Operational failure patterns
Operational reasons dominate stopped clinical trials
12,086 records, or 51.3% of the stopped-trial database, are classified as operational. That is the strongest reason not to treat every stopped trial as a failed drug.
- The current database contains 23,575 terminated, suspended, and withdrawn trial records.
- 12,086 records, or 51.3%, are classified as operational stops.
- 8,662 operational records are terminated, 3,165 are withdrawn, and 259 are suspended.
- Oncology is the largest operational disease-area slice with 4,201 records.
- M.D. Anderson Cancer Center has the largest operational stopped-record count in this dataset with 203 records.
The strongest result in the database
The clearest high-level finding is that operational reasons account for more stopped trial records than efficacy, futility, or safety signals. That is not a small technical distinction. It changes what the word failure should mean when someone searches a registry of terminated, suspended, and withdrawn studies.
A stopped study may reflect recruitment, feasibility, site execution, logistics, sponsor decisions, or an unclear administrative history. Those outcomes matter, but they do not automatically show that a drug or biological hypothesis failed.
What counts as an operational stop
Operational source language can describe poor recruitment, low accrual, site problems, feasibility concerns, supply constraints, study-design changes, or a sponsor decision that is not presented as an efficacy or safety result.
These records are still useful evidence. Repeated enrollment or execution problems can show that a development strategy is difficult to run in practice. The careful conclusion is operational failure or feasibility risk, not automatic drug failure.
Why status alone gives the wrong answer
Terminated, suspended, and withdrawn are registry statuses. They tell us that a study did not continue as originally planned, but they do not explain why. The stop-reason language is where the scientific or operational interpretation begins.
This is why a count of terminated trials by sponsor is easy to misuse. Large organizations run more studies, academic centers often manage complex investigator-led programs, and operational stops can dominate the total. A useful comparison needs a denominator and a reason classification.
Where operational stops concentrate
The disease-area and sponsor tables below show where operational records are most visible in the current database. They should be read as workload and pattern indicators, not league tables of poor performance.
The better research question is whether a disease area, study phase, patient population, or sponsor repeatedly encounters the same feasibility problem. That is more informative than treating every stop as one undifferentiated failure event.
How I would use this result
I would first separate operational records from efficacy/futility and safety records. Then I would filter by sponsor, phase, disease area, and intervention, looking for repeated wording or related study designs.
Finally, I would open the source NCT records. The classification is a screening layer that makes a large dataset usable; the registry language remains the primary evidence for any important conclusion.
Operational stop status mix
| Trial status | Operational records |
|---|---|
| Terminated | 8,662 |
| Withdrawn | 3,165 |
| Suspended | 259 |
Operational stops compared with biological signals
| Reason classification | Current records |
|---|---|
| Operational | 12,086 |
| Efficacy/futility | 1,100 |
| Safety | 719 |
Largest operational disease-area slices
| Disease area | Operational records |
|---|---|
| Oncology | 4,201 |
| Other | 2,821 |
| Infectious Disease | 832 |
| Gastroenterology & Hepatology | 790 |
| Cardiovascular | 727 |
| Neurology | 495 |
Largest operational sponsor counts
| Sponsor | Operational records |
|---|---|
| M.D. Anderson Cancer Center | 203 |
| National Cancer Institute (NCI) | 173 |
| Novartis Pharmaceuticals | 169 |
| Pfizer | 146 |
| Massachusetts General Hospital | 116 |
| Mayo Clinic | 111 |
Continue from here
FAQ
Is an operational stop a clinical trial failure?
It can be an execution or feasibility failure, but it is not automatically evidence that the intervention failed biologically.
Why are operational records so common?
Clinical trials are difficult to recruit and operate. Feasibility, site execution, logistics, study design, funding, and sponsor decisions can stop a study before biology is fully tested.
Should sponsors be ranked by operational stop count?
Not without context. Larger and more active sponsors naturally run more trials, so counts should be compared with total volume, phase, disease area, and source wording.
Source note: counts are generated from the current ClinicalTrials.gov-derived stopped-trial dataset used by ClinicalTrialFailures.com. These labels are analytical screening signals, not medical advice.