Webinar recording: Computational Toxicology

If you missed Gerhard’s webinar on Computational Toxicology, where he also talked about our products ToxPHACTS and Transporter Models, we have good news for you! The webinar was recorded and you can watch it here.

Computational Toxicology – from models to workflows

Development of a new drug currently takes 10 – 12 years with costs of around 2 billion Euro. Main reasons for failures comprise lack of efficacy and unforeseen toxicity. In this Webinar, Gerhard Ecker outlines computational approaches to minimize the risk of failures due to toxicity. These comprise classical machine learning models to predict certain toxicity endpoints such as cholestasis, as well as deep learning approaches to overcome insufficient size and imbalancy of toxicity datasets. Integration of structure-based methods for prediction of molecular initiating events with machine learning and pharmacophore modeling is outlined for the use case of mitochondrial toxicity. Leveraging complex data analysis pursued with KNIME workflows allows to create compound-pathway interaction fingerprints and link them to hepatotoxicity and cardiotoxicity. Finally, ToxPHACTS, a data driven tool for toxicological read across is presented.