DATABASES

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Several toxicity databases are available. They address different endpoints, chemicals, and have different format. Check should be done if the collection of data has been curated.

The DSSTox database gather a series of collections of curated datasets:

 

Below is reported a list of resources containing links to databases:

 

Databases of calculated properties

 

Databases of chemical structures

 

Related FAQ

Are QSAR models expensive, or free to use?

The CAESAR and VEGA platforms have been produced from EC-funded research, and are therefore freely available for use.  The software can be downloaded. Furthermore, predicted values for more than four million chemicals will be made freely available.

The Danish Environmental Protection Agency has created and made available a database with predictions from more than 70 (Q)SAR models on endpoints for physico-chemical properties, fate, eco-toxicity, absorption, metabolism and toxicity.  More than half of all the estimates are for mammalian (human) toxicity endpoints and include commercial data sets from TOPKAT and MULTICASE as well as models developed in-house.  A structure set of about 166.000 discrete organic chemicals, including almost half of the (around) 100,000 EINECS substances, has been batched through the models, and the results are integrated in the database.  (EINECS: European INventory of Existing Commercial chemical Substances.)

The US Environmental Protection Agency made available a series of QSAR models, within the EPISuite and the T.E.S.T. platforms.

The EC funded ANTARES project is evaluating existing models which could be used for REACH, many of which are free to use.  Hundreds of possible models have been identified and listed, which theoretically could be used for tens of REACH endpoints.

The EU Joint Research Centre has promoted the availability of reliable computer-based estimation methods for use in the regulatory assessment of chemicals.  Within the JRC Institute for Health and Consumer Protection (IHCP), the European Chemicals Bureau (ECB) developed a range of freely available software.  One of the aims of the IHCP is to support the implementation of EU chemicals policy (including the safety assessment of industrial chemicals, chemicals in consumer products, pesticides and biocides) through the development, assessment and application of computational (in silico) methods. 

Typically in such QSAR models, the training set used to develop the model, the algorithm, and other aspects of the model are open for scrutiny by the regulator.   However, in commercially available software the full documentation of each model may not be available.  Indeed, the algorithm and the training set used to build the model are often confidential.  Despite this, the use of commercial programs has not been explicitly criticised by regulatory authorities.  In reality, commercial programs have been used in the USA and Europe, because of their ease of use, their availability and because they represent a major source of QSAR models.  We do not foresee restrictions in their use, and in our opinion it would be a pity to renounce these models.  However, it is likely that in the case of two similar models being available, one commercial and one freely available, the user will prefer the second one.  Within REACH, it also seems likely that the regulators will demand more transparency from the commercial models, and/or prefer the use of fully documented models.

How can I access QSAR platforms for our use?

Several platforms of QSAR models exist. The ANTARES project lists hundreds of QSAR models, tens of them are freely available.

Some well known platforms are:

EPISuite  www.epa.gov/oppt/exposure/pubs/episuite.htm

T.E.S.T.  www.epa.gov/nrmrl/std/qsar/qsar.html#TEST

CAESAR  www.caesar-project.eu/

JRC http://ihcp.jrc.ec.europa.eu/our_labs/computational_toxicology

VEGA:  The ORCHESTRA project, with ANTARES, has developed the VEGA platform, which incorporates CAESAR and T.E.S.T. models into a single framework. An advantage of the VEGA platform is the facilitated and supported user-access: supporting information, tutorials and videos are all available on the web site.  It has been developed from the point of view of the user, and of the REACH requirements. Each model produces not only a predicted value, but also many pages of explanation and assessment of its reliability.

What makes a good QSAR model?

According to REACH regulation (Annex XI) an assessment using a QSAR model is valid if:

  1. the model is recognised as scientifically valid;
  2. the substance is included in the applicability domain of the model;
  3. results are adequate for classification and labelling and for risk assessment;
  4. adequate documentation of the methods is provided.’

These four ‘conditions’ are specific to the regulatory context, and address important scientific and practical aspects of the use of in silico models.  It is important to note that the four conditions are not just about the model, but also about the particular chemicals it is used for in an assessment, the particular regulatory function it is used for, and how well the model and its use are documented.  

A QSAR model is built on a set of experimental data for particular chemicals (a ‘training set’) and it is trialled by testing other chemicals for which there is also experimental data available (the ‘test set’).  In this way a QSAR model is designed to evaluate a particular set of chemicals in relation to a particular endpoint.  So while it could be used for other chemicals outside this ‘applicability domain’, the evaluation of those chemicals will have a higher level of uncertainty.  

For this reason, REACH and ECHA do not provide approval for models: each use of QSAR models has to be evaluated on its own merit, on a case-by-case basis.  

The first of the four conditions above is nevertheless about the model itself.  In the implementation of REACH, ECHA and others usefully refer to the five OECD principles for QSAR models.  The OECD stated that ‘to facilitate the consideration of a (Q)SAR model for regulatory purposes, it should be associated with the following information:

  1. a defined endpoint;
  2. an unambiguous algorithm;
  3. a defined domain of applicability;
  4. appropriate measures of goodness-of-fit, robustness and predictivity;
  5. a mechanistic interpretation, if possible.’

These five principles refer to the rigour of the model and the transparency of the information provided by the model developer.  The REACH demand to provide ‘adequate documentation of the models’ and their use, is central to demanding and ensuring the quality of models and the quality of their use, now and in the future.  It is ultimately about enabling the regulator to evaluate the chemical safety assessments independently in the interest of human health and the environment.

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