PMID- 24721472
OWN - NLM
STAT- MEDLINE
DCOM- 20140715
LR  - 20191210
IS  - 1879-3185 (Electronic)
IS  - 0300-483X (Linking)
VI  - 321
DP  - 2014 Jul 3
TI  - Construction and analysis of a human hepatotoxicity database suitable for QSAR 
      modeling using post-market safety data.
PG  - 62-72
LID - S0300-483X(14)00065-1 [pii]
LID - 10.1016/j.tox.2014.03.009 [doi]
AB  - Drug-induced liver injury (DILI) is one of the most common drug-induced adverse 
      events (AEs) leading to life-threatening conditions such as acute liver failure. 
      It has also been recognized as the single most common cause of safety-related 
      post-market withdrawals or warnings. Efforts to develop new predictive methods to 
      assess the likelihood of a drug being a hepatotoxicant have been challenging due 
      to the complexity and idiosyncrasy of clinical manifestations of DILI. The FDA 
      adverse event reporting system (AERS) contains post-market data that depict the 
      morbidity of AEs. Here, we developed a scalable approach to construct a 
      hepatotoxicity database using post-market data for the purpose of quantitative 
      structure-activity relationship (QSAR) modeling. A set of 2029 unique and 
      modelable drug entities with 13,555 drug-AE combinations was extracted from the 
      AERS database using 37 hepatotoxicity-related query preferred terms (PTs). In 
      order to determine the optimal classification scheme to partition positive from 
      negative drugs, a manually-curated DILI calibration set composed of 105 negatives 
      and 177 positives was developed based on the published literature. The final 
      classification scheme combines hepatotoxicity-related PT data with supporting 
      information that optimize the predictive performance across the calibration set. 
      Data for other toxicological endpoints related to liver injury such as liver 
      enzyme abnormalities, cholestasis, and bile duct disorders, were also extracted 
      and classified. Collectively, these datasets can be used to generate a battery of 
      QSAR models that assess a drug's potential to cause DILI.
CI  - Published by Elsevier Ireland Ltd.
FAU - Zhu, Xiao
AU  - Zhu X
AD  - U.S. Food and Drug Administration, Center for Drug Evaluation and Research, 10903 
      New Hampshire Avenue, Silver Spring, MD 20993, United States.
FAU - Kruhlak, Naomi L
AU  - Kruhlak NL
AD  - U.S. Food and Drug Administration, Center for Drug Evaluation and Research, 10903 
      New Hampshire Avenue, Silver Spring, MD 20993, United States. Electronic address: 
      Naomi.Kruhlak@fda.hhs.gov.
LA  - eng
PT  - Journal Article
PT  - Research Support, U.S. Gov't, P.H.S.
PT  - Validation Study
DEP - 20140408
PL  - Ireland
TA  - Toxicology
JT  - Toxicology
JID - 0361055
RN  - 0 (Anti-Bacterial Agents)
RN  - 0 (Anti-Inflammatory Agents, Non-Steroidal)
RN  - 0 (Vitamins)
RN  - 57Y76R9ATQ (Naproxen)
RN  - 6GNT3Y5LMF (Levofloxacin)
RN  - 7C782967RD (Ampicillin)
RN  - PQ6CK8PD0R (Ascorbic Acid)
SB  - IM
MH  - Algorithms
MH  - Ampicillin/toxicity
MH  - Animals
MH  - Anti-Bacterial Agents/toxicity
MH  - Anti-Inflammatory Agents, Non-Steroidal/toxicity
MH  - Ascorbic Acid/toxicity
MH  - Bile Duct Diseases/chemically induced/pathology
MH  - Calibration
MH  - Chemical and Drug Induced Liver Injury/classification/enzymology/*pathology
MH  - Cholestasis/chemically induced/pathology
MH  - Data Mining
MH  - Databases, Factual
MH  - Drug Labeling
MH  - Endpoint Determination
MH  - Humans
MH  - Levofloxacin/toxicity
MH  - Liver/enzymology/pathology
MH  - Naproxen/toxicity
MH  - Product Surveillance, Postmarketing
MH  - Quantitative Structure-Activity Relationship
MH  - Toxicity Tests/*statistics & numerical data
MH  - Vitamins/toxicity
OTO - NOTNLM
OT  - Drug-induced liver injury
OT  - Post-market safety
OT  - Predictive toxicology
OT  - QSAR
EDAT- 2014/04/12 06:00
MHDA- 2014/07/16 06:00
CRDT- 2014/04/12 06:00
PHST- 2014/03/21 00:00 [received]
PHST- 2014/03/28 00:00 [accepted]
PHST- 2014/04/12 06:00 [entrez]
PHST- 2014/04/12 06:00 [pubmed]
PHST- 2014/07/16 06:00 [medline]
AID - S0300-483X(14)00065-1 [pii]
AID - 10.1016/j.tox.2014.03.009 [doi]
PST - ppublish
SO  - Toxicology. 2014 Jul 3;321:62-72. doi: 10.1016/j.tox.2014.03.009. Epub 2014 Apr 
      8.