Can Standardizing Protocols Improve Clinical Supply Execution?
By Rachel Grabenhofer, Chief Editor, Clinical Supply Leader
Regulatory affairs may not be a sexy subject, but their impact certainly catches our attention. When ICH’s M11 guidance went into effect in June 2026, it caught mine, sending me down a rabbit hole exploring how clinical trial protocols are translated from study design into clinical supply execution. What I found was surprising.
The goal of M11 is to standardize the structure and content of clinical trial protocols globally. With its template and technical specifications, the guidance aims to enable the electronic exchange of protocol information across stakeholders involved in the development, amendment, review, conduct, and closeout of clinical trials.
While M11 was not written specifically for clinical supply, its potential value seems straightforward. Protocol information that is consistently structured and easier to access could make activities such as forecasting, study startup planning, and amendment impact assessments more efficient. It may also alleviate some of the friction associated with locating, sharing, and re-entering protocol information across functions.
To explore whether these assumptions hold true in practice, I spoke with experts in clinical operations, RTSM, and clinical supply to learn more about how protocol information moves from study design into execution. I expected to hear frustrations around protocol ambiguity and translation errors, and perhaps some optimism that M11 might improve internal processes. Those concepts emerged, but discussions repeatedly circled back to feasibility, communication, and the realities of execution. The experts seemed much less concerned about the protocol content itself, and more about what comes next: operationalizing it.
I hadn’t anticipated that. M11 is not the only initiative focused on improving how protocol information is structured and exchanged. There’s the FDA's Real-Time Clinical Trials (RTCT) pilot program, announced in April (2026), along with longer-term efforts like CDISC and broader investments in protocol digitalization, interoperability, and automation. These all demonstrate growing interest in making key clinical trial information easier to access and share across stakeholders.
The easier exchange of protocol information, however, does not directly translate to better execution. For clinical supply, the protocol serves as a foundational planning document, but many operational decisions depend on input beyond the protocol itself.
Shivani Tanwar expressed this in a recent Clinical Supply Leader article, where she described clinical protocols ultimately as models of expected trial behavior that “rarely survive unchanged once trial execution begins.” Enrollment patterns, site performance, and other operational realities force teams to revisit assumptions and adapt forecasts, influencing downstream inventory placement, manufacturing schedules, depot stocking strategies, and distribution activities.
Tanwar’s observation helped explain why the discussions kept drifting away from my original assumption. Many execution challenges emerge only after protocol information has been exchanged and put into action. Successful execution depends on how that information is translated, supplemented, communicated, and ultimately acted upon. As my conversations continued, one central lesson became clear: standardizing and operationalizing information are not the same thing.
Designing Studies For Clinical Supply Execution
To understand how protocol information moves from study design into execution, I first spoke with Sandra Moss, head of operations excellence at Parabilis Medicines. Moss leads systems design, processes, and operational frameworks for the organization and previously spent more than a decade in leadership roles at Amgen, spanning global procurement, global trial management, and clinical trial site operations. Although Moss’s perspective is mostly upstream to clinical supply, it’s relevant because she’s seen how protocols are written and used by supply teams to forecast demand, position inventory, and support study execution.
I started our conversation with the question of how clinical protocols are translated across functions, but Moss quickly turned to the people and processes that help shape them in the first place. She emphasized how crucial it is to include operational stakeholders early in the planning process to challenge assumptions and ensure study designs are operationally feasible.
“I’ve seen translation challenges emerge where protocol development is done in a silo with scientific and medical expertise but without operational execution input,” she said. Moss has also participated in protocol development where patient advocacy and clinical trial site perspectives were specifically included to better understand how a study could be operationalized. In her view, bringing those voices in early helps to identify issues that scientific and medical teams may not otherwise see.
“I'll give you an extreme example,” she recalled. “I've seen a trial where the PK draw schedule would have required a patient to be at the site for 18 hours. … The draw was never executed.” Moss offered the example as a reminder that scientific requirements must also withstand operational reality. She added that operations experts help to reality-check the math and practicality of the plan. “They can determine if a patient comes in at 8:00 and we have the scientific need for PK draws, is it really feasible? The operational element is key,” Moss explained.
This scenario illustrates how execution realities can diverge from protocol intent. A visit schedule that appears feasible on paper may prove difficult, for both sites and patients, to execute in practice, forcing teams to reconsider protocol assumptions or modify study procedures. For clinical supply, those adjustments can affect enrollment expectations, study timelines, and the demand assumptions upon which forecasting and inventory plans are built.
Just as operations teams can help improve protocol feasibility, they can also gain execution insights by participating in protocol discussions early. Moss pointed to primary endpoints such as survival rate as one example. “I have seen protocols where the primary endpoint was defined, but how to get to that endpoint wasn't fully thought through,” she noted.
She highlighted that a trial may be designed to examine survival rate post-treatment completion, but the operational requirements needed to support that endpoint are not always fully considered. Understanding those requirements early can help supply teams anticipate how long patients may remain engaged in the study and what operational support may be required over time.
“Many times, the execution team is so focused on enrollment to completion of the trial that they don’t think about loss to follow-up, or how patients are being followed up in the longer term, which is very important,” Moss emphasized. In this scenario, Moss said that as an operations person, she would have benefitted from knowing from her biometrics team that patients needed to be followed for 18 months after treatment. “That's something I need to earmark as I'm executing the trial and reporting metrics,” she added.
While follow-up activities may not always affect investigational product demand directly, they can affect study duration, database lock timelines, comparator retention requirements, and inventory disposition planning, all of which influence clinical supply strategy.
