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OECD QSAR Application Toolbox를 이용한 화학물질의 건강유해성 및 생태독성 예측
김정곤,서정관,김탁수,김현경,박상희,김필제,Kim, Jungkon,Seo, Jung-Kwan,Kim, Taksoo,Kim, Hyun-Kyung,Park, Sanghee,Kim, Pil-Je 한국환경보건학회 2013 한국환경보건학회지 Vol.39 No.2
Objectives: The OECD QSAR Application Toolbox was developed by the Organisation for Economic Cooperation and Development (OECD) to facilitate the practical use of QSAR approaches in regulatory contexts as well as to reduce the need for additional animal testing. In this study, human health and the ecotoxicity of chemicals were predicted by applying the OECD QSAR Application Toolbox and the results were compared with experimental data in order to evaluate the applicability of this program. Methods: Read-across, trend analysis, and QSAR of OECD QSAR Application Toolbox were used for the prediction of toxicity. Results: The toxicity prediction was conducted on 6,354 chemicals for which toxicity data have been produced on the six endpoints of skin sensitization, skin irritation, eye irritation, mutagenicity, and acute toxicities of fish and Daphnia. From the total of 6,354, we obtained prediction results for 1,621 chemicals (25.5%). Conclusions: The predicted properties of mutagenicity, skin sensitization, and acute aquatic toxicities were reasonably good when compared with experimental data, but other endpoints were not due to the limitation of applicable chemical groups.
TOPKAT®, Derek®, OECD toolbox를 활용한 화학물질 독성 예측 연구
이진욱,박선영,장석원,이상규,문상아,김현지,김필제,유승도,성창호 한국환경보건학회 2019 한국환경보건학회지 Vol.45 No.5
Objectives: Quantitative structure-activity relationship (QSAR) is one of the effective alternatives to animal testing, but its credibility in terms of toxicity prediction has been questionable. Thus, this work aims to evaluate its predictive capacity and find ways of improving its credibility. Methods: Using TOPKAT®, OECD toolbox, and Derek®, all of which have been applied world-wide in the research, industrial, and regulatory fields, an analysis of prediction credibility markers including accuracy (A), sensitivity (S), specificity (SP), false negative (FN), and false positive (FP) was conducted. Results: The multi-application of QSARs elevated the precision credibility relative to individual applications of QSARs. Moreover, we found that the type of chemical structure affects the credibility of markers significantly. Conclusions: The credibility of individual QSAR is insufficient for both the prediction of chemical toxicity and regulation of hazardous chemicals. Thus, to increase the credibility, multi-QSAR application, and compensation of the prediction deviation by chemical structure are required.
TOPKATⓇ, DerekⓇ, OECD toolbox를 활용한 화학물질 독성 예측 연구
이진욱(Jin Wuk Lee),박선영(Seonyeong Park),장석원(Seok-Won Jang),이상규(Sanggyu Lee),문상아(Sanga Moon),김현지(Hyunji Kim),김필제(Pilje Kim),유승도(Seung Do Yu),성창호(Chang Ho Seong) 한국환경보건학회 2019 한국환경보건학회지 Vol.45 No.5
Objectives: Quantitative structure-activity relationship (QSAR) is one of the effective alternatives to animal testing, but its credibility in terms of toxicity prediction has been questionable. Thus, this work aims to evaluate its predictive capacity and find ways of improving its credibility. Methods: Using TOPKATⓇ , OECD toolbox, and DerekⓇ , all of which have been applied world-wide in the research, industrial, and regulatory fields, an analysis of prediction credibility markers including accuracy (A), sensitivity (S), specificity (SP), false negative (FN), and false positive (FP) was conducted. Results: The multi-application of QSARs elevated the precision credibility relative to individual applications of QSARs. Moreover, we found that the type of chemical structure affects the credibility of markers significantly. Conclusions: The credibility of individual QSAR is insufficient for both the prediction of chemical toxicity and regulation of hazardous chemicals. Thus, to increase the credibility, multi-QSAR application, and compensation of the prediction deviation by chemical structure are required.
TOPKAT<sup>®</sup>, Derek<sup>®</sup>, OECD toolbox를 활용한 화학물질 독성 예측 연구
이진욱,박선영,장석원,이상규,문상아,김현지,김필제,유승도,성창호,Lee, Jin Wuk,Park, Seonyeong,Jang, Seok-Won,Lee, Sanggyu,Moon, Sanga,Kim, Hyunji,Kim, Pilje,Yu, Seung Do,Seong, Chang Ho 한국환경보건학회 2019 한국환경보건학회지 Vol.45 No.5
Objectives: Quantitative structure-activity relationship (QSAR) is one of the effective alternatives to animal testing, but its credibility in terms of toxicity prediction has been questionable. Thus, this work aims to evaluate its predictive capacity and find ways of improving its credibility. Methods: Using $TOPKAT^{(R)}$, OECD toolbox, and $Derek^{(R)}$, all of which have been applied world-wide in the research, industrial, and regulatory fields, an analysis of prediction credibility markers including accuracy (A), sensitivity (S), specificity (SP), false negative (FN), and false positive (FP) was conducted. Results: The multi-application of QSARs elevated the precision credibility relative to individual applications of QSARs. Moreover, we found that the type of chemical structure affects the credibility of markers significantly. Conclusions: The credibility of individual QSAR is insufficient for both the prediction of chemical toxicity and regulation of hazardous chemicals. Thus, to increase the credibility, multi-QSAR application, and compensation of the prediction deviation by chemical structure are required.
정량적인 구조-활성상관(QSAR) 기법을 활용한 in silico 위해평가
이태환,김민경,김희중,이얼,이용문 대한약학회 2019 약학회지 Vol.63 No.5
The hazard testing on each chemicals which are continuously synthesized is too much task to meet the rapidindustrial development. Currently, national administrative office also prohibited the distribution and sale of cosmeticproducts under animal testing. Therefore, as an alternative hazard evaluation method, a variety of in silico programs havebeen developed and applied to predict the chemical hazard assessment. The OECD Toolbox program which database isdonated from many chemical companies and regulatory authorities of OECD nations is an excellent free software withcomparable hazard prediction ability. In this study, we exhibits the predictive evaluation on the skin sensitization for 100cosmetic ingredients domestically available. In addition, the precise assessment steps were explained as supplementarymaterial. The predicted reliability of data for the skin sensitization is 88.2% when using the data in the highest categoryof similarity (>60%). When this toolbox finds and uses more than 5 similarities for read-across, the predicted reliabilitycomes to 90%. Conclusively, the predictive ability of OECD Toolbox 4.2 were successfully applied on the hazardassessment on skin sensitization of 100 cosmetic chemicals.