The startup offers a real-time data quality platform for clinical trials that integrates data from multiple sources to provide a unified view. It automates the identification of data deviations and trends, enabling clinical research organizations to quickly recognize data quality issues and enhance trial efficiency.
Funding
$3.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Clinical trials often suffer from fragmented data scattered across multiple sources, leading to delays in identifying critical data deviations and hindering efficient trial oversight. Manual data review processes are time-consuming and prone to errors, making it difficult to proactively address potential risks to patient safety and data integrity.
Solution
studyOS offers a real-time data quality platform that centralizes clinical trial data from various sources, providing a unified view for enhanced study oversight. The platform leverages an AI-powered Clinical Trial Agent, "Ash," to automate the detection of data discrepancies, anomalies, and trends, enabling clinical research teams to identify and resolve issues early in the trial lifecycle. By automating data review and generating actionable insights, studyOS reduces manual workload, streamlines clinical operations, and ensures compliance with regulatory standards such as ICH E6 R3. The platform's agentic AI produces SQL, allowing for validation, repeatability, and reproducibility of analyses.
Target Audience
The primary target audience includes clinical-stage biotech companies, clinical research organizations (CROs), and clinical operations teams seeking to streamline data management, improve data quality, and enhance trial efficiency.
Features
- Unified data hub consolidating data from EDC, eCOA, ePRO, labs, and other sources
- Real-time risk detection and dynamic risk assessment
- AI-powered central monitoring to oversee trial activities and identify irregularities
- Automated query generation tailored to specific protocols and study patterns
- Customizable listings and dashboards for displaying key metrics
- Patient profiles with real-time data synchronization based on the CDISC standard
- Integration with existing clinical data systems