Biography and Research Information
OverviewAI-generated summary
Kamel Mansouri investigates the application of computational chemistry and machine learning techniques to predict chemical toxicity. His research focuses on developing and evaluating computational models, particularly Quantitative Structure-Activity Relationships (QSAR), to assess the potential hazards of chemical substances. Mansouri is involved in the creation of software suites, such as CATMoS (Collaborative Acute Toxicity Modeling Suite), designed to streamline and enhance toxicity predictions.
His work often involves analyzing existing toxicity data, such as variability in rat acute oral systemic toxicity studies, and exploring new approach methodologies (NAMs) to support chemical evaluations. Mansouri also contributes to the development of workflows for standardizing chemical structures to improve the reliability of QSAR modeling. Furthermore, his research extends to pharmacokinetic modeling and in vitro to in vivo extrapolation for various toxicity endpoints, including developmental toxicity.
Mansouri holds a significant publication record, with 111 total publications and over 6,500 citations, reflecting his designation as a highly cited researcher. He has collaborated with Nicole Kleinstreuer on multiple publications within the National Center for Toxicological Research.
Metrics
- h-index: 31
- Publications: 111
- Citations: 6,589
Selected Publications
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Advancing Human and Environmental Safety Science Using <i>In Silico</i> Methods (2025)
Collaboration Network
Top Collaborators
- Advancing Human and Environmental Safety Science Using <i>In Silico</i> Methods
- Advancing Human and Environmental Safety Science Using <i>In Silico</i> Methods
- Advancing Human and Environmental Safety Science Using <i>In Silico</i> Methods
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