Why More Tools Won't Fix Clinical Supply

By Constantin Fahom, Ph.D.

Clinical supply has become harder to coordinate as trials span more countries, partner organizations, and delivery models. Recent evidence indicates increasing trial and protocol complexity, a growing amendment workload, and ongoing start-up delays related to regulatory approvals, contracts, site activation, and clinical supplies, as well as additional logistical and temperature control requirements in decentralized models.^1–5

A common approach is to introduce additional tools in the expectation that improved visibility, enhanced planning, and more effective shipment monitoring will solve the problem. Those tools may help, but the root cause often lies in a weak operating model that technology alone cannot repair. When ownership, handoffs, escalation paths, data stewardship, and exception handling are unclear, digital tools often expose the problem rather than solve it.^6–9

The more appropriate question, therefore, is not, “What tool should we add next?” but rather, “What foundational elements need to be established to enable our tools to enhance planning, release management, distribution, and exception handling without creating new risks or diminishing our control?” In this article, the term “operating model” refers to the practical design of the work, including role ownership, the records teams rely on, approval processes, escalation procedures, and the management of handoffs between partners.

In clinical supply, this design is important because performance rarely declines suddenly. More typically, it diminishes at the interfaces between different functions and partner organizations. Forecasting may be managed by one team, label readiness by another, release visibility with a packaging or depot partner, shipment monitoring with a logistics provider, and excursion review with quality, sponsor oversight, and local disposition rules. Each function may perform adequately on its own, yet the overall process can still feel slow, uncertain, and difficult to rely on when responsibilities, records, and escalation pathways are not aligned across the workflow.^{4–7, 9} Organizations that scale effectively tend to enhance workflow design, accountability, and handovers prior to determining which additional tools are necessary.^{6, 7, 9}

Viewed from this perspective, scalable clinical supply is supported by five practical foundations that can enhance control, coordination, and scalability within clinical supply operations.

1. Define The Workflow Before You Digitize It

The first step is to define the end-to-end workflow before determining how to automate it. In clinical supply, this involves mapping the complete process from demand signal to patient-ready inventory. It includes forecast updates, country setup, packaging and labeling release, depot replenishment, shipment booking, receipt confirmation, temperature review, returns, destruction, and resupply. It also encompasses the exception paths, not just the ideal scenario.

While this may seem straightforward, it is often where many efforts encounter difficulties. Teams tend to digitize a process that was never truly stable. When the system goes live, there can be a tendency for personnel to revert to spreadsheets, emails, and local trackers, especially when the trial deviates from the original plan. Such deviations may occur due to enrollment fluctuations, label version updates, delayed country start dates, partial stock received at depots, or urgent shipment reviews. Although the workflow is digitized, it may not be fully designed to accommodate real-world operating conditions.^{6, 7, 9}

ICH E6(R3) reinforces this logic. Trial processes should be proportionate, operationally feasible, and focused on what matters most to participant safety and data reliability.⁶ That principle applies to clinical supply as much as any other trial function. Do not automate noise. First, define the few steps that must work every time.

Three questions can provide helpful guidance: Where does the workflow start and conclude? Who is responsible for each handoff? Which manual steps are truly temporary, and when should they be phased out? If these questions go unanswered, hybrid work often becomes a permanent arrangement.

2. Clarify Governance Before Exceptions Happen

Clinical supply teams do not need additional governance procedures. They require timely, transparent decisions made by the appropriate individuals to safeguard the study.

In many organizations, delays are not primarily due to regulatory processes but rather stem from unclear authority. Questions such as who can update forecast assumptions, who approves labeling changes affecting already packed stock, who can reallocate inventory between countries, who is responsible for responding to temperature excursions or chain-of-custody issues, and who escalates partner delays impacting dosing schedules often remain unresolved.

When these roles and responsibilities are ambiguous, teams spend unnecessary time in meetings, email exchanges, and multiple review cycles. While work continues, progress is slow and uncertain. By the time a decision reaches the appropriate owner, the timeline may already be compromised.^{6, 9}

ICH E6(R3) places strong emphasis on proportionate quality management, documented responsibilities between parties, and risk-based control of important trial processes.⁶ The European Commission’s guideline on sponsor responsibilities for handling and shipping investigational medicinal products (IMPs) adds another practical point: sponsors must ensure that shipping, handling, and oversight arrangements are clearly defined and controlled across the involved parties.⁷ The implications for clinical supply are clear. Not every issue requires the same level of escalation, but high-impact decisions should be identified in advance.

The most effective way to improve speed is to establish the decision-making process in advance of any issues. Identify the responsible party, outline the necessary supporting evidence, set clear escalation thresholds, and assign appropriate response timelines. This approach ensures that governance functions effectively.

3. Create One Trusted Operational Record

A clinical supply operation slows down when trust in the record diminishes. This lack of confidence often manifests in familiar ways: inventory balances do not align, release statuses are unclear, shipment condition data is incomplete, label versions conflict, or one system indicates stock is available while another team considers it blocked.

