Protocol Design Doesn't Fail in the Protocol, It Fails in Transition to Trial

Article 1 of this series examined why execution strategy must begin at the business decision and what happens when it doesn't. This article examines what that early strategy actually consists of, specifically the interpretive work required to bridge scientific intent into operational reality, and why that work demands a distinct kind of expertise at a precise point in development.

Clinical trials do not struggle because protocols are poorly designed. They struggle because the assumptions embedded in those protocols were never tested against the reality of executing them. Visit schedules that look reasonable in theory become unrealistic at sites managing competing study demands. Eligibility criteria that appear straightforward exclude the patient population that actually presents. Data flow designs assume system integrations that do not yet exist. The protocol defined the intent. The transition to trial exposed what the intent never accounted for.

This gap between scientific intent and real-world execution does not close on its own. It closes because qualified people with direct operational experience, pattern recognition, and the judgment to recognize where a protocol assumption will not hold are engaged at the point where those assumptions are still being formed. When that expertise is absent or engaged too late, the gap persists, surfacing during start-up and conduct as amendments, delays, and performance gaps that trace back to decisions made long before a site was selected or a vendor contracted. Examining what closes that gap is the focus of this article.

Protocols describe what a study is intended to learn. They do not, on their own, ensure that learning is possible. Bridging scientific intent into real-world execution is interpretive work, not administrative coordination. It involves judgment, pattern recognition, and an understanding of how protocol requirements behave when exposed to real-world variability across sites, vendors, systems, and patients.

The work of bridging that gap requires people who can read a protocol requirement and understand its operational implications simultaneously. Who recognize that a twice-monthly visit schedule places a burden on a site coordinator already managing four other studies. Who can identify that an enrollment assumption is built on a patient population that standard of care in the target geography does not support.

This is pattern recognition developed through direct operational experience. It is the ability to see what a protocol intends and anticipate where that intent will meet friction before the friction becomes a deviation, an amendment, or a timeline reset. It cannot be replicated through process design, project management frameworks, or scale alone. It exists in people who have watched assumptions break down in real programs and carry that knowledge into the next one. This capability over scale distinction matters. Large teams and complex processes are not prerequisites for effective execution. What matters is having the right expertise engaged at the right time to define assumptions, resolve ambiguity, and guide decisions before issues compound.

When this capability is present and engaged at the right stage, organizations surface protocol and feasibility issues while changes are still manageable. When it is absent or engaged too late, those issues surface during start-up and conduct when correction is expensive, disruptive, and visible to everyone including regulators and investors.

The same gap appears in activation timelines. Contract execution, site-specific review committee processes, IRB review, and site initiation visit scheduling are sequential dependencies that routinely consume four to six months before a single patient is screened. Timelines built without direct site activation experience treat these as administrative steps with predictable durations. They are not. Each one operates on its own timeline, subject to institutional calendars, competing priorities, and review processes that do not compress for sponsor urgency. The qualified people who know this don't estimate activation timelines from a template. They build them from experience with how these sequences actually behave, providing transparency into real task durations.

This internal alignment extends beyond protocol design. Investigational product planning, supply chain assumptions, manufacturing readiness, and regulatory sequencing are cross-functional dependencies that must be integrated into the execution model before the study reaches the starting line. A protocol that is operationally feasible in theory but disconnected from IP supply reality or manufacturing constraints will encounter those gaps during startup when resolving them is significantly more disruptive. The cross-functional work of early operational strategy is integration, ensuring that every function whose decisions shape execution has been brought into alignment before commitments are made.

The Operational Strategy Timing Model illustrates where this work must occur. Reading left to right, each phase represents increasing commitment and decreasing flexibility. At the portfolio and asset planning stage, decisions are still reversible. By the time a study reaches trial startup and active execution, those same decisions have hardened into executed contracts with sites and vendors, regulatory submissions, and operational commitments that are difficult and expensive to unwind. The window for qualified execution input is most open in the earliest stages of early operational strategy and closes faster than most organizations recognize.

As commitment increases across development phases, flexibility decreases and the cost of course correction rises.

The critical window sits in the middle, at early operational strategy and planning feasibility through study design and integrated operational planning. This is where protocol assumptions are first formalized, where vendor scope begins to take shape, where enrollment models are built, and where the RFP process establishes the contractual foundation for execution. The RFP process is the point at which strategy is translated into an operational model. When approached deliberately, it enables alignment, transparency, and sponsor control. When approached as a transactional step, it introduces hidden complexity that compounds throughout the study lifecycle.

When this stage is engaged deliberately and with the right expertise, it produces the operational scaffolding that makes credible planning possible: the grounded protocol synopsis, tested enrollment projections, defined vendor strategy, realistic timeline, and matched resourcing that execution actually requires.

Organizations that compress or bypass this stage do not eliminate this work. They defer it into rework, change orders, and delays. The assumptions that were never tested surface during startup and conduct as protocol amendments, vendor change orders, enrollment shortfalls, and timeline resets. By then the options for correction have already narrowed and the cost of exercising them has already risen.

Root cause analysis of clinical execution instability consistently points upstream. The fishbone diagram below maps the factors that most commonly contribute to instability during trial conduct. What it reveals is a breakdown of the conditions under which execution was designed, not a breakdown of execution teams.

