PMID- 23670904
OWN - NLM
STAT- MEDLINE
DCOM- 20150629
LR  - 20220311
IS  - 1099-1263 (Electronic)
IS  - 0260-437X (Linking)
VI  - 33
IP  - 11
DP  - 2013 Nov
TI  - Bayesian integrated testing strategy to assess skin sensitization potency: from 
      theory to practice.
PG  - 1353-64
LID - 10.1002/jat.2869 [doi]
AB  - Frameworks to predict in vivo effects by integration of in vitro, in silico and 
      in chemico information using mechanistic insight are needed to meet the 
      challenges of 21(st) century toxicology. Expert-based approaches that 
      qualitatively integrate multifaceted data are practiced under the term 'weight of 
      evidence', whereas quantitative approaches remain rare. To address this gap we 
      previously developed a methodology to design an Integrated Testing Strategy (ITS) 
      in the form of a Bayesian Network (BN). This study follows up on our proof of 
      concept work and presents an updated ITS to assess skin sensitization potency 
      expressed as local lymph node assay (LLNA) potency classes. Modifications to the 
      ITS structure were introduced to include better mechanistic information. The 
      parameters of the updated ITS were calculated from an extended data set of 124 
      chemicals. A detailed validation analysis and a case study were carried out to 
      demonstrate the utility of the ITS for practical application. The improved BN ITS 
      predicted correctly 95% and 86% of chemicals in a test set (n = 21) for hazard 
      and LLNA potency classes, respectively. The practical value of using the BN ITS 
      is far more than a prediction framework when all data are available. The BN ITS 
      can develop a hypothesis using subsets of data as small as one data point and can 
      be queried on the value of adding additional tests before testing is commenced. 
      The ITS represents key steps of the skin sensitization process and a 
      mechanistically interpretable testing strategy can be developed. These features 
      are illustrated in the manuscript via practical examples.
CI  - Copyright (c) 2013 John Wiley & Sons, Ltd.
FAU - Jaworska, Joanna
AU  - Jaworska J
AD  - Procter & Gamble NV, 100 Temselaan, 1853, Strombeek - Bever, Belgium.
FAU - Dancik, Yuri
AU  - Dancik Y
FAU - Kern, Petra
AU  - Kern P
FAU - Gerberick, Frank
AU  - Gerberick F
FAU - Natsch, Andreas
AU  - Natsch A
LA  - eng
PT  - Journal Article
DEP - 20130514
PL  - England
TA  - J Appl Toxicol
JT  - Journal of applied toxicology : JAT
JID - 8109495
SB  - IM
MH  - Animal Testing Alternatives/*methods/statistics & numerical data
MH  - Animals
MH  - Bayes Theorem
MH  - Cell Line
MH  - Databases, Factual
MH  - Dermatitis, Allergic Contact/*etiology/immunology
MH  - *Drug-Related Side Effects and Adverse Reactions
MH  - *Models, Biological
MH  - Predictive Value of Tests
MH  - Toxicity Tests/*methods/statistics & numerical data
OTO - NOTNLM
OT  - Bayesian Network
OT  - LLNA potency class
OT  - integrated testing strategy
OT  - skin sensitization
EDAT- 2013/05/15 06:00
MHDA- 2015/06/30 06:00
CRDT- 2013/05/15 06:00
PHST- 2013/01/14 00:00 [received]
PHST- 2013/02/04 00:00 [revised]
PHST- 2013/02/04 00:00 [accepted]
PHST- 2013/05/15 06:00 [entrez]
PHST- 2013/05/15 06:00 [pubmed]
PHST- 2015/06/30 06:00 [medline]
AID - 10.1002/jat.2869 [doi]
PST - ppublish
SO  - J Appl Toxicol. 2013 Nov;33(11):1353-64. doi: 10.1002/jat.2869. Epub 2013 May 14.