Future Toxicology: Better predicting Toxicant-induced cell fate.

Projektbeschreibung

Verbesserte Vorhersage der chemischen Toxizität

Die moderne Toxikologie wendet sich immer mehr rechnergestützten Ansätzen zu, bei denen die Vorhersage der Toxizität auf Datensätzen über chemische Strukturen und toxikologische Auswirkungen beruht. Doch noch verstehen wir nicht vollständig, wie sich Chemikalien auf Zellen auswirken, was die Effektivität solcher Ansätze beeinträchtigt. Im Mittelpunkt des EU-finanzierten Projekts TOXIFATE steht die Entwicklung neuer Assays zur Ermittlung chemisch-induzierter Veränderungen von Zellen. Dabei konzentrieren sich die Forschenden auf die Myotoxizität, eine schwerwiegende Toxizität, die sich durch die Schädigung der Skelettmuskulatur auszeichnet. Forschende werden transkriptomische Daten erzeugen, welche Reaktionen auf Zellstress und Zelltod beschreiben, und mithilfe dieser Daten neuartige rechnergestützte Ansätze für eine verbesserte Vorhersage der Toxizität entwickeln.

Ziel

TOXIFATE will help change the paradigm of chemical safety assessment and give the next generation of toxicologists the fundamental knowledge and experimental skills that are required to bring about this change. The safe use of chemicals is essential for global prosperity and human health and this is entirely dependent upon robust toxicology. For practical, scientific and ethical reasons, modern toxicology is moving to computational approaches in which large datasets describing chemical structures and toxicological outcomes are used to predict toxicity. The promise of this approach was recently demonstrated when computational approaches for the first-time outperformed animal testing in predicting human toxicity. Nonetheless, our ability to predict toxicity is poor because our understanding of how chemicals affect cells is still rudimentary. TOXIFATE will provide intersectoral training to 2 researchers who will build new assays to detect toxicant-induced changes in cells. Multi-disciplinary training will generate unique high-content and transcriptomic data describing cell stress and cell death responses. This multidimensional dataset will be used to develop novel computational approaches to improve toxicity prediction. TOXIFATE will focus on chemical-induced myotoxicity, a severe and sometimes life-threatening toxicity that is characterized by skeletal muscle breakdown. Although at least 200 drugs and chemicals cause myotoxicity, it is relatively under-investigated and what is learnt here to improve prediction of myotoxicity will also be used to improve prediction of other types of toxicity. TOXIFATE researchers will bridge the gap between state-of-the-art science and chemical hazard and risk assessment and be equipped for career paths in the emerging computational toxicology sectors. TOXIFATE will also aid the EU and the global community by quickly, ethically and economically addressing the societal challenge of better identifying chemical hazards to human health.