328 related articles for article (PubMed ID: 23670904)
1. Bayesian integrated testing strategy to assess skin sensitization potency: from theory to practice.
Jaworska J; Dancik Y; Kern P; Gerberick F; Natsch A
J Appl Toxicol; 2013 Nov; 33(11):1353-64. PubMed ID: 23670904
[TBL] [Abstract][Full Text] [Related]
2. Bayesian integrated testing strategy (ITS) for skin sensitization potency assessment: a decision support system for quantitative weight of evidence and adaptive testing strategy.
Jaworska JS; Natsch A; Ryan C; Strickland J; Ashikaga T; Miyazawa M
Arch Toxicol; 2015 Dec; 89(12):2355-83. PubMed ID: 26612363
[TBL] [Abstract][Full Text] [Related]
3. A dataset on 145 chemicals tested in alternative assays for skin sensitization undergoing prevalidation.
Natsch A; Ryan CA; Foertsch L; Emter R; Jaworska J; Gerberick F; Kern P
J Appl Toxicol; 2013 Nov; 33(11):1337-52. PubMed ID: 23576290
[TBL] [Abstract][Full Text] [Related]
4. Non-animal assessment of skin sensitization hazard: Is an integrated testing strategy needed, and if so what should be integrated?
Roberts DW; Patlewicz G
J Appl Toxicol; 2018 Jan; 38(1):41-50. PubMed ID: 28543848
[TBL] [Abstract][Full Text] [Related]
5. Integrating non-animal test information into an adaptive testing strategy - skin sensitization proof of concept case.
Jaworska J; Harol A; Kern PS; Gerberick GF
ALTEX; 2011; 28(3):211-25. PubMed ID: 21993957
[TBL] [Abstract][Full Text] [Related]
6. Probabilistic hazard assessment for skin sensitization potency by dose-response modeling using feature elimination instead of quantitative structure-activity relationships.
Luechtefeld T; Maertens A; McKim JM; Hartung T; Kleensang A; Sá-Rocha V
J Appl Toxicol; 2015 Nov; 35(11):1361-1371. PubMed ID: 26046447
[TBL] [Abstract][Full Text] [Related]
7. Prediction of skin sensitization potency using machine learning approaches.
Zang Q; Paris M; Lehmann DM; Bell S; Kleinstreuer N; Allen D; Matheson J; Jacobs A; Casey W; Strickland J
J Appl Toxicol; 2017 Jul; 37(7):792-805. PubMed ID: 28074598
[TBL] [Abstract][Full Text] [Related]
8. Data integration of non-animal tests for the development of a test battery to predict the skin sensitizing potential and potency of chemicals.
Nukada Y; Miyazawa M; Kazutoshi S; Sakaguchi H; Nishiyama N
Toxicol In Vitro; 2013 Mar; 27(2):609-18. PubMed ID: 23149339
[TBL] [Abstract][Full Text] [Related]
9. Filling the concept with data: integrating data from different in vitro and in silico assays on skin sensitizers to explore the battery approach for animal-free skin sensitization testing.
Natsch A; Emter R; Ellis G
Toxicol Sci; 2009 Jan; 107(1):106-21. PubMed ID: 18832184
[TBL] [Abstract][Full Text] [Related]
10. A comparison of reactivity schemes for the prediction skin sensitization potential.
Patlewicz G; Roberts DW; Uriarte E
Chem Res Toxicol; 2008 Feb; 21(2):521-41. PubMed ID: 18189364
[TBL] [Abstract][Full Text] [Related]
11. Non-animal methods to predict skin sensitization (II): an assessment of defined approaches
Kleinstreuer NC; Hoffmann S; Alépée N; Allen D; Ashikaga T; Casey W; Clouet E; Cluzel M; Desprez B; Gellatly N; Göbel C; Kern PS; Klaric M; Kühnl J; Martinozzi-Teissier S; Mewes K; Miyazawa M; Strickland J; van Vliet E; Zang Q; Petersohn D
Crit Rev Toxicol; 2018 May; 48(5):359-374. PubMed ID: 29474122
[TBL] [Abstract][Full Text] [Related]
12. Computer models versus reality: how well do in silico models currently predict the sensitization potential of a substance.
Teubner W; Mehling A; Schuster PX; Guth K; Worth A; Burton J; van Ravenzwaay B; Landsiedel R
Regul Toxicol Pharmacol; 2013 Dec; 67(3):468-85. PubMed ID: 24090701
[TBL] [Abstract][Full Text] [Related]
13. Novel approach for classifying chemicals according to skin sensitizing potency by non-radioisotopic modification of the local lymph node assay.
Takeyoshi M; Iida K; Shiraishi K; Hoshuyama S
J Appl Toxicol; 2005; 25(2):129-34. PubMed ID: 15744759
[TBL] [Abstract][Full Text] [Related]
14. A quantitative in silico model for predicting skin sensitization using a nearest neighbours approach within expert-derived structure-activity alert spaces.
Canipa SJ; Chilton ML; Hemingway R; Macmillan DS; Myden A; Plante JP; Tennant RE; Vessey JD; Steger-Hartmann T; Gould J; Hillegass J; Etter S; Smith BPC; White A; Sterchele P; De Smedt A; O'Brien D; Parakhia R
J Appl Toxicol; 2017 Aug; 37(8):985-995. PubMed ID: 28244128
[TBL] [Abstract][Full Text] [Related]
15. Applicability of an Integrated Testing Strategy consisting of in silico, in chemico and in vitro assays for evaluating the skin sensitization potencies of isocyanates.
Ohtake T; Maeda Y; Hayashi T; Yamanaka H; Nakai M; Takeyoshi M
Toxicology; 2018 Jan; 393():9-14. PubMed ID: 29100879
[TBL] [Abstract][Full Text] [Related]
16. Accounting for data variability, a key factor in in vivo/in vitro relationships: application to the skin sensitization potency (in vivo LLNA versus in vitro DPRA) example.
Dimitrov S; Detroyer A; Piroird C; Gomes C; Eilstein J; Pauloin T; Kuseva C; Ivanova H; Popova I; Karakolev Y; Ringeissen S; Mekenyan O
J Appl Toxicol; 2016 Dec; 36(12):1568-1578. PubMed ID: 27080242
[TBL] [Abstract][Full Text] [Related]
17. Integrated testing and assessment approaches for skin sensitization: a commentary.
Roberts DW; Patlewicz GY
J Appl Toxicol; 2014 Apr; 34(4):436-40. PubMed ID: 24122899
[TBL] [Abstract][Full Text] [Related]
18. Adjustment of a no expected sensitization induction level derived from Bayesian network integrated testing strategy for skin sensitization risk assessment.
Otsubo Y; Nishijo T; Mizumachi H; Saito K; Miyazawa M; Sakaguchi H
J Toxicol Sci; 2020; 45(1):57-67. PubMed ID: 31932558
[TBL] [Abstract][Full Text] [Related]
19. Anchoring molecular mechanisms to the adverse outcome pathway for skin sensitization: Analysis of existing data.
van der Veen JW; Soeteman-Hernández LG; Ezendam J; Stierum R; Kuper FC; van Loveren H
Crit Rev Toxicol; 2014 Aug; 44(7):590-9. PubMed ID: 25000333
[TBL] [Abstract][Full Text] [Related]
20. Can currently available non-animal methods detect pre and pro-haptens relevant for skin sensitization?
Patlewicz G; Casati S; Basketter DA; Asturiol D; Roberts DW; Lepoittevin JP; Worth AP; Aschberger K
Regul Toxicol Pharmacol; 2016 Dec; 82():147-155. PubMed ID: 27569201
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
