A client sends you an RFI for a Phase 3 oncology trial with 500 patients across 8 countries. Can you run it? What will it cost? How long to activate sites? What's the risk of enrollment failure?
If your feasibility assessment takes days and still leaves the client guessing, you're losing bids to faster, more data-driven competitors.
In this guide, we'll cover the complete CRO feasibility assessment framework — the five dimensions every bid team should evaluate, how to source the data from ClinicalTrials.gov and other public sources, and how to deliver a go/no-go recommendation the client can act on.
The Five Dimensions of CRO Feasibility
A rigorous feasibility assessment covers five areas:
- Enrollment feasibility — Can we hit the target enrollment?
- Geographic footprint — Where are the sites, and which regions are best for recruitment?
- Design complexity — How operationally demanding is the protocol?
- Patient pool competition — Are other trials draining the same patient pool?
- Go/No-Go recommendation — Should we bid, and at what price?
Let's break down each dimension.
1. Enrollment Feasibility
This is the make-or-break question. If you can't enroll the trial, nothing else matters.
What to Evaluate
- Target enrollment vs. realistic eligible population. How many patients exist in your target geographies with the indication? How many are already enrolled in competing trials?
- Competing trial drain. A Phase 3 NSCLC trial with 5 competing trials in the same region will struggle to enroll.
- Inclusion/exclusion strictness. Broad criteria = easier enrollment. Narrow criteria (specific biomarkers, prior treatments) = harder.
- Recruitment strategy adequacy. Does the protocol have a realistic recruitment plan, or does it assume patients will appear?
How to Source the Data
- CT.gov: Current enrollment numbers, competing trials (search by condition + status = RECRUITING), inclusion/exclusion criteria
- Epidemiology data: WHO, CDC, or national health databases for disease prevalence
- Competing trials: CT.gov search by condition + RECRUITING status to count active competitors
Feasibility verdicts
- Realistic: ≤1,500 patients, common indication, ≤3 competing trials
- Challenging: 1,500–4,000 patients, rare disease, or 4–10 competing trials
- Unrealistic: >4,000 patients, ultra-rare indication, or >10 competing trials
2. Geographic Footprint
Where you run the trial determines enrollment speed, regulatory complexity, and cost.
What to Evaluate
- Site count and distribution. Does the protocol specify countries? Are those countries realistic for the indication?
- Patient density. Which regions have the highest prevalence of the target condition?
- Regulatory speed. How long does ethics review take in each country? (FDA: 30 days, EMA: 60 days, PMDA: 90+ days)
- Site infrastructure. Does the region have experienced sites with the required equipment and expertise?
Recommended Regions by Therapeutic Area
- Oncology: US (largest patient pool, fastest ethics), EU (centralized ethics via CTIS), Asia-Pacific (fast enrollment, lower cost)
- Rare disease: US + EU (patient registries, orphan drug incentives), avoid regions with no prior rare disease trials
- Cardiology: US, EU, Eastern Europe (high site density, experienced investigators)
- Pediatrics: US, EU, Japan (strict regulations, specialized sites required)
3. Design Complexity
How hard is the trial to run? Complexity drives cost, timeline, and risk.
Key Complexity Drivers
- Intervention model: Parallel = simpler. Crossover/Factorial = harder (blinding, washout periods).
- Blinding: Open-label = easiest. Double-blind = drug management complexity. Blinded endpoint adjudication = adds 2–4 months.
- Central lab requirements: Biomarker-driven trials need centralized labs. Adds $3K–$8K/patient and 2–3 months for lab setup.
- Imaging requirements: Central imaging review adds $2K–$5K/patient and 1–2 months.
- Monitoring intensity: Number of visits per patient. More visits = higher cost and higher dropout risk.
- Special populations: Pediatrics, geriatrics, renal/hepatic impairment — require specialized sites and protocols.
Complexity tiers
- Low: Oral drug, standard labs, single country, <10 visits → $8K–$15K/patient
- Medium: IV infusion OR central imaging OR 2–3 countries OR 10–20 visits → $20K–$45K/patient
- High: Cell/gene therapy OR hospitalization OR >20 visits OR biomarker-heavy → $50K–$120K/patient
4. Patient Pool Competition
Even if your design is perfect and your sites are ready, competing trials can drain the patient pool.
