Applicability of in silico models for the prediction of the sensitization potential of industrial chemicals

被引:0
|
作者
Teubner, Wera [1 ]
Mehling, Annette [2 ]
Schuster, Paul Xaver [3 ]
Guth, Katharina [3 ]
Worth, Andrew [4 ]
Burton, Julien [4 ]
van Ravenzwaay, Bennard [3 ]
Landsiedel, Robert [3 ]
机构
[1] BASF Schweiz AG, Basel, Switzerland
[2] BASF Personal Care & Nutr GmbH, Dusseldorf, Germany
[3] BASF SE, Ludwigshafen, Germany
[4] European Commiss, Joint Res Ctr, Inst Hlth & Consumer Protect, Ispra, Italy
关键词
D O I
10.1016/j.toxlet.2013.05.480
中图分类号
R99 [毒物学(毒理学)];
学科分类号
100405 ;
摘要
引用
收藏
页码:S204 / S204
页数:1
相关论文
共 50 条
  • [31] Prediction of microbial toxicity of industrial organic chemicals
    Trevizo, C
    Nirmalakhandan, N
    WATER SCIENCE AND TECHNOLOGY, 1999, 39 (10-11) : 63 - 69
  • [32] Prediction models of toxicological properties of chemicals
    Osipov, A.L.
    Semenov, R.D.
    Avtometriya, 1996, (06): : 101 - 106
  • [33] Comparison of In Silico Models for Prediction of Mutagenicity
    Bakhtyari, Nazanin G.
    Raitano, Giuseppa
    Benfenati, Emilio
    Martin, Todd
    Young, Douglas
    JOURNAL OF ENVIRONMENTAL SCIENCE AND HEALTH PART C-ENVIRONMENTAL CARCINOGENESIS & ECOTOXICOLOGY REVIEWS, 2013, 31 (01): : 45 - 66
  • [34] The use of in silico models for the prediction of mutagenicity
    Middlemiss, R.
    Crooks, I.
    Lopez-Belmonte, J.
    Nielson, L.
    Meredith, C.
    TOXICOLOGY LETTERS, 2019, 314 : S246 - S247
  • [35] Expanding the applicability of multimedia fate models to polar organic chemicals
    Breivik, K
    Wania, F
    ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2003, 37 (21) : 4934 - 4943
  • [36] LC-MS-Based Characterization of the Peptide Reactivity of Chemicals to Improve the In Vitro Prediction of the Skin Sensitization Potential
    Natsch, Andreas
    Gfeller, Hans
    TOXICOLOGICAL SCIENCES, 2008, 106 (02) : 464 - 478
  • [37] Applicability domain for in silico models to achieve accuracy of experimental measurements
    Sushko, Iurii
    Novotarskyi, Sergii
    Koerner, Robert
    Pandey, Anil Kumar
    Kovalishyn, Vasily V.
    Prokopenko, Volodymyr V.
    Tetko, Igor V.
    JOURNAL OF CHEMOMETRICS, 2010, 24 (3-4) : 202 - 208
  • [38] In Silico Prediction of Chemicals Binding to Aromatase with Machine Learning Methods
    Du, Hanwen
    Cai, Yingchun
    Yang, Hongbin
    Zhang, Hongxiao
    Xue, Yuhan
    Liu, Guixia
    Tang, Yun
    Li, Weihua
    CHEMICAL RESEARCH IN TOXICOLOGY, 2017, 30 (05) : 1209 - 1218
  • [39] THP-1 in Coculture with HaCaT Keratinocytes (COCAT) for an advanced in vitro prediction of sensitization potential and potency of chemicals
    Hennen, J.
    Blomeke, B.
    TOXICOLOGY LETTERS, 2016, 258 : S145 - S145
  • [40] In Silico Prediction of the Toxic Potential of Lupeol
    Ruiz-Rodriguez, Manuel A.
    Vedani, Angelo
    Flores-Mireles, Ana L.
    Chairez-Ramirez, Manuel H.
    Gallegos-Infante, Jose A.
    Gonzalez-Laredo, Ruben F.
    CHEMICAL RESEARCH IN TOXICOLOGY, 2017, 30 (08) : 1562 - 1571