Evidence map›Paper›PMID 35188642›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Use of Lhasa Limited Products for the In Silico Prediction of Drug Toxicity.

David J Ponting, Michael J Burns, Robert S Foster, Rachel Hemingway, Grace Kocks, Donna S MacMillan, Andrew L Shannon-Little, Rachael E Tennant, Jessica R Tidmarsh, David J Yeo

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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

10 authors.

David J PontingLhasa Limited, Leeds, UK. david.ponting@lhasalimited.org.
Michael J BurnsLhasa Limited, Leeds, UK.
Robert S FosterLhasa Limited, Leeds, UK.
Rachel HemingwayLhasa Limited, Leeds, UK.
Grace KocksLhasa Limited, Leeds, UK.
Donna S MacMillanLhasa Limited, Leeds, UK.
Andrew L Shannon-LittleLhasa Limited, Leeds, UK.
Rachael E TennantLhasa Limited, Leeds, UK.
Jessica R TidmarshLhasa Limited, Leeds, UK.
David J YeoLhasa Limited, Leeds, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lhasa Limited have had a role in the in silico prediction of drug and other chemical toxicity for over 30 years. This role has always been multifaceted, both as a provider of predictive software such as Derek Nexus, and as an honest broker for the sharing of proprietary chemical and toxicity data. A changing regulatory environment and the drive for the Replacement, Reduction and Refinement (the 3Rs) of animal testing have led both to increased acceptance of in silico predictions and a desire for the sharing of data to reduce duplicate testing. The combination of these factors has led to Lhasa Limited providing a suite of products and coordinating numerous data-sharing consortia that do indeed facilitate a significant reduction in the testing burden that companies would otherwise be laboring under. Many of these products and consortia can be organized into workflows for specific regulatory use cases, and it is these that will be used to frame the narrative in this chapter.

Indexed as

Drug-Related Side Effects and Adverse ReactionsSoftwareAnimalsComputer SimulationDrug toxicityGenotoxicityIn silico modelsLhasa Limited productsToxicophore

Identifiers

What OpenQuestion holds

Textmetadata
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.