Neurotoxicity occurs when the exposure to natural or manmade toxic substances (neurotoxicants) alters the normal activity of the nervous system. This can eventually disrupt or even kill neurons, key cells that transmit and process signals in the brain and other parts of the nervous system. […]


There is still a lack of complete understanding of the complex pathways and mechanisms leading to central and peripheral drug-induced neurotoxicity. However, these adverse effects are second only to cardiovascular adverse effects in contributing to failure in clinical development, severe adverse drug reactions volunteers or patients, disadvantageous drug labelling, hospitalizations caused by adverse effects of marketed drugs, and withdrawal from sale (Redfern & Valentin, 2017). The poor detection and prediction of neurological adverse effects by preclinical experiments is due to the complexity of both CNS and PNS. Moreover, there is still a lack of in silico models for reliably predicting off-target pharmacology and quantitative structure-neurotoxicity relationships (neurotoxicophores). Furthermore, validated in vitro in vivo systems suitable for medium/high throughput screening for central and peripheral neurotoxicity do not yet exist in a sufficient number. This extends to the lack of comprehensive data warehousing allowing to conveniently derive new hypotheses on adverse outcome pathways and related toxicophores (i.e., quantitative pharmacophore models encoding for adverse effects mediated by interaction of compounds with off-targets). Additionally lacking are reliable integrated systems for BBB penetration prediction allowing estimation of brain exposure by investigational drugs. Finally, integration of knowledge for an understanding of inter-species differences as well as pathway interdependencies is missing.

Therefore, the ambition of NeuroDeRisk is to bundle the scientific expertise of experimental and theoretical scientists and to collaborate with software developers to address the challenge of preclinical prediction of neurotoxicity using a fully integrated approach: By linking unique expertise for building in vitro and in vivo models with in silico prediction tools, we will establish a novel and validated toolbox for preclinical prediction of neurotoxicity in humans.