When trust erodes, teams shift from execution to reconciliation. They review inboxes, compare spreadsheets, contact partners, and manually reconstruct timelines. The operation may continue to progress, but it does so based on manual verification rather than operational certainty.^{6, 7, 9}

The goal is not to have perfect data everywhere. Instead, it is to maintain a single, trusted operational record for the most critical decisions. Typically, this includes release status, lot and expiry dates, country allocation, label version, depot inventory, shipment condition, chain of custody, and final disposition after a deviation. For each of these, leaders should identify the authoritative source, designate the owner, and establish a correction process.

This is not solely a supply issue; it also pertains to compliance. ICH E6(R3) emphasizes the importance of data handling, exchange, and computerized systems in maintaining integrity, traceability, and fitness for purpose throughout the trial.⁶ If a transfer between systems requires repeated manual checks before anyone believes it, the process is not stable enough.

Temperature excursions clearly demonstrate this point. They should not be relegated to side emails or informal conversations. Instead, they should be documented in a formal record, undergo a structured review process, and conclude with a traceable disposition. The wider pharmaceutical quality literature similarly emphasizes that excursions must be recorded, investigated, and managed through a formal risk-based process rather than through informal judgment.¹¹

4. Design Adoption Into Day-To-Day Work

A workflow can be technically implemented and still encounter operational challenges. This often occurs because organizations view adoption as a training event rather than a fundamental change to the operating model. Employees may complete training but revert to previous habits under pressure. External partners may agree to a new process but still bypass it when local circumstances conflict with the design. Recent research on risk-based quality management in clinical trials indicates that adoption remains a challenge, with barriers related not only to awareness but also to inadequate execution and change management planning.⁸

Clinical supply leadership should therefore design adoption strategies that align with actual roles and daily workflows. Clearly define who executes tasks, who reviews them, who escalates issues, who updates records, and who communicates with clinical operations. Update standard operating procedures (SOPs), service-level agreements, and handoff processes to ensure the new procedures replace existing ones effectively, rather than operating alongside them.

This approach is especially important in decentralized and direct-to-participant models. The Trials@Home RADIAL project demonstrated that direct-to-participant IMP supply is achievable, but it also emphasized the need for clearer role delineation, enhanced planning, comprehensive temperature monitoring, and well-defined contingency plans across different countries and delivery models.⁴ For clinical supply leaders, this lesson applies beyond decentralized trials. Partner operations do not become stable simply because a process map is in place. They achieve stability when each party clearly understands its responsibilities and knows how to respond when the process encounters a break.^{4, 7}

Hypercare is also important. If the go-live period lacks prompt issue triage, regular review of friction points, and efficient processes for correction, workarounds can effectively become the primary operating method.^{8, 9}

5. Scale With Evidence, Not Enthusiasm

Clinical supply teams often recognize when a pilot has shown improvements. However, this does not necessarily indicate that the program is ready for scaling. A more effective approach is to define evidence-to-scale criteria prior to initiating the pilot. This evidence should encompass three key areas:

First, operational performance: responsiveness to forecasts, country readiness, inventory accuracy, reduction in stockouts, minimized expiry waste, faster closure of excursions, and more consistent release-to-ship timelines.

Second, control and assurance: fewer undocumented handoffs, enhanced traceability, reduced inbox-driven decision-making, improved visibility across partners, and records that withstand audit or inspection requirements.

Third, business value: decreased rework, reduced exposure to premium freight costs, improved labor productivity, and the avoidance of disruptions.

This approach is important because foundational improvements may not always initially translate into significant cost savings. Often, they first manifest as fewer surprises, fewer reconciliation issues, and fewer urgent escalations. These aspects are still critical. Research in pharmaceutical supply chains consistently indicates that risks often stem not only from external shocks but also from internal process deficiencies, personnel issues, coordination gaps, and integration weaknesses.^{9, 10} Addressing those weaknesses provides genuine value, even before the financial benefits become evident.

Leaders should also establish a clear definition of the new normal. Which traditional processes are being phased out? Which hybrid solutions are permitted temporarily, and for how long? Without clarity on these questions, the organization risks layering digital solutions over manual processes and mistakes, mistaking them for progress.

Where Clinical Supply Leaders Can Start

For teams seeking to adopt this approach, the most practical starting point is not a comprehensive transformation program. Instead, focus on a single, critical workflow that directly impacts dosing continuity, timeline reliability, or compliance confidence. Suitable examples include country activation, packaging release to depot availability, shipment excursion management, or resupply following enrollment changes.^{2–5, 7}

Begin by mapping the entire workflow from start to finish, including exceptions, approval processes, data sources, partner handoffs, and escalation points. Then, identify the top three breakpoints that cause teams to rely on manual bridging. For each of these breakpoints, assign a clearly defined decision owner and specify the minimum evidence necessary to make an informed decision.