Several of these gaps concentrate specifically at the transition from protocol design to trial execution via early strategy, where the interpretive gap between scientific intent and operational reality is widest.

Protocol assumptions about patient populations are among the most consistently untested. Eligibility criteria are designed around the ideal study candidate. The patient who actually presents at the site is shaped by standard of care, geography, referring physician patterns, and competing study availability. When those two populations diverge, and they frequently do, enrollment slows, screen failure rates climb, and enrollment timelines extend.

Visit schedules present a similar dynamic. A schedule that appears feasible at the investigator level often looks entirely different to the study coordinator managing it. Feasibility conversations that stop at the physician level produce scientific validation without operational verification. The people who will run the protocol are not the same people who were asked whether it was feasible.

Timeline construction is where optimistic assumption accumulates most quietly. Qualified execution leaders know the actual sequencing that governs site activation such as contract negotiation and execution, site-specific review committee processes, IRB review, and site initiation visit scheduling are sequential dependencies that routinely consume four to six months before a single patient is screened. That knowledge belongs in the planning model before timelines are presented to leadership, boards, or investors. Timelines built without that operational grounding are aspirations presented as commitments, and that gap creates the pressure that drives every subsequent shortcut.

Vendor strategy assumptions complete the picture. A pattern that recurs with remarkable consistency is the protocol-as-RFP with a cover request sent to vendors with a protocol attached and minimal scope definition beyond it. The intention is speed. The result is vendors responding to incomplete information, filling scope gaps with their own assumptions because the scope was never defined. It was inherited. The misalignment that results does not surface at contracting. It surfaces mid-study as change orders, scope disputes, and performance gaps that are treated as vendor delivery breakdowns when they are more accurately described as sponsor scope gaps.

Study startup is where the quality of these early decisions becomes visible. It is not where they are made. Transitioning scientific intent into an operational model that sites can follow and vendors can execute is sponsor-led design work that belongs in early strategy, before contracts are executed and before the cone of uncertainty closes around assumptions that were never pressure-tested.

Most operational problems are not execution failures. They are strategy timing failures.

Closing the transition gap requires deliberate evaluation of the operational decisions made during early strategy by people with the experience to recognize what the answers actually mean. Early operational strategy asks:

Which elements of the trial design are most sensitive to operational execution? Every protocol has pressure points, such as assessments, visit schedules, eligibility criteria, data requirements, that are more vulnerable to real-world variability than others. Identifying them early allows sponsors to design mitigation into the study rather than manage consequences during conduct.

What assumptions about sites, patients, IP supply, vendors, and timelines must hold for the design to work as intended? Assumptions are unavoidable in early development. What is avoidable is allowing them to persist untested until commitments have hardened around them.

Can aspects of the protocol or operational approach be adjusted to improve execution feasibility without compromising scientific integrity? This question requires someone who understands both the scientific intent and the operational reality simultaneously. It is most valuable when asked before the protocol is finalized rather than after an amendment is required.

Where dependencies remain, what structures will support reliable delivery across sites and vendors? Dependencies identified and owned during early strategy become manageable execution variables. Dependencies discovered during startup or conduct become the source of change orders, delays, and performance gaps.

Does the sponsor organization have the visibility and decision authority required to oversee those dependencies effectively? A program can be well-designed operationally and still fall short if the sponsor-side capability to monitor, interpret, and intervene is not structured and resourced proportionately. This is not a theoretical gap. It is among the most common, and least examined, sources of execution instability in clinical development.

Protocol design does not struggle in the protocol. It struggles in the transition to trial, when assumptions embedded in the design meet a reality that early operational strategy was never given the runway to validate.

Closing that gap is not a process problem. It is a capability and timing problem. The right expertise, engaged at the right stage, with enough runway to ask the hard questions before they become expensive answers.

This is Quality by Design (QbD) in practice. The deliberate, front-loaded work of ensuring that what is designed can actually be executed, applied before commitments make course correction costly.

When early operational strategy is deliberate and proportionate, it produces the scaffolding that stable execution requires. When it is compressed or bypassed, that scaffolding never forms. Startup becomes the moment when reality enters the conversation rather than the moment when informed decisions become actions.

The organizations that close this gap consistently are not the largest or the most resourced. They are the ones that positioned interpretive capability where assumptions were being formed early enough to shape them, before commitments made that shaping impossible.

About the author

Elizabeth Walsh, PMP, ACRP-CP, is a clinical development executive specializing in execution strategy and delivery across complex development programs. With more than 25 years of experience spanning sponsor organizations, CROs, and research environments, she has led global Phase I–IV programs from early development through regulatory submission and commercialization.

Her work focuses on integrating clinical execution into development strategy, ensuring operational assumptions are tested early and sponsor oversight remains active across outsourced models. She has built and led Clinical Operations organizations, supported IND, NDA, and BLA submissions, and guided programs across oncology, rare disease, neurology, immunology, and infectious disease.

She is the founder of Walsh Clinical Advisory, where she advises biotech sponsors on clinical execution and oversight. She is the co-author of The Clinical Execution Blueprint: Aligning Strategy, Oversight, and Delivery in Clinical Development, published in 2026.