How to Assess Competition
- Search CT.gov for competing trials: Same condition + RECRUITING status + overlapping geographies
- Count overlapping trials: 5+ trials in the same indication + region = high overlap risk
- Assess patient availability: "Tight" if multiple trials compete for the same pool. "Adequate" if indication is common and trials are in different regions.
Mitigation Strategies
- Distinct inclusion/exclusion criteria: Target a subpopulation not covered by competing trials
- Under-served geographies: Run sites in regions with no competing trials
- Patient advocacy partnerships: Particularly effective for rare diseases
- Extended recruitment window: Plan for a longer enrollment period if competition is high
5. Go/No-Go Recommendation
After assessing the four dimensions above, deliver a clear recommendation:
Recommendation framework
- GO: Enrollment realistic (≤2,000 for common indication) + design tier low/medium + sponsor has ≥1 prior completed trial + no significant competition
- CONDITIONAL GO: Enrollment challenging OR sponsor inexperienced OR complex design — state exact conditions to de-risk
- NO GO: Enrollment >4,000 OR ultra-rare with no patient registry OR sponsor no prior trials AND high complexity
The recommendation should be specific and actionable. "Conditional go — recommend adding 2 sites in Eastern Europe to de-risk enrollment" is useful. "We think this is doable" is not.
Pricing Feasibility Trials
Once you've decided to bid, the next question is price. Here's a framework:
- Calculate per-patient cost based on complexity tier (see Section 3 above)
- Add site costs: Activation ($50K–$150K/site), monitoring (4–8 days/site), closeout ($20K–$50K/site)
- Add overhead: Project management (10–15% of total), regulatory, data management, statistical analysis
- Factor in risk: Add 10–20% contingency for enrollment delays, protocol amendments, or site dropouts
- Competitive positioning: If the client is evaluating multiple CROs, price 5–10% below your top-end to win — but know your floor
Delivering the Feasibility Report
A good feasibility report is concise, structured, and actionable. Include:
- Executive summary: One paragraph — enrollment feasibility, complexity tier, competition level, and go/no-go recommendation
- Enrollment check: Target vs. realistic, competing trials, recruitment strategy, timeline
- Geographic strategy: Recommended regions with rationale and barriers, regions to avoid
- Design complexity: Tier, cost drivers, estimated setup timeline
- Patient pool competition: Overlap risk, competing trials, mitigation strategies
- Bidding considerations: Pricing guidance, contract terms to clarify, risks to flag
The report should be data-driven — cite CT.gov enrollment numbers, competing trial counts, and epidemiology data. Avoid vague statements like "enrollment should be feasible." Say "enrollment is realistic based on 3,200 estimated eligible patients across 5 proposed sites with 2 competing trials."
Common Feasibility Mistakes
Mistake 1: Underestimating competition. Always search CT.gov for ALL recruiting trials in the same indication — not just the ones you know about.
Mistake 2: Ignoring site activation timelines. A site in Eastern Europe might be cheaper, but ethics review takes 3–4 months. Factor this into your enrollment timeline.
Mistake 3: Pricing too low to win. A losing bid wastes resources. A winning bid at a loss costs money. Know your floor and walk away if the client won't meet it.
Mistake 4: No contingency planning. Things go wrong — enrollment stalls, sites drop out, protocols get amended. Build 10–20% contingency into your bid.
The Future of CRO Feasibility
In 2026, AI is transforming feasibility assessment:
- Automated data sourcing: Pull CT.gov data, epidemiology, and competing trial info with one click
- AI-powered scoring: Enrollability risk, complexity tier, and competition level calculated from protocol data
- Structured reports: Generate feasibility reports in minutes, not days — ready to drop into proposals
- Real-time monitoring: Track competing trials and adjust feasibility assessment as new data emerges
The CROs that win bids in 2026 aren't the ones with the lowest price — they're the ones with the fastest, most data-driven feasibility assessments.
Conclusion
CRO feasibility assessment is a structured process: enrollment feasibility → geographic footprint → design complexity → patient pool competition → go/no-go recommendation.
The teams that win are the ones who do this fast and well. Source data from CT.gov and public databases, apply the five-dimension framework, and deliver a recommendation that's specific, actionable, and backed by data.
Try TrialScope free — AI-powered CRO feasibility assessment with enrollment check, geographic strategy, and go/no-go recommendation — right inside ClinicalTrials.gov.
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