software for toxicology

Applications: chemical safety and risk assessment

There are a plethora of software tools for in silico computational toxicology.  Some resources are freely available while others are commercial tools. Each has its strengths and weaknesses. We pride ourselves on our knowledge of utilizing the best software relevant to the task.  Among the free resources, we often use the OECD QSAR Toolbox, Vega, Janus, ChemSpiderDanish (Q)SAR Models and Database, ICE and the EPA Computox.

For commercial software, we use ACD/Labs' Percepta for prediction of physicochemical properties as it is known as a world leader in this area. We also use some Percepta ADMET endpoints too. For chemical nomenclature and chemical drawing we use ACD/Name and ACD/ChemSketch


Knime is used for workflows and SIMCA from Umetrics for statistical applications. 


For both general read-across and screening applications for genotoxicity, ChemTunes.ToxGPS from MN-AM is an excellent software package offering some unique facilities. As we are particularly impressed with this package we have undertaken the distributorship of MN-AM's products in UK, Ireland and Italy.


If your organisation is in the UK, Ireland or Italy and want to know more about ChemTunes.ToxGPS®, please contact us.

For a brief overview, see below:


A unique cheminformatics platform to support the safety and risk assessment of chemical substances which provides expert-reviewed toxicity databases as well as a knowledgebase and workflows for MoA-based in silico predictions and read-across for a series of in vivo and in vitro human health and regulatory-relevant toxicity endpoints. Optionally, the RepDose database from Fraunhofer ITEM is available now

Toxicity Database, Knowledgebase and Read-Across


ChemTunes offers an easy-to-use user interface to retrieve relevant information, combining chemistry and toxicity searches tailored to the needs of toxicologists working in the area of safety and risk assessment.

  • Save time retrieving existing toxicological data and information searching a database containing approximately 100,000 chemical compounds, over 32,000 toxicity studies and 70 endpoints, diverse regulatory use types: a single query to interrogate 22 inventories​

  • Build a interactive workflows based on your reasoning and review your work at any time adding new data at any point of your workflow

  • Store your reasoning and all your supporting evidences collected from multiple sources in a single platform​​

  • Bring a consistent and reasoned process to the justification of your hazard assessment combining all the evidences and the related uncertainties with a consistent and reproducible methodology ​

  • Share your work with your colleagues with a link

  • Rapidly produce reports

Key facts


  • Approximately 100,000 chemical compounds

  • Over 32,000 toxicity studies and 70 endpoints

  • Diverse chemical space and regulatory use types, including food-related substances, drugs, cosmetics, industrial chemicals and pesticides


ChemTunes database is now available with an optionally integrated version of the RepDose database from Fraunhofer ITEM.



ToxGPS® provides a reliable toxicity knowledgebase including workflows and predictions for a series of in vivo and in vitro human health and regulatory-relevant endpoints. The predictions are based on mechanistically-informed, probabilistic QSAR models and endpoint-specific structural knowledge (expert rules) which are combined to provide a weight-of-evidence prediction together with an estimate of the associated uncertainty. Nearest neighbors of the query compounds in the training sets are identified and linked to the experimental study data in the ChemTunes databases.

ToxGPS® predictions are also suited for the assessment of genotoxic impurities in drug products under the ICH M7 guideline.


ToxGPS® also features the ToxGPS Read-Across workflow for data gap filling by identifying structural, physicochemical and biological analogs from the ChemTunes databases. The system offers tools to line up diverse evidence sources, either experimental or in silico, and to combine them to obtain an overall outcome with estimated uncertainty. Users can interactively explore how the read-across outcome varies depending on which evidence sources are used and the reliability assigned to each 


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  3. Yang C, et al. Computational Toxicology Approaches at the US Food and Drug Administration. ATLA 2009, 37, 523-531.

  4. Rathman JF, et al. Uncertainty Estimation and Quantitative Combination-of-Evidence using Dempster-Shafer Theory. Comp. Tox. 2018, 6, 16-31.