Imagine if doctors had to manually copy patient notes from one digital folder to another for every single medical study; it's slow and full of typos. This system acts like a smart bridge that automatically reads the hospital's records and streams the right data directly into the study's database. It removes the boring paperwork and lets medical staff focus on patients instead of data entry.
Clinical trial data collection is currently a manual, labor-intensive process that causes staff burnout and data entry errors. This inefficiency prevents medical centers from participating in more trials and slows down the development of new therapies.
An AI-driven platform that automatically maps and streams prospective clinical trial data from Electronic Health Records (EHR) to Electronic Data Capture (EDC) systems.
If you are a drug developer dealing with slow trial timelines and manual data entry errors — this project developed an AI-driven mapping system that streams data in real-time. This reduces the time spent waiting for medical centers to upload data and improves overall data quality.
If you are an EHR provider dealing with fragmented data export processes for research — this project developed a secure integration layer that allows frictionless data migration to trial databases. This adds a high-value feature for hospitals participating in global research.
If you are a CRO dealing with high staff burnout and turnover at medical centers due to labor-intensive data tasks — this project developed an automated EHR-to-EDC streaming platform. This enables the management of multi-site and multi-national trials with far less manual labor.
Based on available project data, specific pricing or cost structures are not disclosed.
Yes, the project specifically aimed to implement a platform scale-up to meet commercial requirements and enable the management of multi-site and multi-national clinical trials.
Based on available project data, the system is developed by Yonalink Ltd, but specific licensing terms are not provided.
The system uses AI-driven data mapping to ensure fast and frictionless integration with various EHR systems, as validated in multiple clinical settings.
The project period runs from 2022-09-01 to 2025-02-28, with the goal of demonstrating suitability for the EU market by the end of the term.
The project is led by a single Israeli SME, Yonalink Ltd. This lean structure indicates a high level of agility and direct control over the IP, though it lacks a diverse consortium of EU-based partners, relying instead on external validation at medical centers.
Contact Yonalink Ltd via their corporate office in Israel.
Contact us to explore integration opportunities with Yonalink's AI data mapping technology.
