Integrating QSAR and read-across for environmental assessment

被引:9
|
作者
Benfenati, E. [1 ]
Roncaglioni, A. [1 ]
Petoumenou, M. I. [1 ]
Cappelli, C. I. [1 ]
Gini, G. [2 ]
机构
[1] IRCCS, Ist Ric Farmacol Mario Negri, Milan, Italy
[2] Politecn Milan, Dipartimento Elettron Informaz & Bioingn, I-20133 Milan, Italy
关键词
read-across; BCF; REACH; QSAR; log P; BIOCONCENTRATION FACTOR BCF; CHEMICALS; MODELS;
D O I
10.1080/1062936X.2015.1078408
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Read-across and QSAR have different traditions and drawbacks. We address here two main questions: (1) How do we solve the issue of the subjectivity in the evaluation of data and results, which may be particularly critical for read-across, but may have a role also for the QSAR assessment? (2) How do we take advantage of the results of both approaches to support each other? The QSAR model starts from the training set. The presence of similar chemicals with property values close to that predicted can support the result. The approach in read-across is the opposite. The assessment is focused on the few substances similar to the target. The data quality of the similar chemicals is fundamental. A risk is poor standardization in the definition of similarity', because different approaches may be applied. Inspired by the principles of high transparency and reproducibility, a new program for read-across, called ToxRead, has been developed and made freely available (www.toxgate.eu). The output of ToxRead can be compared and integrated with the output of QSAR, within a weight-of-evidence strategy. We discuss the evaluation and integration of ToxRead and QSAR with examples of the assessment of bioconcentration factors of chemicals.
引用
收藏
页码:605 / 618
页数:14
相关论文
共 50 条
  • [41] Predicting neurological targets for chemical neurotoxins using ToxCast in vitro data and read-across within QSAR Toolbox
    Chushak, Yaroslav
    Pangburn, Heather
    Gearhart, Jeffery M.
    TOXICOLOGY LETTERS, 2017, 280 : S281 - S281
  • [42] The QSAR Toolbox automated read-across workflow for predicting acute oral toxicity: II. Verification and validation
    Kutsarova, Stela
    Schultz, Terry W.
    Chapkanov, Atanas
    Cherkezova, Daniela
    Mehmed, Aycel
    Stoeva, Stoyanka
    Kuseva, Chanita
    Yordanova, Darina
    Georgiev, Marin
    Petkov, Todor
    Mekenyan, Ovanes G.
    COMPUTATIONAL TOXICOLOGY, 2021, 20
  • [43] Using Integrated Approaches to Testing and Assessment to streamline Grouping and Read-Across of solid nanomaterials
    Stone, V.
    Oomen, A.
    Johnston, H.
    Hristozov, D.
    Schmidt, O.
    Stoeger, T.
    Aparicio, S.
    Vogel, U.
    Wohlleben, W.
    Murphy, F.
    TOXICOLOGY LETTERS, 2023, 384 : S13 - S14
  • [44] Is read-across for chemicals comparable to medical device equivalence and where to use it for conformity assessment?
    Suendermann, Jan
    Bitsch, Annette
    Kellner, Rupert
    Doll, Theodor
    REGULATORY TOXICOLOGY AND PHARMACOLOGY, 2024, 149
  • [45] Read-across approach in the risk assessment of ferrochromium. Case: Repeated dose toxicity
    Stockmann-Juvala, Helene
    Zitting, Antti
    Darrie, Grant
    Wallinder, Inger Oddnevall
    Santonen, Tiina
    TOXICOLOGY LETTERS, 2009, 189 : S245 - S245
  • [46] Integrating in silico models and read-across methods for predicting toxicity of chemicals: A step-wise strategy
    Benfenati, Emilio
    Chaudhry, Qasim
    Gini, Giuseppina
    Dorne, Jean Lou
    ENVIRONMENT INTERNATIONAL, 2019, 131
  • [47] Assessment of the predictive capacity of a physiologically based kinetic model using a read-across approach
    Paini, Alicia
    Worth, Andrew
    Kulkarni, Sunil
    Ebbrell, David
    Madden, Judith
    COMPUTATIONAL TOXICOLOGY, 2021, 18 (18)
  • [48] Grouping of nanomaterials to read-across hazard endpoints: a review
    Lamon, L.
    Aschberger, K.
    Asturiol, D.
    Richarz, A.
    Worth, A.
    NANOTOXICOLOGY, 2019, 13 (01) : 100 - 118
  • [49] Read-across Estimates of Aquatic Toxicity for Selected Fragrances
    Rorije, Emiel
    Aldenberg, Tom
    Peijnenburg, Willie
    ATLA-ALTERNATIVES TO LABORATORY ANIMALS, 2013, 41 (01): : 77 - 90
  • [50] Formation of Structural Categories to Allow for Read-Across for Teratogenicity
    Enoch, Steven J.
    Cronin, Mark T. D.
    Madden, Judith C.
    Hewitt, Mark
    QSAR & COMBINATORIAL SCIENCE, 2009, 28 (6-7): : 696 - 708