs, and compromised data integrity, all of which undermine the potential for life-saving treatments to reach patients.
“As we all saw being brought to life through our experiences of Covid, the supply chain implications for clinical trials from temperature management, demand forecasting and visibility through a supply chain are more than the standard models were prepared for,” says Archer. Traditional supply chain management in clinical trials faces several entrenched issues. The process involves coordinating with multiple stakeholders – sponsors, CROs, suppliers, logistics providers, clinical sites, and regulators. Each has specific roles, but often operate in silos. This fragmentation leads to inefficiencies such as limited visibility. Without end-to-end transparency, stakeholders struggle to anticipate bottlenecks, track inventory, or mitigate risks like temperature excursions for sensitive products.
As well as this, manual processes are still prevalent in so many organisations, meaning operations are slowed down and there is an increased risk of errors. Communication gaps further exacerbate these challenges, creating situations where clinical sites either run out of critical supplies or receive shipments that far exceed their immediate needs.
Digitalising in action
It’s clear that the digitalisation of clinical trial supply chain management has emerged as a game-changing solution. Be it integrating digital tools, data-driven insights, and automation, companies can transform their operations to achieve unparalleled levels of visibility, efficiency, and collaboration. To illustrate the impact of digitalisation, consider a global temperaturesensitive oncology clinical trial, involving over 100 sites across multiple continents. Traditional supply chain management methods would typically lead to frequent stockouts, excessive wastage and compliance challenges. However, after implementing digital solutions, not only is it possible for stakeholders to see real-time monitoring, but also enhanced forecasting if AI-driven models are used. As well as this, streamlined logistics can ensure faster customs clearance and improved on-time delivery to sites.
Digitalisation offers a comprehensive solution to these issues by introducing end-to-end visibility, predictive analytics, and automation. Through real-time tracking and monitoring tools, stakeholders gain unprecedented transparency into the supply chain.
For instance, Internet of Things (IoT) sensors can monitor the conditions of temperature-sensitive products throughout transit, immediately alerting operators if conditions deviate from acceptable parameters. Beyond basic real-time monitoring, IoT technology is evolving to offer predictive capabilities. Sensors now come equipped with advanced analytics to identify patterns that may indicate future risks, such as minor temperature fluctuations that precede full-blown excursions. This pre-emptive capability transforms supply chain management from reactive to proactive.
Similarly, blockchain technology enhances traceability by providing an immutable record of every transaction and movement, ensuring that all parties can verify the integrity of the supply chain at every stage. Through its decentralised ledger system, blockchain ensure that every transaction, from production to delivery, is securely recorded and easily auditable. Predictive analytics, powered by artificial intelligence (AI) and machine learning, represent another cornerstone of digital supply chain optimisation. These advanced tools enable organisations to forecast demand more accurately by analysing historical data, patient recruitment rates, and trial protocols. But what role will predictive analytics play in optimising the supply chain? “To put it simply, we use predictive analytics to minimise surprises in the supply chain and reduce the need for firefighting,” explains Erika Biggadike, head of supply chain at 4C Associates.
Digital clinical supply chain
Analytics-driven performance – Clinical supply analytics
“Using historical data, external drivers and statistical algorithms, we can create better forecasts of future demand signals, and, most importantly, describe and track the range of uncertainty in that prediction.”
By anticipating supply needs with greater precision, organisations can avoid common pitfalls such as overproduction, understocking, or emergency shipments. These technologies also enable scenario planning, allowing stakeholders to model potential disruptors or changes in trial dynamics and proactively adjust their supply strategies.
However, despite its advantages, the path to digitalisation is not without its own challenges. Many organisations face resistance to change, particularly from teams accustomed to traditional methods. Additionally, integrating new technologies with legacy systems can be both time-consuming and costly.
Even then, there are multiple strategies or tools that can help stakeholders share real-time data and insights, as Erika explains: “Having open data sharing between partners gives each business its own best chance of understanding supply, demand, contingency and at the bottom-line profitability.”
For example, a phased approach to implementation, starting with pilot projects to demonstrate tangible benefits, can help build internal buy-in. Partnering with experienced vendors and consultants also streamlines the transition, ensuring that new systems integrate seamlessly with existing workflows.
Transforming trials with AI
As the digital transformation of clinical trial supply chains gains momentum, emerging technologies are poised to further enhance these capabilities.
The past year especially, has seen huge strides in advanced AI and machine learning. Future applications of AI will go beyond forecasting to include adaptive algorithms that optimise supply chain operations in real time. These systems will dynamically respond to changes in trial protocols or unexpected disruptions.
“Across technologies, we are increasingly looking at the efficiencies automation can bring and here at 4C Associates, we see that just as much in supply chain as in other areas,” Kelly Archer says. “Each leading software is offering an extension to introduce efficiency, so many new supply chain AI products are emerging and alongside that, the tried-and-tested platforms of Teneo, CoPilot, Amelia et cetera, sit quietly and wait to be noticed.”
Digital twins – virtual replicas of physical supply chain networks – will allow stakeholders to continuously model, monitor, and optimise supply chain performance. Sustainability metrics, integrated into digital tools, will help organisations minimise their environmental impact by optimising packaging, reducing carbon emissions, and cutting waste. One of the most significant advantages of digital twins is their ability to support scenario planning. For instance, stakeholders can simulate the impact of various disruptions, such as adverse weather, sudden changes in trial protocols, or geopolitical events affecting transportation routes. By testing these scenarios virtually, organisations can identify vulnerabilities and pre-emptively develop mitigation strategies. Digitalisation and automation are not just enhancements but necessities for the modern clinical trial supply chain. By embracing these technologies, organisations can transform their operations, overcoming traditional challenges while unlocking new levels of efficiency, collaboration, and patient-centricity.
“The role for our pharma supply chain professionals will be to inform, judge and evaluate the information which is supplied to their screens and make better decisions, and never lose track of the patient at the centre of the service. Let’s hope digitalisation will give us the chance to be more human in our interactions with those wonderful people who are willing to break new ground for the greater good,” shares Erika Biggadike. As the industry moves forward, the adoption of digital tools will become a key differentiator for sponsors and CROs seeking to drive innovation and improve patient outcomes. With continuous advancements in AI, IoT, and predictive analytics, the future of clinical trial supply chain management is bright – and digital.
Biopharma industry trends create challenges for clinical supply chains
- Full traceability of clinical supplies: End-to-end finished goods traceability is needed at the trial, program, CMO, and geography levels
- Regulatory complexity and varied trial designs: Regulatory changes, import/export rules, and expiry date requirements create regional complexities to manage and adapt operations. Evolving trial models, such as direct-to-patient, adaptive designs, and the push to faster trials drive additional clinical supply requirements
- Increased externalisation: Increased reliance on external partners drives integration and standardisation challenges required for achieving orchestration capabilities
- Next-gen advanced therapies: New drug modalities, including gene and cell therapy, create additional implications due to their unique and evolving requirements
- Increasing cost pressures: Cost management expectations exceed capabilities for managing and continually improving cost performance
