Tag: Department of Pharmaceutical Sciences

In recent years, machine learning models have become increasingly popular for risk assessment of chemical compounds. However, they are often considered ‘black boxes’ due to their lack of transparency, leading to scepticism among toxicologists and regulatory authorities. To increase confidence in these models, researchers at the University of Vienna proposed to carefully identify the areas of chemical space where these models are weak. They developed an innovative software tool (‘MolCompass’) for this purpose and the results of this research approach have just been published in the prestigious Journal of Cheminformatics.