Molecular Mechanisms of Specific Target Organ Toxicity
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Toxicology".
Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 30873
Special Issue Editor
Interests: in vitro toxicology; experimental hepatology
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The field of toxicology is moving away from classical strategies that use animals to generate apical toxic outcomes assumed to be extrapolatable to humans toward more predictive human-based approaches devoid of animals. One of the historical milestones in this regard was the publication of the report “Toxicity testing in the 21st century: a vision and a strategy” by the US National Academy of Sciences in 2007, which fully embraces these novel approaches and that highlighted the importance of mechanistic toxicology. In this respect, human-based in vitro (cell culture) and in silico (computational) methodologies are strongly preferred over complex animal models to elucidate and predict mechanisms of toxicological action. This research field is still gaining momentum and has now evolved to become a multidisciplinary science feeding from various areas.
This Special Issue of the International Journal of Molecular Sciences focuses on the use of in vitro and in silico tools for the study and prediction of specific target organ toxicity at the mechanistic level. Submission of manuscripts, both original research papers and review papers, related to basic and applied animal-free and human-based toxicology involving a broad chemical space, such as pharmaceuticals, food ingredients, cosmetics, biocides, and industrial chemicals, is encouraged. The target audience includes undergraduates to full professionals in academic, industrial, and regulatory settings.
Prof. Dr. Mathieu Vinken
Guest Editor
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Keywords
- toxicity
- mechanism
- adverse outcome pathway
- cell and tissue culture
- computational modeling
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