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Computational 'eco-toxicity' assessment of pharmaceutical and cosmetics materials, an approach towards a green and sustainable environment

Project description

Smart design of green chemicals

Industrial chemicals find their way into aquatic environments during production, use, and disposal of end-products. Even so-called 'green' chemicals can harm living organisms if microscopic particles accumulate in natural environments. For the safe use of existing chemicals and the smart design of future ones, a clear understanding of the structural characteristics responsible for eco-toxicity is needed. EU-funded scientists are using well-known tools such as quantitative structure–activity relationship (QSAR) models supplemented with others developed within the scope of the project for this purpose. This will help industries be competitive while fostering sustainable environments for aquatic life.


The main goal of the proposed research project is the computational evaluation of eco-toxicity (diverse endpoints) of various chemicals that are vastly utilized and produced by the pharmaceutical and cosmetic industries, such as green solvents (including future ones, i.e. ionic liquids and deep eutectic solvents) and active pharmaceutical ingredients (API).

We will be majorly focusing on toxicity in aquatic environment, where the toxicity data will cover four trophic levels of aquatic organisms, i.e. fish (vertebrates), invertebrates such as daphnids, algae (aquatic plants), and microorganisms. The toxicity related properties that will be studied include acute and chronic toxicity, biodegradation and bioaccumulation.

The research methodology to perform toxicity assessment and for understanding the structural features responsible for the eco-toxicity, will involve diverse Artificial Intelligence (AI) and chemoinformatics techniques like Quantitative Structure-Activity Relationship (QSAR), interspecies QSAR (QAAR), toxicophore mapping, virtual screening, similarity search, clustering techniques, multimedia mass-balance (MM) modeling (to understand the distribution profile of chemicals in different environmental compartments), matched molecular pair (MMPs) analysis etc.

The knowledge gained from the study will help in classifying existing chemicals into toxic and non-toxic groups and will also help in designing novel analogues of selected chemical that will show better desirable physicochemical properties with less or no eco-toxicity. This project will also include development of AI software tools and scheming KNIME workflows for various computational tasks.


Net EU contribution
€ 172 932,48
C salvador ferrandis luna 45 pta 23
46018 Valencia

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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Este Comunitat Valenciana Valencia/València
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Other funding
€ 0,00