Integrated approaches to testing and assessment (IATA) provide a framework for combining information from different sources (experimental, in silico) for hazard characterisation of chemicals, including nanomaterials (NM), based on a weight of evidence approach. Experimentally acquiring the exposure, hazard and characterisation data for NMs necessary to perform risk assessment is time-consuming and costly, thus driving demand for in silico models to facilitate read-across from data rich NMs to data poor ones, or to predict exposure or hazard. In this work, we present three integrated computational approaches which can be used to generate data relevant to human health risk assessment, namely the multi-box aerosol model for prediction of indoor air concentrations of NMs, the lung exposure model to determine the lung burden of NMs following acute exposures and a physiologically based pharmacokinetic (PBPK) model to determine the biodistribution of the NMs to other organs over longer timescales following inhalation. The lung exposure application is based on empirical deposition equations for calculating the deposited mass in the human respiratory system. The PBPK model extends the lung exposure model by introducing clearance terms and translocation of the NMs to the systemic circulation after passage through the air-blood barrier in the alveoli. Several exposure scenarios with varying conditions are introduced in order to compare the models in relation to the accumulated mass of NMs in the alveolar, tracheobronchial and head airways regions of the respiratory system, thus exploring their capabilities and weaknesses, and potential contribution to a NM-specific IATA for occupational exposure.