Nicole Kleinstreuer Data-verified

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

High Impact

Researcher

Last publication 2025 Last refreshed 2026-04-01

faculty

53 h-index 284 pubs 13,775 cited

Biography and Research Information

OverviewAI-generated summary

Nicole Kleinstreuer's research focuses on the development and application of new approach methodologies (NAMs) in toxicology, particularly as alternatives to traditional animal testing. She investigates computational and <i>in silico</i> methods to predict toxicity and facilitate risk assessment, aiming to improve the efficiency and reliability of toxicological evaluations.

Her work includes developing frameworks for establishing scientific confidence in NAMs and evaluating the quality of data used in these models. Kleinstreuer has published on topics such as large-scale modeling of multispecies toxicity, the integration of <i>in vitro</i> data into risk assessment, and the impact of data quality on artificial intelligence models. She is also involved in evaluating variability in animal toxicity studies to better understand and refine alternative testing strategies.

Kleinstreuer's research network includes collaborations with Kamel Mansouri and Weida Tong at the National Center for Toxicological Research, with whom she has co-authored multiple publications. Her scholarship is characterized by a high citation count (13,775) and a significant number of publications (284), reflected in her h-index of 53 and designation as a highly cited researcher.

Metrics

  • h-index: 53
  • Publications: 284
  • Citations: 13,775

Selected Publications

  • Challenges and opportunities for validation of AI-based new approach methods (2025)
    32 citations DOI OpenAlex
  • The skin allergy risk assessment-integrated chemical environment (SARA-ICE) defined approach to derive points of departure for skin sensitization (2024)
    19 citations DOI OpenAlex
  • A Novel Machine Learning Model and a Web Portal for Predicting the Human Skin Sensitization Effects of Chemical Agents (2024)
    7 citations DOI OpenAlex
  • Democratizing cheminformatics: interpretable chemical grouping using an automated KNIME workflow (2024)
    17 citations DOI OpenAlex
  • Unlocking the Potential of Clustering and Classification Approaches: Navigating Supervised and Unsupervised Chemical Similarity (2024)
    13 citations DOI OpenAlex
  • Integrated Approach for Testing and Assessment for Developmental Neurotoxicity (DNT) to Prioritize Aromatic Organophosphorus Flame Retardants (2024)
    10 citations DOI OpenAlex
  • Differences in the anatomy and physiology of the human and rat respiratory tracts and impact on toxicological assessments (2024)
    27 citations DOI OpenAlex
  • 60 Years of the 3Rs symposium: Lessons learned and the road ahead (2024)
    8 citations DOI OpenAlex
  • Evaluation of in silico model predictions for mammalian acute oral toxicity and regulatory application in pesticide hazard and risk assessment (2024)
    8 citations DOI OpenAlex
  • Use of human predictive patch test (HPPT) data for the classification of skin sensitization hazard and potency (2024)
    14 citations DOI OpenAlex
  • Free and open-source QSAR-ready workflow for automated standardization of chemical structures in support of QSAR modeling (2024)
    43 citations DOI OpenAlex
  • Artificial intelligence (AI)—it’s the end of the tox as we know it (and I feel fine)* (2024)
    81 citations DOI OpenAlex
  • Examining animal testing for risk assessment: A WC-12 workshop report (2024)
    9 citations DOI OpenAlex
  • Computational application of internationally harmonized defined approaches to skin sensitization: DASS App (2024)
    7 citations DOI OpenAlex
  • Report of the Assay Guidance Workshop on 3-Dimensional Tissue Models for Antiviral Drug Development (2023)
    7 citations DOI OpenAlex

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Collaboration Network

351 Collaborators 133 Institutions 19 Countries

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