采用贝叶斯网络法评价化妆品原料眼刺激性

doi:10.13218/j.cnki.csdc.2017.10.007

Abstract

Abstract: This study applied a Bayesian Network (BN) to predict eye irritation of cosmetic ingredients.It bases on the Integrated Testing Strategy (ITS) and combines evidence from different information sources such as QSAR model predictions,in vitro alternative method results and in vivo test results in order to increase the reliability of a conclusion on the eye irritation of cosmetic ingredients.The parameters of BN were calculated from an extended data set of 104 cosmetic ingredients.A detailed validation analysis and a case study of five cosmetic ingredients were carried out to demonstrate the utility of the BN for practical application.These results suggest that BN displays good predictive capacity in eye irritation of cosmetic ingredients and is of well application value as a prediction model in cosmetic safety evaluation.

Key words: cosmetic ingredient, eye irritation, alternative methods, Bayesian Network, Integrated Testing Strategy

CLC Number:

TQ658

CHEN Li, CHEN Wei, JI Wen-jun, ZHU Nai-jun, FANG Yun. A safety evaluation method of eye irritation evaluation of cosmetic ingredients based on Bayesian Network[J].China Surfactant Detergent & Cosmetics, 2017, 47(10): 568-572.

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A safety evaluation method of eye irritation evaluation of cosmetic ingredients based on Bayesian Network

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