Evidence map›Paper›PMID 38895462›Full record

ArticlebioRxiv : the preprint server for biology2024

Improved Detection of Drug-Induced Liver Injury by Integrating Predicted

Srijit Seal, Dominic P Williams, Layla Hosseini-Gerami, Manas Mahale, Anne E Carpenter, Ola Spjuth, Andreas Bender

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Srijit SealYusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Rd, CB2 1EW, Cambridge, United Kingdom.ORCID 0000-0003-2790-8679
Dominic P WilliamsSafety Innovation, Clinical Pharmacology and Safety Sciences, AstraZeneca, Cambridge CB4 0FZ, United Kingdom.ORCID 0000-0002-0758-3152
Layla Hosseini-GeramiIgnota Labs, County Hall, Westminster Bridge Rd, SE1 7PB, London, United Kingdom.ORCID 0000-0003-0948-2387
Manas MahaleBombay College of Pharmacy Kalina Santacruz (E), Mumbai 400 098, India.ORCID 0009-0007-3867-996X
Anne E CarpenterImaging Platform, Broad Institute of MIT and Harvard, US.
Ola SpjuthDepartment of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Box 591, SE-75124, Uppsala, Sweden.ORCID 0000-0002-8083-2864
Andreas BenderYusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Rd, CB2 1EW, Cambridge, United Kingdom.ORCID 0000-0002-6683-7546

Funding

Extracting rich information from biological imagesR35GM122547 · NIGMS · BROAD INSTITUTE, INC. · PI Anne E. Carpenter · 2017 to 2026
$6.2M
NIGMS NIH HHS R35 GM122547
6 · The paper itself

Abstract

Drug-induced liver injury (DILI) has been significant challenge in drug discovery, often leading to clinical trial failures and necessitating drug withdrawals. The existing suite of in vitro proxy-DILI assays is generally effective at identifying compounds with hepatotoxicity. However, there is considerable interest in enhancing in silico prediction of DILI because it allows for the evaluation of large sets of compounds more quickly and cost-effectively, particularly in the early stages of projects. In this study, we aim to study ML models for DILI prediction that first predicts nine proxy-DILI labels and then uses them as features in addition to chemical structural features to predict DILI. The features include

Indexed as

DILIDrug-Induced Liver Injuryin vitroin vivoMachine LearningToxicityToxicity Prediction

Identifiers

PMID38895462
PMCPMC11185581

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.