Clinical Trials Without Bias
Continuous bias monitoring for your trial data. Issues detected automatically, explained clearly, corrected before submission.
Bias Threatens Trial Validity
From demographic underrepresentation to methodological flaws, bias compromises scientific validity, distorts treatment effects, and triggers regulatory rejection. Most issues remain invisible until submission—when it's too late.
of clinical trials contain systematic bias
cost per Phase III trial amendment due to bias
potential cost reduction with bias correction
Cost of Late Discovery
What it costs when bias is caught at submission vs. during the trial
Estimates based on Phase II/III trials. Actual costs vary by therapeutic area, trial size, and regulatory jurisdiction.
Business and Clinical Impact
Financial Risk
Clinical trials cost $17M (Phase I) to $200M (Phase III) on average. Bias-driven trial amendments add further costs, and studies with high risk of bias show exaggerated treatment effects that fail to replicate, wasting development investment.
Regulatory Scrutiny
FDA and EMA increasingly require documented evidence of representative enrollment and robust methodology. Trials with inadequate randomization, poor blinding, or unrepresentative populations face rejection.
Documented Bias Types
Manual review catches some. Regulatory checklists flag a few more. Clinequal systematically detects all of them.
Detected automatically. Explained clearly.
How It Works
Your trial data flows through four stages. Bias is caught early, explained clearly, and corrected before it becomes a regulatory problem.
Detect
Continuous scanning across 21 trial-relevant bias types. Issues surface as they emerge, not at submission.
Explain
Explainable AI traces each bias to its root cause—site selection, protocol design, or enrollment patterns.
Simulate
Model corrections before implementing them. See how changes affect bias metrics in real time.
Report
Audit-ready documentation for regulatory submission, aligned with Cochrane methodology.
See It in Action
Explore bias detection on sample clinical trial datasets. No signup required.
2 sample trials • ~2 min walkthrough
Recognition & Achievements
Selected from 495 applicants for Fit4Start Luxembourg. Winner of the US-Italy Hackathon and Startcup Campania Social Impact Prize.
Fit4Start Finalist
Luxembourg Accelerator Program
Luxembourg
Academic Collaborations
Leadership Team
Expertise spanning AI/ML, bioinformatics, healthcare data science, software engineering, and regulatory compliance.
Scientific Board
World-class researchers in clinical pathology, biomedical engineering, AI, and neurology.
Adrian Elmi Telander
Scientific Board
Full Professor of Neurology
Advisory Board
Expertise in startups, health tech, and strategic growth.
Latest Insights
Stay informed on clinical trial equity and AI-driven bias detection.
Reduce Regulatory Risk with Representative Datasets
Schedule a consultation to see how Clinequal addresses bias in your trial data before submission.
info@clinequal.com