Evidence map›Paper›PMID 29313964›Full record

ArticleClinical pharmacology and therapeutics2018

The Next Generation of Drug Safety Science: Coupling Detection, Corroboration, and Validation to Discover Novel Drug Effects and Drug-Drug Interactions.

Nicholas P Tatonetti

Abstract read
In one paragraph

Article in Clinical pharmacology and therapeutics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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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

1 author.

Nicholas P TatonettiDepartment of Biomedical Informatics, Columbia University, New York, New York, USA.

Funding

Biomedical Data Translator Technical Feasibility Assessment and Architecture DesignOT3TR002027 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI DUMONTIER, MICHEL, TATONETTI, NICHOLAS P · 2016 to 2019
$2.7M
Drug Effect Discovery Through Data Mining and Integrative Chemical BiologyR01GM107145 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI TATONETTI, NICHOLAS P · 2014 to 2018
$2.5M
NCATS NIH HHS OT3 TR002027NIGMS NIH HHS R01 GM107145
6 · The paper itself

Abstract

Rare adverse drug reactions and drug-drug interactions (DDIs) are difficult to detect in randomized trials and impossible to prove using observational studies. We must ascribe to a new way of conducting research that has the efficiency of a retrospective analysis and the rigor of a prospective trial. This can be achieved by integrating observational data from humans with laboratory experiments in model systems. The former establishes clinical significance and the latter supports causality.

Indexed as

PharmacovigilanceAnimalsDatabases, FactualData MiningDrug DevelopmentDrug DiscoveryDrug InteractionsDrug-Related Side Effects and Adverse ReactionsEvidence-Based MedicineHumansLearningModels, AnimalModels, TheoreticalPatient SafetyReproducibility of ResultsRisk Assessment

Identifiers

PMID29313964
PMCPMC6005687

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.