PMID- 26851134
OWN - NLM
STAT- MEDLINE
DCOM- 20170410
LR  - 20220311
IS  - 1099-1263 (Electronic)
IS  - 0260-437X (Print)
IS  - 0260-437X (Linking)
VI  - 36
IP  - 9
DP  - 2016 Sep
TI  - Integrated decision strategies for skin sensitization hazard.
PG  - 1150-62
LID - 10.1002/jat.3281 [doi]
AB  - One of the top priorities of the Interagency Coordinating Committee for the 
      Validation of Alternative Methods (ICCVAM) is the identification and evaluation 
      of non-animal alternatives for skin sensitization testing. Although skin 
      sensitization is a complex process, the key biological events of the process have 
      been well characterized in an adverse outcome pathway (AOP) proposed by the 
      Organisation for Economic Co-operation and Development (OECD). Accordingly, 
      ICCVAM is working to develop integrated decision strategies based on the AOP 
      using in vitro, in chemico and in silico information. Data were compiled for 120 
      substances tested in the murine local lymph node assay (LLNA), direct peptide 
      reactivity assay (DPRA), human cell line activation test (h-CLAT) and 
      KeratinoSens assay. Data for six physicochemical properties, which may affect 
      skin penetration, were also collected, and skin sensitization read-across 
      predictions were performed using OECD QSAR Toolbox. All data were combined into a 
      variety of potential integrated decision strategies to predict LLNA outcomes 
      using a training set of 94 substances and an external test set of 26 substances. 
      Fifty-four models were built using multiple combinations of machine learning 
      approaches and predictor variables. The seven models with the highest accuracy 
      (89-96% for the test set and 96-99% for the training set) for predicting LLNA 
      outcomes used a support vector machine (SVM) approach with different combinations 
      of predictor variables. The performance statistics of the SVM models were higher 
      than any of the non-animal tests alone and higher than simple test battery 
      approaches using these methods. These data suggest that computational approaches 
      are promising tools to effectively integrate data sources to identify potential 
      skin sensitizers without animal testing. Published 2016. This article has been 
      contributed to by US Government employees and their work is in the public domain 
      in the USA.
CI  - Published 2016. This article has been contributed to by US Government employees 
      and their work is in the public domain in the USA.
FAU - Strickland, Judy
AU  - Strickland J
AD  - ILS, Research Triangle Park, North Carolina, 27709, USA.
FAU - Zang, Qingda
AU  - Zang Q
AD  - ILS, Research Triangle Park, North Carolina, 27709, USA.
FAU - Kleinstreuer, Nicole
AU  - Kleinstreuer N
AD  - ILS, Research Triangle Park, North Carolina, 27709, USA.
FAU - Paris, Michael
AU  - Paris M
AD  - ILS, Research Triangle Park, North Carolina, 27709, USA.
FAU - Lehmann, David M
AU  - Lehmann DM
AD  - EPA/NHEERL/EPHD/CIB, Research Triangle Park, North Carolina, 27709, USA.
FAU - Choksi, Neepa
AU  - Choksi N
AD  - ILS, Research Triangle Park, North Carolina, 27709, USA.
FAU - Matheson, Joanna
AU  - Matheson J
AD  - U.S. Consumer Product Safety Commission, Bethesda, Maryland, 20814, USA.
FAU - Jacobs, Abigail
AU  - Jacobs A
AD  - FDA/CDER, Silver Spring, Maryland, 20993, USA.
FAU - Lowit, Anna
AU  - Lowit A
AD  - EPA/OCSPP/OPP/HED, Washington, District of Columbia, 20460, USA.
FAU - Allen, David
AU  - Allen D
AD  - ILS, Research Triangle Park, North Carolina, 27709, USA.
FAU - Casey, Warren
AU  - Casey W
AD  - NIH/NIEHS/DNTP/NICEATM, Research Triangle Park, North Carolina, 27709, USA.
LA  - eng
GR  - HHSN273201500010C/ES/NIEHS NIH HHS/United States
GR  - Z99 ES999999/Intramural NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
DEP - 20160206
PL  - England
TA  - J Appl Toxicol
JT  - Journal of applied toxicology : JAT
JID - 8109495
RN  - 0 (Allergens)
RN  - 0 (Xenobiotics)
SB  - IM
EIN - J Appl Toxicol. 2018 Mar;38(3):432. PMID: 29363186
MH  - Allergens/*toxicity
MH  - Animal Testing Alternatives/methods
MH  - Animals
MH  - Cell Line
MH  - Computational Biology
MH  - Decision Making
MH  - Dermatitis, Allergic Contact/pathology
MH  - Humans
MH  - Local Lymph Node Assay
MH  - Mice
MH  - Reproducibility of Results
MH  - Risk Assessment
MH  - Skin/*drug effects
MH  - Xenobiotics/*toxicity
PMC - PMC4945438
MID - NIHMS747600
OTO - NOTNLM
OT  - DPRA
OT  - KeratinoSens
OT  - LLNA
OT  - allergic contact dermatitis
OT  - h-CLAT
OT  - integrated decision strategy
OT  - machine learning
OT  - skin sensitization
OT  - support vector machine
COIS- Conflict of interest statement The authors declare that there are no conflicts of 
      interest.
EDAT- 2016/02/07 06:00
MHDA- 2017/04/11 06:00
PMCR- 2017/09/01
CRDT- 2016/02/07 06:00
PHST- 2015/10/09 00:00 [received]
PHST- 2015/11/10 00:00 [revised]
PHST- 2015/12/02 00:00 [accepted]
PHST- 2016/02/07 06:00 [entrez]
PHST- 2016/02/07 06:00 [pubmed]
PHST- 2017/04/11 06:00 [medline]
PHST- 2017/09/01 00:00 [pmc-release]
AID - 10.1002/jat.3281 [doi]
PST - ppublish
SO  - J Appl Toxicol. 2016 Sep;36(9):1150-62. doi: 10.1002/jat.3281. Epub 2016 Feb 6.