Evidence map›Paper›PMID 26262134›Full record

ArticleStudies in health technology and informatics2015

Conceptual Knowledge Discovery in Databases for Drug Combinations Predictions in Malignant Melanoma.

Kelly Regan, Satyajeet Raje, Cartik Saravanamuthu, Philip R O Payne

Abstract read
In one paragraph

Article in Studies in health technology and informatics, 2015. 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. PhLeGrA: Graph Analytics in Pharmacology over the Web of Life Sciences Linked Open Data.Proceedings of the ... International World-Wide Web Conference. International WWW Conference · 2017
    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

4 authors.

Kelly ReganDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.
Satyajeet RajeDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.
Cartik SaravanamuthuDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.
Philip R O PayneDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.

Funding

Translational Therapeutics Research Program (TT)P30CA016058 · NCI · OHIO STATE UNIVERSITY · PI Tasleem J Padamsee · 1985 to 2026
$132.3M
The OSU Clinical and Translational Research Informatics Training Program (CTRIP)T15LM011270 · NLM · OHIO STATE UNIVERSITY · PI COOMBES, KEVIN ROBERT, JANIES, DANIEL A. · 2012 to 2016
$2.2M
NCI NIH HHS P30 CA016058
6 · The paper itself

Abstract

The worldwide incidence of melanoma is rising faster than any other cancer, and prognosis for patients with metastatic disease is poor. Current targeted therapies are limited in their durability and/or effect size in certain patient populations due to acquired mechanisms of resistance. Thus, the development of synergistic combinatorial treatment regimens holds great promise to improve patient outcomes. We have previously shown that a model for in-silico knowledge discovery, Translational Ontology-anchored Knowledge Discovery Engine (TOKEn), is able to generate valid relationships between bimolecular and clinical phenotypes. In this study, we have aggregated observational and canonical knowledge consisting of melanoma-related biomolecular entities and targeted therapeutics in a computationally tractable model. We demonstrate here that the explicit linkage of therapeutic modalities with biomolecular underpinnings of melanoma utilizing the TOKEn pipeline yield a set of informed relationships that have the potential to generate combination therapy strategies.

Indexed as

Knowledge BasesAntineoplastic Combined Chemotherapy ProtocolsClinical Pharmacy Information SystemsDatabases, PharmaceuticalData MiningDecision Support Systems, ClinicalMachine LearningMelanomaNatural Language ProcessingSkin Neoplasms

Identifiers

PMID26262134
PMCPMC5081134

What OpenQuestion holds

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LicenceCC BY
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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.