Evidence map›Paper›PMID 33291630›Full record

ReviewGenes2020

Technologies for Pharmacogenomics: A Review.

Maaike van der Lee, Marjolein Kriek, Henk-Jan Guchelaar, Jesse J Swen

Abstract readReview
In one paragraph

Review in Genes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Article
  2. Polygenic risk scores in pharmacogenomics: methodological challenges, current applications, and perspectives for clinical implementation.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Unlocking Performance: Pharmacogenomic Insights for Athletes.Sports medicine international open · 2026
    Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Overcoming Barriers to Discovery and Implementation of Equitable Pharmacogenomic Testing in Oncology.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2024
    Review
  17. Article
  18. Article
  19. Article
  20. 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.

Maaike van der LeeDepartment of Clinical Pharmacy and Toxicology, Leiden University Medical Center, 2333ZA Leiden, The Netherlands.ORCID 0000-0003-3344-6896
Marjolein KriekDepartment of Clinical Genetics, Leiden University Medical Center, 2333ZA Leiden, The Netherlands.
Henk-Jan GuchelaarDepartment of Clinical Pharmacy and Toxicology, Leiden University Medical Center, 2333ZA Leiden, The Netherlands.ORCID 0000-0002-7085-1383
Jesse J SwenDepartment of Clinical Pharmacy and Toxicology, Leiden University Medical Center, 2333ZA Leiden, The Netherlands.ORCID 0000-0002-3965-5552

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The continuous development of new genotyping technologies requires awareness of their potential advantages and limitations concerning utility for pharmacogenomics (PGx). In this review, we provide an overview of technologies that can be applied in PGx research and clinical practice. Most commonly used are single nucleotide variant (SNV) panels which contain a pre-selected panel of genetic variants. SNV panels offer a short turnaround time and straightforward interpretation, making them suitable for clinical practice. However, they are limited in their ability to assess rare and structural variants. Next-generation sequencing (NGS) and long-read sequencing are promising technologies for the field of PGx research. Both NGS and long-read sequencing often provide more data and more options with regard to deciphering structural and rare variants compared to SNV panels-in particular, in regard to the number of variants that can be identified, as well as the option for haplotype phasing. Nonetheless, while useful for research, not all sequencing data can be applied to clinical practice yet. Ultimately, selecting the right technology is not a matter of fact but a matter of choosing the right technique for the right problem.

Indexed as

HaplotypesHigh-Throughput Nucleotide SequencingPharmacogeneticsPolymorphism, Single NucleotidePrecision MedicineHumansgenotypelong-read sequencingnext generation sequencingpharmacogenomicsphenotype

Identifiers

PMID33291630
PMCPMC7761897

What OpenQuestion holds

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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.