Evidence map›Paper›PMID 38851876›Full record

ArticleToxicological sciences : an official journal of the Society of Toxicology2024

Cross study analyses of SEND data: toxicity profile classification.

Mark A Carfagna, Cm Sabbir Ahmed, Susan Butler, Tamio Fukushima, William Houser, Nikolai Jensen, Brianna Paisley, Stephanie Leuenroth-Quinn, Kevin Snyder, Saurabh Vispute and 2 more

Abstract read
In one paragraph

Article in Toxicological sciences : an official journal of the Society of Toxicology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Comment on "A systematic review and meta‑analysis of side effects influenced by non‑surgical treatments in African cancer patients".Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
    Article
  3. 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

12 authors.

Mark A CarfagnaEli Lilly & Company, Indianapolis, IN 46285, United States.ORCID 0000-0003-2839-7858
Cm Sabbir AhmedUS Food & Drug Administration, Silver Spring, MD 20901, United States.
Susan ButlerUS Food & Drug Administration, Silver Spring, MD 20901, United States.ORCID 0000-0002-7116-7516
Tamio FukushimaShionogi & Co., Ltd, Osaka, 530-8560, Japan.ORCID 0000-0003-0045-4064
William HouserBristol Myers Squibb, New Brunswick, NJ 08901, United States.ORCID 0009-0002-8108-7189
Nikolai JensenNovo Nordisk, Copenhagen, 2700 Kobenhavn K, Denmark.ORCID 0000-0003-3589-3067
Brianna PaisleyEli Lilly & Company, Indianapolis, IN 46285, United States.
Stephanie Leuenroth-QuinnUS Food & Drug Administration, Silver Spring, MD 20901, United States.
Kevin SnyderUS Food & Drug Administration, Silver Spring, MD 20901, United States.ORCID 0000-0003-3029-4815
Saurabh VisputePfizer Inc, Groton, CT 06340, United States.ORCID 0009-0003-3454-2983
Wenxian WangBristol Myers Squibb, New Brunswick, NJ 08901, United States.
Md Yousuf AliUS Food & Drug Administration, Silver Spring, MD 20901, United States.ORCID 0000-0001-9382-7215

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A SEND toxicology data transformation, harmonization, and analysis platform were created to improve the identification of unique findings related to the intended target, species, and duration of dosing using data from multiple studies. The lack of a standardized digital format for data analysis had impeded large-scale analysis of in vivo toxicology studies. The CDISC SEND standard enables the analysis of data from multiple studies performed by different laboratories. This work describes methods to analyze data and automate cross-study analysis of toxicology studies. Cross-study analysis can be used to understand a single compound's toxicity profile across all studies performed and/or to evaluate on-target versus off-target toxicity for multiple compounds intended for the same pharmacological target. This work involved development of data harmonization/transformation strategies to enable cross-study analysis of both numerical and categorical SEND data. Four de-identified SEND datasets from the BioCelerate database were used for the analyses. Toxicity profiles for key organ systems were developed for liver, kidney, male reproductive tract, endocrine system, and hematopoietic system using SEND domains. A cross-study analysis dashboard with a built-in user-defined scoring system was created for custom analyses, including visualizations to evaluate data at the organ system level and drill down into individual animal data. This data analysis provides the tools for scientists to compare toxicity profiles across multiple studies using SEND. A cross-study analysis of 2 different compounds intended for the same pharmacological target is described and the analyses indicate potential on-target effects to liver, kidney, and hematopoietic systems.

Indexed as

Toxicity TestsAnimalsDatabases, FactualHumansMaleToxicologycomputational toxicologycross-study analysisSENDtoxicity profile

Identifiers

PMID38851876
PMCPMC11285163

What OpenQuestion holds

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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.