Why Protocol Complexity Is Slowing First Patient In — And How Small Sponsors Can Fix Start-Up Inefficiencies

By Jessica Cordes, Senior Consultant for Clinical Operations, Clinical Excellence GmbH

Clinical trial start-up inefficiencies are rarely caused by a single bottleneck. Yet when timelines slip, discussions often focus on individual delays such as contract negotiations, ethics approvals, or site activation. What is frequently overlooked is a more fundamental issue: the increasing complexity of clinical trial protocols and the way this complexity cascades across all start-up activities.

For small and emerging biotech companies, this issue is particularly critical. Limited internal experience, resource constraints, and reliance on external partners make it difficult to absorb inefficiencies. As a result, delays to first patient in are not just frustrating. They can impact funding milestones, investor confidence, and the overall viability of a development program.

Protocol complexity is not only a scientific or regulatory concern but an operational risk that directly affects timelines, costs, and execution quality. Addressing this challenge requires sponsors to change their approach to protocol design, feasibility, and start-up processes.

The Hidden Cost Of Protocol Complexity

Over the past decade, clinical trial protocols have become significantly more complex . Increased data collection requirements, more endpoints, adaptive designs, and the incorporation of biomarkers or digital tools all contribute to this trend. While these changes are often scientifically justified, they create substantial operational consequences.

Protocols that are not designed with execution in mind tend to require more amendments, more clarification cycles with sites, and more negotiation with institutional stakeholders. Each amendment triggers a cascade of activities, including re-review by ethics committees, updates to contracts, and retraining of site personnel. These cycles introduce delays that accumulate quickly during start-up.

From an operational perspective, complexity increases variability. Sites interpret requirements differently, feasibility assessments become less reliable, and resource needs are harder to predict. For small sponsors, this variability is particularly difficult to manage because there is a limited internal buffer to absorb inefficiencies.

Regulatory guidance already recognizes that clinical trial design should avoid unnecessary complexity. Protocols, procedures, and data collection requirements should be fit for purpose and operationally feasible. Yet in practice, many trials still move forward with designs that are scientifically robust but operationally challenging.

Start-Up Inefficiency Is A System Problem

Start-up inefficiency is often treated as a series of isolated issues: delays in feasibility, slow contract negotiations, or prolonged ethics approvals. In reality, these are symptoms of a broader systemic problem.

Clinical trial start-up involves multiple interdependent processes, including feasibility assessment, site selection, budgeting, contracting, regulatory submissions, and site preparation. When protocol complexity increases, it affects each of these processes simultaneously.

For example, complex inclusion and exclusion criteria make it more difficult for sites to assess patient availability during feasibility. This leads to less reliable feasibility data, which in turn affects site selection decisions. Similarly, extensive schedules of assessments and bespoke procedures increase the burden on sites, resulting in longer contracting discussions and higher costs.

The key issue is that these dependencies are often not managed proactively. Instead of aligning processes, many organizations still treat a start-up as a linear sequence of activities. This approach creates delays because each step waits for the previous one to be completed, even when activities could be performed in parallel.

The Sequential Thinking Trap

One of the most common drivers of delay is what can be described as sequential thinking. In many organizations, start-up activities are approached as a checklist:

• finalize protocol
• conduct feasibility
• select sites
• negotiate contracts
• submit to ethics committees
• initiate sites.

While this structure appears logical, it does not reflect the reality of how clinical trials operate. Each of these steps is interconnected. Decisions made in one area affect all others.

Sequential execution leads to several inefficiencies. Feasibility is conducted without input from contracting teams, resulting in unrealistic assumptions about site costs or timelines. Site selection is finalized before a clear understanding of regulatory readiness in different regions. Contracts are negotiated without full alignment on operational requirements, leading to rework later in the process.

This approach is particularly problematic for complex protocols. The more variables involved, the greater the need for coordination across functions. Without this coordination, delays are inevitable.

A more effective model is to treat a start-up as an integrated process, where feasibility, site selection, and operational planning are aligned from the beginning. This requires a shift in mindset from sequential execution to parallel planning.

Why Small Sponsors Are Disproportionately Affected

Large pharmaceutical companies often have established processes, dedicated teams for each function, and historical data to support decision-making. Small biotech companies do not have these advantages.

Emerging sponsors typically operate with lean teams. Individuals often cover multiple roles, and processes are still being developed. External partners such as CROs, central labs, and logistics providers play a significant role in execution. While this model offers flexibility, it also increases the risk of fragmentation.

Without a strong internal framework, coordination across stakeholders becomes challenging. Decisions are made in silos, and alignment is achieved late in the process, if at all. This leads to rework, delays, and increased costs.

In addition, small sponsors often enter the clinical phase under time pressure. There is a strong focus on reaching first patient in quickly, sometimes at the expense of thorough planning. Protocols may be finalized without sufficient input from operational stakeholders, and feasibility assessments may rely on limited or incomplete data.

The result is a cycle of reactive adjustments. Issues are addressed as they arise, rather than being anticipated and mitigated early. This approach not only delays start-up but also increases the risk of protocol deviations and data quality issues during trial conduct.

Effective sponsor oversight is critical in this context. A structured approach to identifying and managing risks can improve both efficiency and data reliability. However, many small organizations have not yet established such frameworks at the start-up stage.

