AI in Clinical Trials: Reporting/Analytics with TrialKit AI
Bring your studies into the future with AI-driven speed and efficiency for data analysis and reporting.
What is TrialKit AI?
TrialKit AI is an integrated artificial intelligence engine built into the TrialKit platform. It empowers clinical research teams to query, analyze, and interpret complex clinical trial data in seconds—not months—using natural language and automated intelligence. This isn’t a bolt-on tool or generic dashboard overlay. TrialKit AI is purpose-built for life sciences, designed to work across all phases of clinical research. The platform supports:
Natural language querying across EDC, eCOA/ePRO, imaging, and wearable device data
Advanced biostatistical analysis with instant p-values and confidence intervals
Integrated visual dashboards that update in real-time
Support for multi-trial, multi-source analytics
Compliance with HIPAA, FDA 21 CFR Part 11, and GDPR
How TrialKit AI Works
TrialKit AI, known internally as Floyd, draws from over 50 built-in reports and data inputs, including TrialKit’s native EDC and real-world data sources like wearables and imaging. Whether you’re monitoring adverse events, enrollment trends, or site performance, you can simply ask:
“Which participants had an adverse event within 15 days of starting treatment?”
“What’s the screen failure rate by site this month?”
“Show me a forecast for enrollment based on current pace.”
Floyd responds instantly with visual outputs and statistically valid results, saving teams weeks of manual work and back-and-forth queries.
Vision AI: Intelligent Medical Image Recognition
TrialKit AI goes beyond numbers; it sees.
Our Vision AI module uses high-resolution DICOM image ingestion to detect anomalies like tumors or fractures by analyzing pixel-level patterns. Unlike human eyes, Vision AI recognizes complex data signatures and can:
- Highlight anomalies invisible to radiologists
- Enlarge areas of interest for review
- Predict progression based on pattern modeling
This offers a breakthrough in oncology and radiology-driven trials by identifying disease earlier and improving data objectivity. While final diagnoses remain human-led, Vision AI adds a new dimension to pre-screening and image-based data validation.
Virtual Trials: From 5 Years to 5 Minutes
TrialKit AI supports virtual participants—AI-modeled profiles that simulate disease progression over time. These virtual trials:
- Compress multi-year study timelines into minutes
- Project treatment outcomes using modeled population data
- Enable rapid iteration of study designs before launch
- Support FDA-guided initiatives for AI in preclinical research
By integrating trial data from millions of participants and thousands of studies, TrialKit AI helps you simulate and optimize trial outcomes before the first patient is enrolled.
See TrialKit AI in Action
Access this on-demand, workshop-style webinar for an introduction to TrialKit AI’s dynamic analytics and reporting capabilities.
Real-World AI Use Cases
Combine EDC, ePRO/eCOA, and wearable data for real-time safety tracking
Automatically flag sites with protocol deviations
Predict trial delays and enrollment gaps
Detect image-based anomalies for early intervention
Simulate outcomes for different populations using virtual participants
Why Choose TrialKit AI for Your Clinical Trials?
Clinical trials are collecting more data than ever before – and the numbers are only going to continue to increase. With too much data for teams to handle effectively on their own, TrialKit AI gets you answers in seconds instead of days or weeks. Harness the power of artificial intelligence to analyze vast amounts of data in real-time, dramatically shortening the time required to derive meaningful results.
Seamless data management
TrialKit AI streamlines the reporting process through its intuitive interface and natural language processing (NLP) capabilities. The AI’s ability to interpret user queries in plain language means that researchers can interact with the system effortlessly, reducing the learning curve and enabling rapid adoption across teams.
Accelerated and accurate data analysis
Accuracy in data analysis is non-negotiable in clinical research. TrialKit AI automates complex data processing tasks, minimizing the potential for human error and ensuring that the insights generated are both reliable and timely.
Advanced visualization for informed decision-making
TrialKit AI transforms your data – regardless of type or source – into easily interpretable visual formats. With its advanced visualization tools, users can create custom dashboards that provide real-time access to study data, allowing for quick and informed decision-making.
Delivering new insights
Whether tracking patient enrollment, monitoring adverse events, or analyzing treatment efficacy, TrialKit AI’s visualization capabilities ensure that study teams are always equipped with the most current and actionable insights. TrialKit AI is the help you need to dive deeper into your data than ever before.
Efficiency gains and cost savings
The efficiencies offered by TrialKit AI translate directly into cost savings. By automating time-consuming tasks traditionally handled by data managers and statisticians, this platform reduces labor costs and shortens study timelines.
Trust and transparency in AI-driven results
TrialKit AI addresses concerns around accuracy and trustworthiness head-on, offering complete transparency through its “thought pathway” feature. Users can see exactly how TrialKit AI arrived at its conclusions, ensuring that the results can be tested, verified, and trusted.
