Evidence map›Paper›PMID 29635477›Full record

ReviewHuman molecular genetics2018

Pharmacogenomics and big genomic data: from lab to clinic and back again.

Adam Lavertu, Greg McInnes, Roxana Daneshjou, Michelle Whirl-Carrillo, Teri E Klein, Russ B Altman

Abstract readReview
In one paragraph

Review in Human molecular genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. New Personalized Medicine Model for Medication Management.Journal of personalized medicine · 2026
    Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Genomewide Association Studies in Pharmacogenomics.Clinical pharmacology and therapeutics · 2021
    Review
  13. Pharmacogenetics at Scale: An Analysis of the UK Biobank.Clinical pharmacology and therapeutics · 2021
    Article
  14. Review
  15. Drug Response Pharmacogenetics for 200,000 UK Biobank Participants.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2021
    Article
  16. Article
  17. Review
  18. Artificial Intelligence and Personalized Medicine.Cancer treatment and research · 2019
    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

6 authors.

Adam LavertuBiomedical Informatics Training Program, Stanford University, Stanford, CA 94305, USA.
Greg McInnesBiomedical Informatics Training Program, Stanford University, Stanford, CA 94305, USA.
Roxana DaneshjouDepartment of Genetics, Stanford University, Stanford, CA 94305, USA.
Michelle Whirl-CarrilloDepartment of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA.
Teri E KleinDepartment of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA.
Russ B AltmanDepartment of Genetics, Stanford University, Stanford, CA 94305, USA.

Funding

PharmGKB: pharmacogenomics knowledge for precision medicineR24GM061374 · NIGMS · STANFORD UNIVERSITY · PI ALTMAN, RUSS BIAGIO, KLEIN, TERI ELLEN · 2010 to 2018
$25.2M
Text Mining for High-fidelity Curation and Discovery of Gene-drug-phenotype RelationshipsR01LM005652 · NLM · STANFORD UNIVERSITY · PI ALTMAN, RUSS BIAGIO · 2000 to 2018
$6.2M
UCSF-Stanford Center of Excellence in Regulatory Science and InnovationU01FD004979 · FDA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ALTMAN, RUSS BIAGIO, GIACOMINI, KATHLEEN M · 2014 to 2016
$5.4M
Clinical Pharmacogenetics Implementation Consortium (CPIC)R24GM115264 · NIGMS · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI KLEIN, TERI ELLEN, RELLING, MARY V · 2015 to 2017
$3.6M
Undergraduate Summer Research Experiences Support for Combining systems biology and structural biology to find new therapeuticsR01GM102365 · NIGMS · STANFORD UNIVERSITY · PI ALTMAN, RUSS BIAGIO · 2012 to 2021
$3.0M
Biomedical Data Science Graduate Training at StanfordT32LM012409 · NLM · STANFORD UNIVERSITY · PI PLEVRITIS, SYLVIA KATINA · 2016 to 2020
$1.5M
FDA HHS U01 FD004979NIGMS NIH HHS R01 GM102365NIGMS NIH HHS R24 GM061374NIGMS NIH HHS R24 GM115264NLM NIH HHS R01 LM005652NLM NIH HHS T32 LM012409
6 · The paper itself

Abstract

The field of pharmacogenomics is an area of great potential for near-term human health impacts from the big genomic data revolution. Pharmacogenomics research momentum is building with numerous hypotheses currently being investigated through the integration of molecular profiles of different cell lines and large genomic data sets containing information on cellular and human responses to therapies. Additionally, the results of previous pharmacogenetic research efforts have been formulated into clinical guidelines that are beginning to impact how healthcare is conducted on the level of the individual patient. This trend will only continue with the recent release of new datasets containing linked genotype and electronic medical record data. This review discusses key resources available for pharmacogenomics and pharmacogenetics research and highlights recent work within the field.

Indexed as

Big DataGenomicsGenotypeHumansPharmacogeneticsPharmacogenomic Testing

Identifiers

PMID29635477
PMCPMC5946941

What OpenQuestion holds

Textmetadata
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.