Evidence map›Paper›PMID 37852183›Full record

ArticleCell reports. Medicine2023

Excessive concentrations of kinase inhibitors in translational studies impede effective drug repurposing.

Chuan Liu, Scott M Leighow, Kyle McIlroy, Mengrou Lu, Kady A Dennis, Kerry Abello, Donovan J Brown, Connor J Moore, Anushka Shah, Haider Inam and 2 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell reports. Medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 27% of its field
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

6 citing papers in PubMed, 2 citations in OpenAlex.

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  4. Review
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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 at 1 institution in 2 countries.

Chuan LiuDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA; Department of Oncology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China.
Scott M LeighowDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA. Electronic address: sml94@psu.edu.
Kyle McIlroyDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
Mengrou LuDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
Kady A DennisDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
Kerry AbelloDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
Donovan J BrownDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
Connor J MooreDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
Anushka ShahDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
Haider InamDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
Victor M RiveraTheseus Pharmaceuticals, Inc., Cambridge, MA 02142, USA.
Justin R PritchardDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA; The Huck Institute for the Life Sciences, Center for Resistance Evolution, The Pennsylvania State University, University Park, PA 16802, USA. Electronic address: jrp94@psu.edu.
Pennsylvania State University · US

Funding

Personalization and Failure Testing of Dual Switch Gene Drives in Lung CancerU01CA265709 · NCI · PENNSYLVANIA STATE UNIVERSITY, THE · PI PRITCHARD, JUSTIN · 2021 to 2025
$2.6M
NCI NIH HHS U01 CA265709
6 · The paper itself

Abstract

Drug repositioning seeks to leverage existing clinical knowledge to identify alternative clinical settings for approved drugs. However, repositioning efforts fail to demonstrate improved success rates in late-stage clinical trials. Focusing on 11 approved kinase inhibitors that have been evaluated in 139 repositioning hypotheses, we use data mining to characterize the state of clinical repurposing. Then, using a simple experimental correction with human serum proteins in in vitro pharmacodynamic assays, we develop a measurement of a drug's effective exposure. We show that this metric is remarkably predictive of clinical activity for a panel of five kinase inhibitors across 23 drug variant targets in leukemia. We then validate our model's performance in six other kinase inhibitors for two types of solid tumors: non-small cell lung cancer (NSCLC) and gastrointestinal stromal tumors (GISTs). Our approach presents a straightforward strategy to use existing clinical information and experimental systems to decrease the clinical failure rate in drug repurposing studies.

Indexed as

Carcinoma, Non-Small-Cell LungLeukemiaLung NeoplasmsDrug RepositioningHumansdrug repositoningdrug repurposingdrug resistancetyrosine kinase inhibitors

Identifiers

PMID37852183
PMCPMC10591048
OpenAlexW4387711216

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.