Construction of a drug safety assurance information system based on clinical genotyping.

John A Springer, Nicholas V Iannotti, Jon E Sprague, Michael D Kane

Abstract read

In one paragraph

Article in ISRN bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

John A SpringerDepartment of Computer and Information Technology, Purdue University, West Lafayette, IN 47907, USA ; Bindley Bioscience Center, Purdue University, IN 47907, USA.

Nicholas V IannottiDepartment of Computer and Information Technology, Purdue University, West Lafayette, IN 47907, USA.

Jon E SpragueRaabe College of Pharmacy, Ohio Northern University, Ada, OH 45810, USA.

Michael D KaneDepartment of Computer and Information Technology, Purdue University, West Lafayette, IN 47907, USA ; Bindley Bioscience Center, Purdue University, IN 47907, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To capitalize on the vast potential of patient genetic information to aid in assuring drug safety, a substantial effort is needed in both the training of healthcare professionals and the operational enablement of clinical environments. Our research aims to satisfy these needs through the development of a drug safety assurance information system (GeneScription) based on clinical genotyping that utilizes patient-specific genetic information to predict and prevent adverse drug responses. In this paper, we present the motivations for this work, the algorithms at the heart of GeneScription, and a discussion of our system and its uses. We also describe our efforts to validate GeneScription through its evaluation by practicing pharmacists and pharmacy professors and its repeated use in training pharmacists. The positive assessment of the GeneScription software tool by these domain experts provides strong validation of the importance, accuracy, and effectiveness of GeneScription.

Identifiers

PMID25969745

DOI10.5402/2012/982737

PMCPMC4407205

What OpenQuestion holds

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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.