Evidence map›Paper›PMID 32324077›Full record

ReviewExpert opinion on drug metabolism & toxicology2020

What have we learned from animal models of idiosyncratic, drug-induced liver injury?

Robert A Roth, Patricia E Ganey

Abstract readReview
In one paragraph

Review in Expert opinion on drug metabolism & toxicology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Robert A RothDepartment of Pharmacology and Toxicology and Institute for Integrative Toxicology, Michigan State University , East Lansing, MI, USA.
Patricia E GaneyDepartment of Pharmacology and Toxicology and Institute for Integrative Toxicology, Michigan State University , East Lansing, MI, USA.

Funding

An Assay to Predict the Potential of Drug Candidates to Cause Idiosyncratic, Drug-induced Liver InjuryR01DK112695 · NIDDK · MICHIGAN STATE UNIVERSITY · PI GANEY, PATRICIA E, ROTH, ROBERT ANDREW · 2017 to 2019
$1.0M
NIDDK NIH HHS R01 DK112695
6 · The paper itself

Abstract

introductionIdiosyncratic, drug-induced liver injury (IDILI) continues to plague patients and restrict the use of drugs that are pharmacologically effective. Mechanisms of IDILI are incompletely understood, and a better understanding would reduce speculation and could help to identify safer drug candidates preclinically. Animal models have the potential to enhance knowledge of mechanisms of IDILI. AREAS COVERED: Numerous hypotheses have emerged to explain IDILI pathogenesis, many of which center on the roles of the innate and/or adaptive immune systems. Animal models based on these hypotheses are reviewed in the context of their contributions to understanding of IDILI and their limitations. EXPERT OPINION: Animal models of IDILI based on an activated adaptive immune system have to date failed to reproduce major liver injury that is of most concern clinically. The only models that have so far resulted in pronounced liver injury are based on the multiple determinant hypothesis or the inflammatory stress hypothesis. The liver pathogenesis in IDILI animal models involves various leukocytes and immune mediators such as cytokines. Insights from animal models are changing the way we view IDILI pathogenesis and are leading to better approaches to preclinical prediction of IDILI potential of new drug candidates.

Indexed as

Disease Models, AnimalAdaptive ImmunityAnimalsChemical and Drug Induced Liver InjuryCytokinesDrug Evaluation, PreclinicalHumansImmunity, InnateCytokinesadaptive immunityanimal modelsdrug-induced liver injuryhepatotoxicityIdiosyncraticinflammatory stress

Identifiers

PMID32324077
PMCPMC7315440

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.