Periodic Reporting for period 2 - YL System (A pioneer clinical trial management system to automatically collect, review and analyse prospective clinical trial data to prompt faster development of novel therapies.)
Okres sprawozdawczy: 2023-09-01 do 2025-02-28
Clinical trial data collection is a labor-intensive task that requires hospital staff to manually transfer trial data to the sponsor’s database (i.e. EDC). This process leads to staff burnout, mistakes in copying data, and overall inefficiency. High staff turnover rates among study employees are among the leading factors that prevent MCs (medical centers) from being able to participate in more clinical trials.
Yonalink is creating a global network of MCs that will provide clinical trial sponsors with EHR-to-EDC streaming based on AI-driven data mapping. This enables the collection of clinical trial data in real-time, improving trial efficiency and data quality, reducing staff burnout, and providing wider access to novel patient care opportunities.
The main objective of this project is to complete the development of Yonalink, and to demonstrate that the technology is suitable for the EU market. Specifically:
1. To finalize development to ensure fast and frictionless integration of the system within EU’s EHR systems.
2. To enable automated management of multi-site/multi-national clinical trials.
3. To validate the efficiency, security and economic benefits.
4. To implement a platform scale up to meet commercial requirements.
Yonalink is creating a global network of MCs that will provide clinical trial sponsors with EHR-to-EDC streaming based on AI-driven data mapping. This enables the collection of clinical trial data in real-time, improving trial efficiency and data quality, reducing staff burnout, and providing wider access to novel patient care opportunities.
The main objective of this project is to complete the development of Yonalink, and to demonstrate that the technology is suitable for the EU market. Specifically:
1. To finalize development to ensure fast and frictionless integration of the system within EU’s EHR systems.
2. To enable automated management of multi-site/multi-national clinical trials.
3. To validate the efficiency, security and economic benefits.
4. To implement a platform scale up to meet commercial requirements.
During the project’s first year, the in-house testing was completed, including front-end and back-end optimization with the first MCs. Yonalink is adding more MCs to its network to expand the data source pool and to learn and adapt more AI/LLM technologies for each varying integration scenario at different MCs. Based on the initial integration experiences, Technological changes were made to reduce the resources needed for integration at the MCs.
Yonalink completed the preliminary system validation and maintenance at four MCs during the project's first year in preparation for in-field validation in clinical settings.
During the project’s second year, technical and scientific progress was achieved. We have successfully completed the in-field validation of the Yonalink system in multiple clinical settings, with data being streamed from a range of MCs. This process involved fine-tuning the system's architecture to ensure smooth integration with EHR systems, optimizing the real-time data transfer to the EDC platform.
Key improvements were made to the backend infrastructure, enhancing system scalability and performance under the growing volume of clinical trial data. Front-end user interfaces were refined based on feedback from medical professionals, ensuring ease of use while maintaining high standards of data accuracy and security.
Additionally, we have expanded the network of MCs participating in the project, integrating data from diverse healthcare environments, which has provided valuable insights for continuous system adaptation. We have also made optimizations to reduce the time and resource requirements for MCs during integration, improving overall efficiency.
In terms of scientific advancements, the integration process has been validated for a variety of data types (resources) and clinical trial scenarios, supporting the successful collection and analysis of retrospective and prospective data.
Yonalink completed the preliminary system validation and maintenance at four MCs during the project's first year in preparation for in-field validation in clinical settings.
During the project’s second year, technical and scientific progress was achieved. We have successfully completed the in-field validation of the Yonalink system in multiple clinical settings, with data being streamed from a range of MCs. This process involved fine-tuning the system's architecture to ensure smooth integration with EHR systems, optimizing the real-time data transfer to the EDC platform.
Key improvements were made to the backend infrastructure, enhancing system scalability and performance under the growing volume of clinical trial data. Front-end user interfaces were refined based on feedback from medical professionals, ensuring ease of use while maintaining high standards of data accuracy and security.
Additionally, we have expanded the network of MCs participating in the project, integrating data from diverse healthcare environments, which has provided valuable insights for continuous system adaptation. We have also made optimizations to reduce the time and resource requirements for MCs during integration, improving overall efficiency.
