Optimising Resources: The Importance of Data-Driven Approaches

Welcome to the latest blog article.

Today, we take a closer look at the world of computational tools within the BIO-SUSHY project. From data management to predictive modelling, this set of computational tools allows our project to innovate and shape the future of a PFAS-free coating industry.

Data Mining

One of the main advantages of computational tools is the minimisation of new experimental data needed, reducing costs, and avoiding the ethical concerns relating to the in vivo tests.

In this direction, one of the applications of the computational tools inside the BIO-SUSHY project is the use of text scraping and data mining tools to generate an internal database with information on all the compounds involved -and candidates to be involved- in the project. This information is gathered from the safety data sheets (SDS) of the compounds and publicly available databases.

QSAR Model Generation and Prediction: Bridging Data Gaps

Once the database is built using existing experimental information, the data gaps will be filled using Quantitative Structure-Activity Relationship (QSAR) predictions.

QSAR models are mathematical models capable of predicting different properties—such as physicochemical and (eco)toxicological properties—of a compound from its chemical structure.

In the BIO-SUSHY project, QSAR models generated by our partner ProtoQSAR and from other free-available tools are used.

Using information from experimental sources and predictive models, we are able to obtain a comprehensive database with all the compounds used—or willing to be used—in the development of the Bio-SUSHY project, essential for the Safe and Sustainable by Design (SSbD) evaluation.

This data-based approach enables our coating-developer partners for the textile, paper, and glass sectors to make informed decisions regarding coating formulations, safety assessments, and life cycle analyses, driving the formulation of coatings that meet stringent safety and sustainability standards.

Physics-based Modelling: Shaping the Future of Coatings

In addition, physics-based approaches are employed to gain deeper insights into coating performance and behaviour.

Through physics-based modelling and simulation, researchers can characterize critical aspects of coating processes, morphology, and physical properties.

For instance, by simulating phenomena such as annealing, adhesion, and surface properties, these models provide valuable insights into the repellent properties and leaching mechanisms of reference coatings. This is of fundamental importance as we strive to obtain bio-based PFAS-free coatings with the same hydro- and oil-repellent properties.

Moreover, by consolidating and storing information within the BIO-SUSHY knowledge exchange infrastructure, researchers can access comprehensive datasets for downstream analysis, safety assessments, and decision-making processes.

Data Management: A Foundation for Collaboration and Knowledge Exchange

In the digital age, effective data management is paramount to fostering collaboration and accelerating research progress, especially in complex multi-partner projects like BIO-SUSHY, combining information from experimental investigations as well as the computational approaches described above.

Within BIO-SUSHY, a comprehensive data infrastructure (Figure 1) has been established, facilitating the storage, harmonization, and sharing of research outputs and ensuring that information is Findable, Accessible, Interoperable, and Re-usable (FAIR); first within the project and then by other researchers, policy makers and the general public.