Evidence map›Paper›PMID 20642836›Full record

ArticleJournal of translational medicine2010

Effective knowledge management in translational medicine.

Sándor Szalma, Venkata Koka, Tatiana Khasanova, Eric D Perakslis

Abstract read
In one paragraph

Article in Journal of translational medicine, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 1 pooled it
–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

43 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  11. A late-binding, distributed, NoSQL warehouse for integrating patient data from clinical trials.Database : the journal of biological databases and curation · 2019
    Article
  12. Phelan-McDermid syndrome data network: Integrating patient reported outcomes with clinical notes and curated genetic reports.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2018
    Article
  13. A systems approach to renal inflammation in SLE.Clinical immunology (Orlando, Fla.) · 2017
    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

4 authors.

Sándor SzalmaCentocor R&D, Inc, 3210 Merryfield Row, San Diego, CA 92130, USA. sszalma@its.jnj.com
Venkata Koka
Tatiana Khasanova
Eric D Perakslis

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe growing consensus that most valuable data source for biomedical discoveries is derived from human samples is clearly reflected in the growing number of translational medicine and translational sciences departments across pharma as well as academic and government supported initiatives such as Clinical and Translational Science Awards (CTSA) in the US and the Seventh Framework Programme (FP7) of EU with emphasis on translating research for human health.

methodsThe pharmaceutical companies of Johnson and Johnson have established translational and biomarker departments and implemented an effective knowledge management framework including building a data warehouse and the associated data mining applications. The implemented resource is built from open source systems such as i2b2 and GenePattern.

resultsThe system has been deployed across multiple therapeutic areas within the pharmaceutical companies of Johnson and Johnsons and being used actively to integrate and mine internal and public data to support drug discovery and development decisions such as indication selection and trial design in a translational medicine setting. Our results show that the established system allows scientist to quickly re-validate hypotheses or generate new ones with the use of an intuitive graphical interface.

conclusionsThe implemented resource can serve as the basis of precompetitive sharing and mining of studies involving samples from human subjects thus enhancing our understanding of human biology and pathophysiology and ultimately leading to more effective treatment of diseases which represent unmet medical needs.

Indexed as

Health Knowledge, Attitudes, PracticeInformation ManagementBiomarkers, TumorHumansMeta-Analysis as TopicModels, BiologicalNeoplasmsReproducibility of ResultsSearch EngineSoftwareTranslational Research, BiomedicalBiomarkers, Tumor

Identifiers

PMID20642836
PMCPMC2914663

What OpenQuestion holds

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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 OpenQuestion graph.