ArticlePharmacogenomics and personalized medicine2011
Clinical application of high throughput molecular screening techniques for pharmacogenomics.
Article in Pharmacogenomics and personalized medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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.
Who cites it
9 citing papers in PubMed.
- Involvement of HLADQA1*05 in Patients with Inflammatory Bowel Disease Treated with Anti-TNF Drugs.Medicina (Kaunas, Lithuania) · 2025Article
- WGS Data Collections: How Do Genomic Databases Transform Medicine?International journal of molecular sciences · 2023Review
- A Robust and Fast/Multiplex Pharmacogenetics Assay to Simultaneously Analyze 17 Clinically Relevant Genetic Polymorphisms inPharmaceuticals (Basel, Switzerland) · 2022Article
- PharmFrag: An Easy and Fast Multiplex Pharmacogenetics Assay to Simultaneously Analyze 9 Genetic Polymorphisms Involved in Response Variability of Anticancer Drugs.International journal of molecular sciences · 2020Article
- Pharmacogenetic testing revisited: 5' nuclease real-time polymerase chain reaction test panels for genotypingPharmacogenomics and personalized medicine · 2017Article
- Genomic sequencing in clinical practice: applications, challenges, and opportunities.Dialogues in clinical neuroscience · 2016Review
- A survey of tools for the analysis of quantitative PCR (qPCR) data.Biomolecular detection and quantification · 2014Review
- Management of incidental findings in clinical genomic sequencing.Current protocols in human genetics · 2013Article
- Pharmacogenetics, pharmacogenomics and ayurgenomics for personalized medicine: a paradigm shift.Indian journal of pharmaceutical sciencesReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genetic analysis is one of the fastest-growing areas of clinical diagnostics. Fortunately, as our knowledge of clinically relevant genetic variants rapidly expands, so does our ability to detect these variants in patient samples. Increasing demand for genetic information may necessitate the use of high throughput diagnostic methods as part of clinically validated testing. Here we provide a general overview of our current and near-future abilities to perform large-scale genetic testing in the clinical laboratory. First we review in detail molecular methods used for high throughput mutation detection, including techniques able to monitor thousands of genetic variants for a single patient or to genotype a single genetic variant for thousands of patients simultaneously. These methods are analyzed in the context of pharmacogenomic testing in the clinical laboratories, with a focus on tests that are currently validated as well as those that hold strong promise for widespread clinical application in the near future. We further discuss the unique economic and clinical challenges posed by pharmacogenomic markers. Our ability to detect genetic variants frequently outstrips our ability to accurately interpret them in a clinical context, carrying implications both for test development and introduction into patient management algorithms. These complexities must be taken into account prior to the introduction of any pharmacogenomic biomarker into routine clinical testing.
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Registered trials
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.