Studying adverse effects of chemical pressure on aquatic ecosystems needs a comprehensive knowledge of bioaccumulation mechanisms of pollutants in biota to predict internal concentrations, especially for Persistent Organic Pollutants (POPs). However, the large variability of responses in measured POP concentrations requires explicit consideration of both individual variability and environmental influences. Dynamic Energy Budget (DEB) theory provides a rigorous and generic conceptual framework for tackling these questions in a relevant mechanistic way. In the present study, parameterisation and calibration of previous DEB models for Solea solea were revisited in order to accurately represent the full life cycle with an original emphasis on larval stage, metamorphosis, reproduction rules and sexual differences. We first improved calibration thanks to the use of the estimation procedure developed by the DEB network coupled with a broad compilation of data from literature. Then, we validated this set of parameter estimates on independent datasets of i) individual monitoring of larval growth in controlled food conditions from a novel experiment, and ii) juvenile and adult growth, and female fecundity, from a natural population. Finally, we combined the DEB model developed in the present paper with we used a simple toxicokinetic (TK) model from literature. This TK model was also combined to a previous DEB model and was used to reproduce the mean trajectories of a growth and contamination dataset. We applied the same TK model with our DEB model considering inter-individual variability in food availability. This application highlighted the need to accurately consider inter-individual variability in ingestion to correctly estimate growth and contamination variability. The present work is the first step in the development of a mechanistic TK model that will be used in a companion paper for investigations of juvenile sole sensitivity to warming, nursery quality and prey contamination, in highly fluctuating estuarine environments.< Réduire