Early Stakeholder Involvement Improves Protocol Feasibility
Ideally, before the full protocol is written, a protocol synopsis is developed and reviewed across functions to identify any feasibility concerns early. This includes input from regulatory. “The worst-case scenario is to have a protocol that is beautifully written, scientifically and statistically, it goes to the FDA, and the FDA rejects it because you didn't get regulatory input,” Moss lamented.
The FDA could also return with questions about the protocol that, through the process of answering those questions, changes the design. This may seem like a strictly regulatory issue, but again, design changes can alter assumptions that clinical supply has used to begin planning. Adjustments to treatment duration, visit schedules, dosing requirements, or enrollment targets may require revisiting manufacturing quantities, depot strategies, inventory levels, and forecasting models.
Moss conceded that she’d be surprised if companies are still developing protocols without operational input. But even with thoughtful planning, she believes something is always missed. “There’s a lot of optimism when we write the protocol – and there is definitely a realization period as we roll it out,” she said. “Even when you engage stakeholders early, feedback from health authorities, clinicians, ethics boards, or investigators may change things later.”
That realization period emerges when study assumptions meet operational reality. Enrollment may occur more slowly than expected, patients may remain on study longer than anticipated, or countries may activate on different timelines. Clinical supply teams are then required to adapt manufacturing schedules, inventory plans, depot strategies, and distribution activities around conditions that differ from the original assumptions.
For Moss, the issue is not that stakeholders misunderstand the protocol. It’s that execution challenges can emerge when operational assumptions are not surfaced early enough. Or, when real-world constraints introduce variables that were not fully visible during protocol development.
For clinical supply, those challenges often translate into protocol changes, enrollment delays, revised study timelines, or new operational requirements. Each can affect how much drug is needed, when it is needed, and how long it must remain available to support the study.
The Clinical Protocol Isn’t The Whole Story
Feasibility isn't the only issue. Clinical supply teams also depend on information outside of the protocol itself – which is perhaps unsurprising given that the protocol is not specifically written for clinical supply. “It is written for physicians to execute the study and collect evidence to test the hypothesis,” Moss noted.
That distinction was echoed by Ana-Zeralda Canals-Hamann, Ph.D., associate director of clinical trial supplies at Debiopharm, where among other responsibilities, she evaluates protocol feasibility and develops supply strategies for global clinical trials. “The protocol provides the outline of the clinical trial, such as the what and why. But clinical supply also needs the when, how and where,” she wrote.
Clinical Supply Requires Information Beyond The Protocol
Critical details include enrollment projections and drop-out rates, according to Canals-Hamann. Also, knowing the countries and sites that will be involved. “That way, we can plan the label languages, import/export licenses, depot strategies, the need for an IRT or not, etc.,” she explained. Attributes including shelf-life and stability data are also necessary to support packaging campaign plans, along with any required ancillary supplies – and clarity around who will manage them.
Moss offered a practical example of how downstream considerations can affect supply planning: when clinical operations decides to carry out a trial in ten different countries, and investigational product labeling requirements are different for all of them, knowing the countries gives clinical supply a heads-up. “I might not know exactly which countries we're ultimately going to use, but I should have a good list of potential countries so I can ask clinical supply about labeling requirements,” Moss highlighted. “Sometimes we lose time because we didn't involve clinical supply early enough to say, ‘I'm pretty sure we're going to Brazil, so get ready for Brazil labeling.’"
Pathways to the clinical trials are another missing piece of the execution puzzle, especially when other countries are involved. “It is vital to understand through which channels that investigational product will be imported,” Moss said. “Countries like Brazil and China, for example, have prolonged import processes.” Exporting the product from the original country, importing it into the destination country, and distributing it within that country – moving through depots and delivered to clinical trial sites – are detailed steps, Moss emphasized. “And if the product has temperature sensitivity, packaging becomes part of the consideration as well.”
Taken together, Moss and Canals-Hamann highlighted how clinical supply execution depends on considerably more information than the protocol provides. In this case, the challenge is not interpreting what is in the protocol, but identifying and incorporating the operational information that is not.
Still, recognizing operational requirements is just part of the process. As my conversations revealed, work is also required to translate those requirements into something that teams can actually execute.
About The Experts
Sandra Moss is head of operations excellence at Parabilis Medicines, where she leads systems design, processes, and operational frameworks for the organization. She previously spent more than a decade in leadership roles at Amgen, including as global head of strategic procurement for development, and regional head of clinical trial site management for North and South America.
Ana-Zeralda Canals Hamann, Ph.D., is Associate Director of Clinical Trial Supplies at Debiopharm. She has more than a decade in sponsor-side pharmaceutical clinical operations, CMC, supply chain management, regulatory, IP, project management, and preclinical services. Her experience includes various roles at Sanifit Therapeutics, where she managed clinical trials between Phase I and III, as well as the supply chain. Canals Hamann earned her M.Sc. in clinical research administration and a Ph.D. in molecular medicine from the University of Oxford.
Luis Rodriguez, MBA, specializes in RTSM/IRT and the integrations that connect it to EDC, eCOA and drug supply forecasting. He spent nearly five years at Suvoda, finishing as Project Manager II, Delivery Lead. He led a team that delivered more than 100 RTSM-EDC integrations across oncology, CNS and rare disease studies, facilitating efforts to improve specification templates and delivery processes, which cut delivery times in half. At the time of this interview, he was an independent consultant focused on RTSM-EDC integrations and AI adoption for clinical data teams.