The development of safe and effective nanomaterials (NMs) is highly important for both industry and regulatory agencies, especially considering their continuously growing economic potential, and their wide range of industrial, consumer, medical, and diagnostic NM applications. The basic methodology for performing risk assessment (RA) for NMs is similar to the philosophy used for conventional chemicals RA, i.e. compare the level of exposure with the hazard assessment. However, exposure and hazard assessments for NMs are more challenging than for conventional chemicals, because of the complex NM structures, which are dynamic as many of their properties are context-dependent (extrinsic), and can be modified or evolve during their life-cycle. In this deliverable (D6.1) we describe a number of computationally oriented tools and methodologies that can be used for exposure modelling, hazard prediction and eventually for RA. Additionally, we present checklists and best practices for the most efficient use of the tools and workflows, as well as optimal combinations of these tools for performing RA for NMs. We report here on the current status of development and integration of existing RA tools into the NanoCommons knowledge infrastructure, and outline the strategy that will be used in the subsequent months of the project for further development, for supporting case studies to demonstrate the utility of the RA tools, and Transnational Access (TA) activities.