Through diet we are continuously exposed to a complexity of chemicals including nutrients and contaminants - the dietary exposome - whose impact on chronic inflammation in the context of whole-diet is still poorly understood. The innovative approach of this proposal relies on finding hidden patterns from data available on literature and databases of consumption data, food nutrients composition, or predominant food contaminants to understand without human-in-the-loop processing the profile of prevalent contaminants associated with different dietary patterns. This knowledge will provide essential tools to design optimal experimental procedures for repeated dietary exposome in vitro assays and later to mathematical modelling the complexity of chronic inflammation triggered by dietary-exposome and finally, to validate the predictive model by using a different dietary pattern and contaminant doses to bring new evidence that can refine nutritional guidelines, considering food-chain chemical contaminants exposure and reducing diet related inflammation.