Skylar Connor

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

ORISE Post Doctoral Fellow

NCTR primary UAMS

Also affiliated: United States Food and Drug Administration (2021–2025)

5 h-index 8 pubs 87 cited

Research Areas

Biomedical Subjects

Links

ORCID

OverviewAI-generated summary

Skylar Connor's research focuses on the application of artificial intelligence (AI) in regulatory science, particularly for evaluating drug safety and toxicity. Connor has investigated the adaptability of AI for drug-induced liver injury (DILI) assessment and developed resources to facilitate AI-driven toxicity studies. This includes work on generating lists of drugs associated with renal injury to support new approach methodologies for nephrotoxicity evaluation and creating a database (DILIrank 2.0) for drug-induced liver injury risk based on FDA labeling and literature reviews. Connor also explores the readiness of AI tools like ChatGPT for specific research applications in organ-specific drug toxicity. Their work emphasizes the need for best practices and reproducible science to advance AI in real-world applications, with a specific interest in drug labeling and its role in AI-based extraction of safety information. Connor's scholarship includes 8 publications and has garnered 76 citations, with an h-index of 5. They have collaborated with Ting Li, Weida Tong, Leihong Wu, and Minjun Chen at the National Center for Toxicological Research.

Metrics

h-index: 5
Publications: 8
Citations: 87

Positions

ORISE Post Doctoral Fellow 2020–present

National Center for Toxicological Research Division of Bioinformatics and Biostatistics ORCID

Selected Publications

DILIrank 2.0: An updated and expanded database for drug-induced liver injury risk based on FDA labeling and a literature review (2025)

Drug Discovery Today 5 citations DOI OpenAlex
Is ChatGPT Ready for Public Use in Organ-Specific Drug Toxicity Research? (2025)

Drug Discovery Today 3 citations DOI OpenAlex
Drug-induced kidney injury: challenges and opportunities (2024)

Toxicology Research 20 citations DOI OpenAlex
Generation of a drug-induced renal injury list to facilitate the development of new approach methodologies for nephrotoxicity (2024)

Drug Discovery Today 21 citations DOI OpenAlex
Adaptability of AI for safety evaluation in regulatory science: A case study of drug-induced liver injury (2022)

Frontiers in Artificial Intelligence 17 citations DOI OpenAlex
Best practice and reproducible science are required to advance artificial intelligence in real-world applications (2022)

Briefings in Bioinformatics 5 citations DOI OpenAlex
DICE: A Drug Indication Classification and Encyclopedia for AI-Based Indication Extraction (2021)

Frontiers in Artificial Intelligence 10 citations DOI OpenAlex
Three Complete Genome Sequences of Genotype G Mumps Virus from the 2016 Outbreak in Arkansas, USA (2017)

Genome Announcements 4 citations DOI OpenAlex