(Q)SAR   Quantitative Structure Activity Relationships ((Q)SARs) are the relationships between the structural properties of chemical substances and another property. This other property can be a physico-chemical property or a biological activity, including the ability to cause toxic effects.  The models can reduce the number of animal tests necessary in the assessment of chemical substances, increase the information for a given substance (including metabolites and degradation products), and save companies and authorities time and money. In the EU legislation, REACH, it is expected that (Q)SARs will be used as a direct replacement for test data as relevant and reliable models become increasingly available, and as experience in their use becomes more widespread. Research and advise in regulatory use In order to increase the level of information about the chemicals in use in the EU with no or insufficient experimental test data, the National Food Institute develops, buys and validates (Q)SAR models. We focus on so-called "global" models with sub-models for different chemical classes that have large chemical applicability domains.  A (Q)SAR prediction database containing predictions for more than 180,000 organic chemicals from more than 70 (Q)SAR models has been established. The predicted endpoints cover physico-chemical properties, fate, eco-toxicity, absorption, metabolism and toxicity. More than half of all the estimates are for mammalian (human) in vitro and in vivo toxicity endpoints. The database is constantly growing as new models are obtained or developed in-house.  We advise on the use and documentation of (Q)SARs in regulatory contexts and other contexts. This can be in connection with the upcoming new chemicals legislation REACH and the work in OECD to increase regulatory use and acceptance of (Q)SARs.  Collaborations Danish Environmental Protection Agency Bourgas University Laboratory of Mathematical Chemistry, Bulgaria BioDetection Systems BV, The Netherlands RIVM, The Netherlands TNO, The Netherlands P&G, Belgium Fraunhofer Institute, Germany Contact for further information Special consultant Jay Niemelä ­­­­­­­­­­­­­Chief adviser Eva B. Wedebye