Next, determine which record should be considered trustworthy within that workflow and identify manual steps that can be eliminated if the redesign is successful. This step is often overlooked, but it is essential. Without explicit decisions about what to phase out, organizations risk maintaining outdated processes alongside new ones.

Only after completing these steps should teams evaluate whether their current tools are adequate, if integration gaps exist, or if new technology is genuinely needed. In other words, address and optimize the workflow logic first, then determine what support tools are required.

Conclusion

Scalable clinical supply management is not achieved through tools alone. It is built by integrating fit-for-purpose tools with well-designed workflows, clear governance, reliable record-keeping, partner-ready adoption, and robust evidence to support scaling efforts. Organizations that excel in this area do not merely digitize processes; they establish a clinical supply operation that remains functional under pressure, maintains credibility during inspections, and adapts effectively to changes in trial requirements.^6–11

References:

1. Markey, N., Howitt, B., El-Mansouri, I., Schwartzenberg, C., Kotova, O., & Meier, C. (2024). Clinical trials are becoming more complex: A machine learning analysis of data from over 16,000 trials. Scientific Reports, 14, 3514. https://doi.org/10.1038/s41598-024-53211-z
2. Getz, K., Smith, Z., Botto, E., Murphy, E., & Dauchy, A. (2024). New benchmarks on protocol amendment practices, trends and their impact on clinical trial performance. Therapeutic Innovation & Regulatory Science, 58(3), 539–548. https://doi.org/10.1007/s43441-024-00622-9
3. Lai, J., Forney, L., Brinton, D. L., & Simpson, K. N. (2021). Drivers of start-up delays in global randomized clinical trials. Therapeutic Innovation & Regulatory Science, 55(1), 212–227. https://doi.org/10.1007/s43441-020-00207-2
4. Heath, M., de Jong, A. J., Magorrian-Spence, S., Jin, C., van Weelij, D. R., Pagnier, L., van Rijswick, Y., Haufe, V., Lagerwaard, B., & Zuidgeest, M. G. P. (2025). The supply of investigational medicinal product and management of study materials for decentralized participants: Insights from the Trials@Home RADIAL proof-of-concept trial. Clinical Pharmacology & Therapeutics, 118(5), 1079–1089. https://doi.org/10.1002/cpt.70072
5. Gumber, L., Agbeleye, O., Inskip, A., Fairbairn, R., Still, M., Ouma, L., Lozano-Kuehne, J., Bardgett, M., Isaacs, J. D., Wason, J. M., Craig, D., & Pratt, A. G. (2024). Operational complexities in international clinical trials: A systematic review of challenges and proposed solutions. BMJ Open, 14(4), e077132. https://doi.org/10.1136/bmjopen-2023-077132
6. International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use. (2025). ICH harmonised guideline E6(R3): Guideline for good clinical practice. https://database.ich.org/sites/default/files/ICH_E6%28R3%29_Step4_FinalGuideline_2025_
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7. European Commission, Directorate-General for Health and Food Safety. (2022). Guideline on the responsibilities of the sponsor with regard to handling and shipping of investigational medicinal products for human use in accordance with good clinical practice and good manufacturing practice. https://health.ec.europa.eu/document/download/6e8ae778-73d0-4a1e-a374-a06e791152a7_en
8. Dirks, A., Florez, M., Torche, F., Young, S., Slizgi, B., & Getz, K. (2024). Comprehensive assessment of risk-based quality management adoption in clinical trials. Therapeutic Innovation & Regulatory Science, 58(3), 520–527. https://doi.org/10.1007/s43441-024-00618-5
9. Yadav, P. (2024). Digital transformation in the health product supply chain: A framework for analysis. Health Systems & Reform, 10(2), 2386041. https://doi.org/10.1080/23288604.2024.2386041
10. Wang, M., & Jie, F. (2020). Managing supply chain uncertainty and risk in the pharmaceutical industry. Health Services Management Research, 33(3), 156–164. https://doi.org/10.1177/0951484819845305
11. Kumar, N., & Jha, A. (2017). Temperature excursion management: A novel approach of quality system in pharmaceutical industry. Saudi Pharmaceutical Journal, 25(2), 176–183. https://doi.org/10.1016/j.jsps.2016.07.001

About The Author:

Constantin Fahom is a Ph.D. researcher specializing in digital manufacturing transformation at the University of Gloucestershire, U.K., with over 15 years of experience in pharmaceutical and biotech sectors. His background includes digital solutions, project management, quality assurance, business development, and leadership within regulated environments. His research examines why digital transformation initiatives often fail to deliver sustained value, emphasizing that the challenge is not a lack of tools, but rather weak foundational elements such as governance, integration maturity, operating models, and adoption capabilities. By combining academic rigor with practical industry experience, his work supports leaders in transitioning from isolated digital projects to scalable, end-to-end solutions while ensuring compliance with regulatory standards.