PMID- 36805911
OWN - NLM
STAT- MEDLINE
DCOM- 20230315
LR  - 20230315
IS  - 1096-0295 (Electronic)
IS  - 0273-2300 (Linking)
VI  - 139
DP  - 2023 Mar
TI  - Estimating uncertainty in LLNA EC3 data and its impact on regulatory 
      classifications.
PG  - 105357
LID - S0273-2300(23)00025-9 [pii]
LID - 10.1016/j.yrtph.2023.105357 [doi]
AB  - The murine Local Lymph Node Assay (LLNA) is a test that produces numerical 
      results (EC3 values) quantifying the sensitization potency of chemicals. These 
      results are broadly used in toxicology and serve as a basis for various 
      classifications, which determine subsequent regulatory decisions. The continuing 
      interest in LLNA data and the diminished likelihood of new experimental EC3 data 
      being generated sparked this investigation of uncertainty. Instead of using the 
      Gaussian distribution as a default choice for assessing variability in a data 
      set, two strictly positive distributions were proposed and their performance over 
      the available experimental EC3 values was tested. In the application stage, how 
      the uncertainty in EC3 values affects the possible classifications was analyzed, 
      and the percentage of the chemicals receiving ambiguous classification was 
      determined. It was shown that this percentage is high, which increases the risk 
      of improper classification. Two approaches were suggested in regulatory practice 
      to address the uncertainty in the EC3 data: the approaches based on "grey zones" 
      and the classification distribution. If a chemical cannot be classified 
      unambiguously, the latter appears to be an acceptable means to assess the level 
      of sensitization potency of chemicals and helps provide better regulatory 
      decisions.
CI  - Copyright (c) 2023 Elsevier Inc. All rights reserved.
FAU - Chapkanov, Atanas
AU  - Chapkanov A
AD  - Laboratory of Mathematical Chemistry, Prof. As. Zlatarov University, Bourgas, 
      Bulgaria.
FAU - Schultz, Terry W
AU  - Schultz TW
AD  - The University of Tennessee, College of Veterinary Medicine, Knoxville, TN, 
      37996-4500, USA.
FAU - Yordanova, Darina
AU  - Yordanova D
AD  - Laboratory of Mathematical Chemistry, Prof. As. Zlatarov University, Bourgas, 
      Bulgaria.
FAU - Kirilov, Kalin
AU  - Kirilov K
AD  - Laboratory of Mathematical Chemistry, Prof. As. Zlatarov University, Bourgas, 
      Bulgaria.
FAU - Ivanova, Hristiana
AU  - Ivanova H
AD  - Laboratory of Mathematical Chemistry, Prof. As. Zlatarov University, Bourgas, 
      Bulgaria.
FAU - Mekenyan, Ovanes G
AU  - Mekenyan OG
AD  - Laboratory of Mathematical Chemistry, Prof. As. Zlatarov University, Bourgas, 
      Bulgaria. Electronic address: omekenya@btu.bg.
LA  - eng
PT  - Journal Article
DEP - 20230216
PL  - Netherlands
TA  - Regul Toxicol Pharmacol
JT  - Regulatory toxicology and pharmacology : RTP
JID - 8214983
RN  - 0 (Allergens)
SB  - IM
MH  - Animals
MH  - Mice
MH  - *Dermatitis, Allergic Contact
MH  - Local Lymph Node Assay
MH  - Allergens/toxicity
MH  - Uncertainty
MH  - Dose-Response Relationship, Drug
OTO - NOTNLM
OT  - Local lymph node assay (LLNA)
OT  - Skin sensitization categorization
OT  - Uncertainty
COIS- Declaration of competing interest The authors declare that they have no known 
      competing financial interests or personal relationships that could have appeared 
      to influence the work reported in this paper.
EDAT- 2023/02/23 06:00
MHDA- 2023/03/16 06:00
CRDT- 2023/02/22 10:09
PHST- 2022/10/28 00:00 [received]
PHST- 2023/02/01 00:00 [revised]
PHST- 2023/02/14 00:00 [accepted]
PHST- 2023/02/23 06:00 [pubmed]
PHST- 2023/03/16 06:00 [medline]
PHST- 2023/02/22 10:09 [entrez]
AID - S0273-2300(23)00025-9 [pii]
AID - 10.1016/j.yrtph.2023.105357 [doi]
PST - ppublish
SO  - Regul Toxicol Pharmacol. 2023 Mar;139:105357. doi: 10.1016/j.yrtph.2023.105357. 
      Epub 2023 Feb 16.