Prediction of Human Health and Ecotoxicity of Chemical Substances Using the OECD QSAR Application Toolbox

Abstract

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.

In vivo micronucleus test of 4-butylaniline and N-butylaniline to classify a chemical's mutagenicity according to the globally harmonized system of classification and labelling of chemicals (GHS)

“…These substances are listed in both the TSCA (Toxic Substances Control Act) chemical substance inventory of the US EPA (United States Environmental Protection Agency) and the Annex III inventory of ECHA (European Chemicals Agency). Computer-aided (in silico) approaches were performed using QSAR Toolbox version 4.2, which is available on the OECD website (http://www.qsartoolbox.org/) [3,4]. 4-Butylaniline tested positive for prediction of gene mutation and carcinogenicity in read-across analyses.…”

Applicability of QSAR Models for Acute Aquatic Toxicity under the Act on Registration, Evaluation, etc. of Chemicals in the Republic of Korea

“…[3][4][5] QSAR 모델을 활용한 예측 툴에는 급성경구독성, 돌연변이유 발성, 피부과민성 등 인체영향과 관련된 여러 독성항목들이 있 는 반면, 급성어류독성, 급성물벼룩독성, 이분해성 등 환경영 향과 관련된 독성항목들도 있다. [6][7][8] 환경유해성 평가를 위해 화학물질의 옥탄올/물 분배계수 (log K ow )를 분자표현자(molecular descriptor)로 선형회귀(linear regression)방식을 통해 예측분석이 진행되는 ECOSAR가 많은 연구에서 활용되고 있으며, 8,9) 계층적 군집화(hierarchical clustering) 등의 합의형성적 방식(consensus method) 기반의 T.E.S.T.도 상당히 적용되고 있다. 6,10,11) 미국 EPA의 ECOTOX 단일 데이터베이스 기반의 두 예측 툴과 달리 ECOTOX 데이 터베이스 기반과 더불어 전문가 검토를 받은 문헌자료에서 독 성 데이터베이스 기반으로 하는 TOPKAT 툴은 최적예측공간 (Optimum Prediction Space, OPS) 및 2차원적 분자구조 기반 으로 예측분석이 수행된다.…”