In terms of scientific advancements, the integration process has been validated for a variety of data types (resources) and clinical trial scenarios, supporting the successful collection and analysis of retrospective and prospective data.
The current standard approach to EHR-to-EDC integration typically begins with a custom data mapping phase. This involves manually linking specific fields in the EHR to corresponding fields in the EDC - a process that takes months, incurs significant costs and requires ongoing maintenance whenever the study protocol changes or the EHR structure is updated.
Yonalink offers a breakthrough alternative: our system enables direct EHR-to-EDC integration, regardless of the data format. Patient data is transmitted as-is from the EHR, and Yonalink automatically identifies and matches the relevant fields to the EDC using advanced AI matching techniques. This eliminates the need for upfront mapping and reduces both setup time and long-term maintenance. Yonalink has made notable progress beyond the state of the art in advancing the integration process by demonstrating that the traditionally resource-intensive and time-consuming mapping phase, which often required months of manual effort, can be significantly streamlined. Yonalink now enables seamless EHR-to-EDC data transfer, allowing EHR systems to send data in any format while the system automatically processes and aligns it with the corresponding EDC fields. Ultimately, this innovation leads to shorter trial timelines, optimized resource allocation, and more precise data capture.
Key Results and Impacts:
• Improved Data Accuracy - The automated process minimizes human error, ensuring that data captured from the EHR is accurately mapped to the EDC fields.
• Scalability - The flexibility of the platform allows seamless integration with different EHR systems, regardless of data format, making it adaptable to various healthcare environments and trial settings.
• Operational Efficiency - Reducing manual intervention optimizing workflows and decreasing labor costs.
Actions Being Taken to Ensure Further Uptake and Success After the Project Ends:
1. Enhancing AI and Adaptive Machine Learning Capabilities - Ongoing research and development efforts focus on refining AI-driven data processing to improve accuracy, adaptability, and performance across diverse EHR systems.
2. Expanding Demonstration and Pilot Projects - Additional pilot studies are being conducted across various clinical trial settings to validate the scalability, reliability, and effectiveness of the integration approach.
3. Strengthening Market Access and Commercialization - Active efforts are underway to establish strategic partnerships with healthcare organizations, sponsors, and industry stakeholders to facilitate broader adoption and integration.
Yonalink offers a breakthrough alternative: our system enables direct EHR-to-EDC integration, regardless of the data format. Patient data is transmitted as-is from the EHR, and Yonalink automatically identifies and matches the relevant fields to the EDC using advanced AI matching techniques. This eliminates the need for upfront mapping and reduces both setup time and long-term maintenance. Yonalink has made notable progress beyond the state of the art in advancing the integration process by demonstrating that the traditionally resource-intensive and time-consuming mapping phase, which often required months of manual effort, can be significantly streamlined. Yonalink now enables seamless EHR-to-EDC data transfer, allowing EHR systems to send data in any format while the system automatically processes and aligns it with the corresponding EDC fields. Ultimately, this innovation leads to shorter trial timelines, optimized resource allocation, and more precise data capture.
Key Results and Impacts:
• Improved Data Accuracy - The automated process minimizes human error, ensuring that data captured from the EHR is accurately mapped to the EDC fields.
• Scalability - The flexibility of the platform allows seamless integration with different EHR systems, regardless of data format, making it adaptable to various healthcare environments and trial settings.
• Operational Efficiency - Reducing manual intervention optimizing workflows and decreasing labor costs.
Actions Being Taken to Ensure Further Uptake and Success After the Project Ends:
1. Enhancing AI and Adaptive Machine Learning Capabilities - Ongoing research and development efforts focus on refining AI-driven data processing to improve accuracy, adaptability, and performance across diverse EHR systems.
2. Expanding Demonstration and Pilot Projects - Additional pilot studies are being conducted across various clinical trial settings to validate the scalability, reliability, and effectiveness of the integration approach.
3. Strengthening Market Access and Commercialization - Active efforts are underway to establish strategic partnerships with healthcare organizations, sponsors, and industry stakeholders to facilitate broader adoption and integration.