Increasing societal concerns for animal welfare and current legislation constraints have made the industry enter a new phasein its innovation and R&D processes. For acute and chronic toxicity testing, which consumes a large number of laboratoryanimals, no alternative is available, one of the reason being the complexity of the biological processes involved. As such, manyresearch programs have been launched with the aim of developing integrative approaches that would accurately predict suchan endpoint. The purpose of the study presented herein was to develop an integrated testing strategy on the basis of the datapreviously generated with the Ctox panelplatform, developed to assess metabolism-mediated toxicity. The set used consisted of 63 proprietary chemicals, categorized®, a multiparameter, cell-based in vitro system and the Solidus® DataChip/MetaChipas Toxic (25 compounds) and Non Toxic (38 compounds) on the basis of an arbitrarily defi ned LD50 threshold of 500 mg/kgin rat following an oral administration. A statistical analysis of the data led to the construction of several integrative models.The most predictive model (discriminating analysis) required the consideration of a total of 22 parameters. On the basis ofa LD50 threshold of 500 mg/kg, the sensitivity and specifi city of the prediction was 92% and 87%, respectively. The next steps willconsist of challenging the model with a set of diverse chemical classes. At last, it is noteworthy that the number of parametersconsidered for the model correlates well with the complexity of the endpoint mentioned above.