Artificial Intelligence tools to advance in the research and development of biomaterials

Nature Review Materials has just published the article "Time to kick-start text mining for biomaterials" (O. Hakimi, M. Krallinger, M.P. Ginebra), which outlines the great possibilities that artificial intelligence presents to the advancement of biomaterials design and development.

The multidisciplinary team, consisting of Osnat Hakimi and Maria Pau Ginebra (BBT, UPC) and Martin Krallinger (BSC-CNS), proposes to use data mining text technologies to extract information about biomaterials, which is currently dispersed across scientific articles, patents, FDA reports and congress proceedings.

These methods of advanced data mining, together with deep learning techniques, could reveal associations not previously considered between materials’ attributes and biological responses, and could help with the design and discovery of new biomaterials.

Biomaterials are materials that interact with biological systems, and are highly used in modern medicine and surgery (implants, prostheses, etc.). Their design involves tapping into complex processes, such as the interactions between cells and materials and the degradation of materials in the body.

The rising volume of published results in the field is contrasted by a low degree of sharing and systematization of data. The article explains the specific challenges in the highly multidisciplinary domain of biomaterials, and proposes steps to tackle them and enable the organization and exploitation of accumulated data.

The article has been written in the context of the DEBBIE project, a Marie Skłodowska-Curie action funded by the EU, dedicated to the development of the first biomaterial database using data mining tools.