Development of machine learning models for the prediction of the skin sensitization potential of cosmetic compounds.

Journal: PeerJ

PMID: 39686995

Abstract

BACKGROUND: To enhance the accuracy of allergen detection in cosmetic compounds, we developed a co-culture system that combines HaCaT keratinocytes (transfected with a luciferase plasmid driven by the AKR1C2 promoter) and THP-1 cells for machine learning applications.

Authors

Wu Qiao

Pigeon Manufacturing (Shanghai) Co., Ltd., Shanghai, China.
Tong Xie

Department of Food Science and Technology, Shanghai Institute of Technology, Shanghai 201418, China.
Jing Lu

Department of Nephrology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Tinghan Jia

Pigeon Manufacturing (Shanghai) Co., Ltd., Shanghai, China.

Keywords

Allergens Coculture Techniques Cosmetics Dermatitis, Allergic Contact HaCaT Cells Humans Keratinocytes Machine Learning Skin Support Vector Machine THP-1 Cells

External Resources

View on PubMed Access via DOI PubMed (39686995)

Development of machine learning models for the prediction of the skin sensitization potential of cosmetic compounds.

Abstract

Authors

Keywords

External Resources

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