Kristin Ashby

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NCTR

Also affiliated: United States Food and Drug Administration (2018–2023)

5 h-index 8 pubs 163 cited

Research Areas

Biomedical Subjects

Links

ORCID

OverviewAI-generated summary

Kristin Ashby's research focuses on understanding the factors that contribute to drug-induced liver injury (DILI). Her work investigates how drug properties and host characteristics influence the biochemical presentation and recovery timeline of DILI. Ashby has explored the use of machine learning approaches to predict DILI risk, including identifying the interaction of single-nucleotide polymorphisms as a potential risk factor for chronic DILI. Her publications also examine the role of drug transporters and metabolizing enzymes in DILI. Collaborating with colleagues at the National Center for Toxicological Research, Ashby has contributed to computational modeling efforts aimed at predicting hepatotoxicity from drugs and chemicals. Her scholarship includes 9 publications with 180 citations and an h-index of 6.

Metrics

h-index: 5
Publications: 8
Citations: 163

Selected Publications

Computational Modeling for the Prediction of Hepatotoxicity Caused by Drugs and Chemicals (2023)

Computational methods in engineering & the sciences 1 citation DOI OpenAlex
Machine Learning to Identify Interaction of Single-Nucleotide Polymorphisms as a Risk Factor for Chronic Drug-Induced Liver Injury (2021)

International Journal of Environmental Research and Public Health 8 citations DOI OpenAlex
Transporter, Drug Metabolism, and Drug‐Induced Liver Injury in Marketed Drugs (2021)

DOI OpenAlex
Elevated bilirubin, alkaline phosphatase at onset, and drug metabolism are associated with prolonged recovery from DILI (2021)

Journal of Hepatology 45 citations DOI OpenAlex
Drug properties and host factors contribute to biochemical presentation of drug-induced liver injury: a prediction model from a machine learning approach (2021)

Archives of Toxicology 6 citations DOI OpenAlex
Predicting the Risks of Drug-Induced Liver Injury in Humans Utilizing Computational Modeling (2019)

Challenges and advances in computational chemistry and physics DOI OpenAlex
The Development of a Database for Herbal and Dietary Supplement Induced Liver Toxicity (2018)

International Journal of Molecular Sciences 34 citations DOI OpenAlex
Review article: therapeutic bile acids and the risks for hepatotoxicity (2018)

Alimentary Pharmacology & Therapeutics 68 citations DOI OpenAlex