Periodic Reporting for period 2 - BIOMATDB (Advanced Database for Biomaterials with Data Analysis and Visualisation Tools extended by a Marketplace with Digital Advisors)
Reporting period: 2023-12-01 to 2025-02-28
Biomaterials are synthetic or natural materials that can be used for medical purposes, such as artificial organs, prostheses, or tissue replacement. Due to the high demand for medical implants, the rising prevalence of cardiovascular diseases, and the increasing research on regenerative medicine, EU has supported biomaterial research for many years, resulting in numerous publications, patents, and clinical trials. However, one of the main challenges is to provide accessible and well-structured data of biomaterials for different stakeholders. Such data should include not only the metadata and properties of biomaterials, but also their biocompatibility, performance, and safety. The synthesis of this knowledge is difficult because of the large and diverse amount of data in the biomaterials’ domain. Against this background, the BIOMATDB project developed an advanced database (biomaterialdatabase.com) which provides detailed information on the properties of biomaterials, based on the testing results from various research outputs. The database has flexible tools for data analysis and visualisation, to help users search and select the best biomaterials for their needs. Additionaly, BIOMATDB project provided a web-optimised information marketplace (biomaterialmarketplace.com) with connected digital advisors to support companies, especially SMEs, to get market access and visibility for their biomaterial products. As part of its commitment to advancing biomaterial standards, BIOMATDB engaged with policymakers to explore the potential for establishing a biocompatibility label. This initiative aimed to address key challenges while aligning with existing biomaterial quality standards. The BIOMATDB project has advanced biomaterial research by optimizing knowledge structuring, improving data accessibility, and enabling informed medical applications. Its online marketplace fosters innovation, connecting suppliers and demanders to streamline collaboration. By integrating AI and machine learning, the project enhances public awareness of healthcare solutions while supporting global competitiveness and innovation in the biomaterials sector.
The BIOMATDB project consolidated insights from previous initiatives to enhance the design of the planned tools – the Biomaterial Database and Marketplace. Additionally, a comprehensive stakeholder survey identified key requirements, use cases, and challenges, shaping the project's strategic direction. An extensive analysis of biomaterials, suppliers, and manufacturers across Europe strengthened collaboration and communication efforts, ensuring effective engagement with industry stakeholders. The integration of findings from the DEBBIE project and other sources enabled the development of best practices to inform future advancements.
Furthermore, the project successfully developed the Biomaterial Database by selecting and harvesting relevant content, primarily from PubMed, and storing it within an ElasticSearch system. The project designed, implemented, and tested key Natural Language Processing (NLP) components, including Named Entity Recognition, Text Classification, and semantic relation extraction, enhancing metadata curation. A pilot integration processed 340k PubMed records, applying NLP techniques to improve data organization and accessibility. The backend system architecture was refined to support automated data processing tools for searching, decision-making, and visualization, further optimizing usability and efficiency.
As a part of Work Package 4 the consortium focused on strengthening the technical infrastructure for the Biomaterial Database and Marketplace, ensuring seamless integration between backend and frontend systems. Major achievements included the development of multilingual web applications, the implementation of an administration panel, and the integration of a biocompatibility label to enhance usability. Advanced NLP and machine learning techniques enriched over 37 million biomaterial records, improving accessibility and data structuring. Continuous collaboration ensured effective frontend development, while a comprehensive online knowledge base was created to support user engagement.
The project demonstrated the Biomaterial Database and Marketplace’s practical application, enhancing usability and accessibility. Iterative validation, user tests, and optimizations refined functionalities, while targeted questionnaires supported testbed deployment, leading to initial live systems. These efforts ensure the tools effectively serve researchers, industry professionals, and stakeholders, fostering collaboration and innovation.
Furthermore, the project successfully developed the Biomaterial Database by selecting and harvesting relevant content, primarily from PubMed, and storing it within an ElasticSearch system. The project designed, implemented, and tested key Natural Language Processing (NLP) components, including Named Entity Recognition, Text Classification, and semantic relation extraction, enhancing metadata curation. A pilot integration processed 340k PubMed records, applying NLP techniques to improve data organization and accessibility. The backend system architecture was refined to support automated data processing tools for searching, decision-making, and visualization, further optimizing usability and efficiency.
As a part of Work Package 4 the consortium focused on strengthening the technical infrastructure for the Biomaterial Database and Marketplace, ensuring seamless integration between backend and frontend systems. Major achievements included the development of multilingual web applications, the implementation of an administration panel, and the integration of a biocompatibility label to enhance usability. Advanced NLP and machine learning techniques enriched over 37 million biomaterial records, improving accessibility and data structuring. Continuous collaboration ensured effective frontend development, while a comprehensive online knowledge base was created to support user engagement.
The project demonstrated the Biomaterial Database and Marketplace’s practical application, enhancing usability and accessibility. Iterative validation, user tests, and optimizations refined functionalities, while targeted questionnaires supported testbed deployment, leading to initial live systems. These efforts ensure the tools effectively serve researchers, industry professionals, and stakeholders, fostering collaboration and innovation.
The BIOMATDB project has advanced beyond the state of the art by transforming biomaterials research through structured data accessibility, automated information extraction, and interactive visualization tools. Its integration of natural language processing techniques enables the conversion of unstructured data into structured knowledge, improving metadata categorization and search functionalities. The project fosters interdisciplinary collaboration, linking external resources to enhance knowledge exchange across material science, biomedical engineering, and clinical research. By establishing the BIOMATDB Biomaterial Database, BIOMATDB accelerates innovation, reduces time-to-market, and supports SMEs in optimizing product development and competitiveness. The biocompatibility assessment tools and Biomaterial Marketplace features drive transparency, regulatory alignment, and market differentiation, ensuring safer material choices and broader adoption. With its extensive stakeholder engagement and expansion across Europe, BIOMATDB strengthens industry growth and facilitates biomaterials commercialization, reinforcing Europe's leadership in medical device innovation and advanced therapies.