Concept

Overall approach and methodology for the chemical mixture toxicity evaluation in ALTERNATIVE

ALTERNATIVE will develop a multidisciplinary approach through the combined efforts of biologists, chemists, bioinformaticians, omics experts, engineers and regulatory bodies. The project idea arises from the scientific outcomes of projects associated to the development of cardiac tissue models (including the aged one) and ML in silico systems and aims at the application of the emerging information in the toxicological profiling of chemical mixtures, supporting the safety assessment. ALTERNATIVE aims to address these targets by developing an in vitro system based on mimicking 3D young and aged cardiac tissue-specific structures integrated into the sensorised bioreactor to replicate the microphysiological cell environment. The cellular systems will be analysed through the support of classic biological markers of toxicity and omics approaches, like transcriptomics, proteomics and metabolomics. ML in silico models will analyse the heterogeneous data collected, integrated with information collected by already established databases. The ML in silico tool will provide a small set of potential biological toxicity markers to be validated in the validation phase and a new approach for the evaluation of chemical mixtures assessment.

Through the support of epidemiology-toxicology and QSAR models, an in-depth analysis of cardiotoxic effects of several pharmaceutical and chemical compounds will be performed and provide the basis for the in vitro experimentation. Three-dimensional (3D) in vitro bioengineered human young and aged cardiac tissues will be developed. They will then be combined into a sensorised bioreactor where the 3D mimetic cell culture environment supported by a sensorised microfluidic system will help reveal the complexity of chemical interactions in terms of cardiac molecular pathways involved in chemical mixtures toxicity. Omics approaches (WP5) will help create a map of the effects of the chemicals on cell biology. Through the integration of ML in silico risk assessment system hosted on the cloud, data analysis will generate a set of TK-TD models and AOPs that together will describe the effects and the weight of each compound in the mixtures toxic effects in the ALTERNATIVE in vitro system.