Periodic Reporting for period 1 - 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.)
Reporting period: 2022-09-01 to 2023-08-31
Clinical trial data collection is a labor-intensive task that requires hospital staff to manually transfer trial data to the sponsor’s database (e.g. EDC). This process leads to staff burnout, data copying mistakes, repetitive monitoring cycles, and overall inefficiency. High burnout and staff turnover rates among study employees are among the leading factors that prevent 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 and AI-driven CRF data mapping. This enables collecting clinical trial data in real-time, improving trial efficiency and data quality, reducing medical center staff burnout ,and providing wider access to novel patient care opportunities.
The main objective of this EIC project is to complete the development of the Yonalink system, and to demonstrate that the technology is suitable for the EU market. Specifically:
1. To finalize the Yonalink’s system development to ensure fast and frictionless integration of the system within the most common EU EHR systems.
2. To enable automated and reliable management of multi-site/multi-national clinical trials.
3. To validate the efficiency, security and economic benefits of Yonalink, at migrating EHR data from a few sites.
4. To implement a platform scale up to meet commercial requirements including EU directives for clinical data management and exploitation
Yonalink is creating a global network of MCs that will provide clinical trial sponsors with EHR-to-EDC streaming and AI-driven CRF data mapping. This enables collecting clinical trial data in real-time, improving trial efficiency and data quality, reducing medical center staff burnout ,and providing wider access to novel patient care opportunities.
The main objective of this EIC project is to complete the development of the Yonalink system, and to demonstrate that the technology is suitable for the EU market. Specifically:
1. To finalize the Yonalink’s system development to ensure fast and frictionless integration of the system within the most common EU EHR systems.
2. To enable automated and reliable management of multi-site/multi-national clinical trials.
3. To validate the efficiency, security and economic benefits of Yonalink, at migrating EHR data from a few sites.
4. To implement a platform scale up to meet commercial requirements including EU directives for clinical data management and exploitation
During the first year of the project we have completed the in house-testing of the Yonalink System, including front-end optimization and back-end optimization with the first medical centres. Yonalink will be adding more MCs to the project to continue and expand the data source, as well as to learn and adapt the technology as needed for each varying integration scenario at the different medical centres. Based on the initial integration experiences, changes are being made to the technology to reduce the medical centre’s resources needed for the integration.
Yonalink has already completed the preliminary system validation and maintenance at four Medical Centers, and is ready to begin the in-field validation in clinical settings.
Yonalink has already completed the preliminary system validation and maintenance at four Medical Centers, and is ready to begin the in-field validation in clinical settings.
The state of the art in EHR-to-EDC is to start a trial with an ad-hoc phase of data mapping that maps specific EHR fields to specific EDC fields. This phase is long (typically months), costly and requires permanent maintenance as EDC protocol undergoes amendments and as EHR data structures change.
Yonalink, clearly going beyond the state of the art, has demonstrated that this phase can be completely skipped by creating a very loose integration between the EHR and the Yonalink Connect system, in which the EHR sends patient data in ANY format and Yonalink Connect uses AI techniques as well as adaptive learning to match specific EHR data with specific EDC forms. As the mapping phase is skipped in its entirety, months of manual labour and project delays are spared, resulting in faster clinical trials and more accurate data capture.
Yonalink, clearly going beyond the state of the art, has demonstrated that this phase can be completely skipped by creating a very loose integration between the EHR and the Yonalink Connect system, in which the EHR sends patient data in ANY format and Yonalink Connect uses AI techniques as well as adaptive learning to match specific EHR data with specific EDC forms. As the mapping phase is skipped in its entirety, months of manual labour and project delays are spared, resulting in faster clinical trials and more accurate data capture.