Rethinking Protocol Design: From Scientific Concept To Operational Blueprint

Addressing start-up inefficiencies begins with protocol design. Protocols should be seen not only as scientific documents but also as operational blueprints.

This means considering execution aspects from the earliest stages of development. Questions that need to be addressed include:

• Are eligibility criteria realistic based on available patient populations?
• Can sites perform all required procedures with existing infrastructure?
• Is the schedule of assessments manageable in routine clinical practice?
• Are data collection requirements aligned with the study objectives?

These questions require input from multiple stakeholders, including clinical operations, regulatory, medical, and external experts. Early engagement with sites can provide valuable insights into feasibility and potential challenges.

The goal is not to simplify protocols at the expense of scientific rigor. Instead, it is to ensure that complexity is purposeful and justified. Every procedure, endpoint, and data point should be linked to a clear objective.

When protocols are designed with execution in mind, the need for amendments decreases. This has a direct impact on start-up timelines, as fewer changes translate into fewer reapproval cycles and less rework.

Moving From Sequential To Parallel Planning

One of the most effective ways to reduce start-up timelines is to shift from sequential execution to parallel planning. In a parallel model, key activities are initiated simultaneously and aligned continuously. Feasibility assessments inform contracting discussions, while regulatory requirements are considered during site selection. Internal functions and external partners are engaged early to ensure alignment on expectations.

This approach requires structured coordination. Clear roles and responsibilities must be defined, and communication channels need to be established. Regular cross-functional meetings can help identify dependencies and resolve issues before they escalate.

Parallel planning also allows for better use of data. Real-time insights from feasibility can be used to adjust site selection strategies, while feedback from contracting can inform budget assumptions. This iterative process leads to more accurate planning and fewer delays.

Data-Driven Feasibility And Site Selection

Traditional feasibility approaches often rely on surveys and self-reported data from sites. While these methods provide useful input, they are prone to bias and variability. Sites may overestimate their capabilities or underestimate the time required for certain activities.

Data-driven approaches can improve the accuracy of feasibility assessments. Historical performance data, real-world evidence, and operational metrics can provide a more objective basis for decision-making.

For example, data on patient recruitment rates, screen failure ratios, and site activation timelines can help identify sites that are more likely to deliver results. This reduces the risk of selecting sites that delay timelines due to a lack of experience or capacity.

Improved feasibility and site selection have a direct impact on start-up efficiency. When sites are selected based on robust data, fewer adjustments are needed later in the process.

Strengthening Sponsor Oversight And Governance

Start-up inefficiencies are often exacerbated by a lack of clear oversight. Without defined governance structures, decisions are delayed, responsibilities are unclear, and issues are not addressed promptly.

A structured sponsor oversight framework can significantly improve performance. This includes:

• defining clear ownership for each start-up activity
• establishing decision-making processes
• implementing regular progress tracking
• identifying and managing risks proactively.

Risk-based approaches are particularly effective. By focusing on the most critical factors that impact patient safety and data quality, sponsors can allocate resources more efficiently.

Oversight should not be limited to internal teams. External partners also need to be integrated into governance structures. Clear expectations, communication processes, and performance metrics are essential for effective collaboration.

The Role Of Emerging Tools

Digital solutions are increasingly being introduced to support clinical trial start-up. Digital protocols, machine-readable formats, and integrated planning tools have the potential to improve efficiency.

These tools can reduce manual data entry, improve consistency, and facilitate data sharing across systems. For example, machine-readable protocols can support automated generation of study documents and reduce the risk of transcription errors.

However, technology alone will not solve start-up inefficiencies. Without clear processes and alignment, digital tools may simply add another layer of complexity.

The focus should therefore be on combining structured processes with appropriate technology. Tools should support decision-making and coordination, not replace them.

Start-Up Efficiency Begins With Better Decisions

Delays in clinical trial start-up are often attributed to external factors such as regulatory requirements or site availability. While these factors play a role, many inefficiencies originate within the sponsor organization.

Protocol complexity, lack of alignment across functions, and sequential execution models are key drivers of delay. Addressing these issues requires a shift in how clinical trials are planned and executed.

For small and emerging sponsors, this shift is particularly important. Efficient start-up processes can make the difference between meeting development milestones and falling behind.

The most effective approach is to focus on early and structured decision-making. Protocols should be designed with execution in mind, feasibility should be data-driven, and start-up activities should be aligned from the beginning. Strong oversight and clear governance provide the foundation for coordination and risk management.

Start-up inefficiency is not inevitable; it is the result of decisions and processes that can be improved. By addressing protocol complexity and adopting a more integrated approach, sponsors can reduce timelines, control costs, and set their clinical trials up for success.

About The Author:

Jessica Cordes is a clinical operations expert and founder of Clinical Excellence GmbH with more than 15 years of experience planning, governing, and executing international clinical trials, with a focus on oncology and cell and gene therapies. She supports small biotech sponsors in building practical, GCP-compliant structures for clinical trial planning, startup, sponsor oversight, vendor management, risk management, and operational decision-making. The benchmark report “Global Clinical Trial Approval and Setup Timelines” reflects her focus on translating regulatory requirements into usable planning guidance for global clinical trial teams. Since 2023, Jessica has worked as an independent consultant and trainer and provides GCP training, templates, and practical implementation support through the Clinical Excellence Training Academy.