The great thirst for data in modern biomedical research is seldom followed by the formulation of models that can explain complex phenotypes by making thorough use of all the information collected. In NANOSOLUTIONS, all the data produced by the partners, including the characterisation of engineered nanomaterials (ENM) and the study of their effect on cell and animal models by a number of in vitro and in vivo experiments, will be systematically collected, organised and analysed in WP11.
The main goal of WP11 is the development of a computational model for predicting the safety of the nanomaterials, which we call the “ENM safety classifier”, by integrating all the data layers produced within the consortium.
Outcomes of the workpackage
The activities of WP11 rotated around three tasks:
- Data management;
- Development of the ENM Safety Classifier;
- Systems biology analysis of ENM mode of action (MoA).
Data management was mainly carried out by the Institute of Occupational Medicine, Edinburgh (IOM), BioByte, and University of Helsinki (UH). First, the data repository was established as a central data warehouse harbouring any protocols, data, and results originated from the activities of the whole consortium. Second, templates for storing the data were established and disseminated to the other partners. This ensured standardization and compatibility with other repositories outside the project. Attention was given to homogenize the data templates with those proposed by the FP7 project eNanoMapper and special agreement was established to ensure data and protocols transfers.
Development of the ENM Safety Classifier was mainly carried out by UH. Novel algorithms and computational methods were developed. Particularly, a novel multi-view adaptive genetic algorithm (MAGA) was established as the main method for carrying out the task of feature selection and evaluation of the predictive models. Rich multi-view data retrieved from multiple partners (mainly in WP3, 6, 7, and 10) were preprocessed and further analysed in search of the minimal set of features able to predict the toxicity levels of the 31 ENM, tested both in vitro and in vivo in multiple exposure scenarios. Several models were established being able to predict cytotoxicity, genotoxicity and overall toxicity potential of ENM with high accuracy (> 90%). In collaboration with WP12, a set of computational validations were carried out on data retrieved from the FP7 project MARINA as well as on collaborative data from Health Canada.
Systems biology analysis of ENM Mode of Action (MoA) was mainly carried out by UH, UniSa, and TIGEM. Several computational methods were established to carry out systematic analysis of ENM MoA, as measured with omics technologies. Attention was given to the possibility to contextualize ENM MoA with respect of the MoA of drug treatments, chemical exposure and human disease. Further detailed analysis has been planned in future collaborative publications with several NANOSOLUTIONS partners (Karolinska Institutet, University of Plymouth, TNO).