ReviewPharmacology & therapeutics2017
Personalized medicine: Genetic risk prediction of drug response.
Review in Pharmacology & therapeutics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 19 papers.
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.
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
19 citing papers in PubMed, 71 citations in OpenAlex.
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- Precision oncology: Computational methods for multi-omics data integration to improve drug response prediction.Cambridge prisms. Precision medicine · 2025Review
- The Use of AI for Phenotype-Genotype Mapping.Methods in molecular biology (Clifton, N.J.) · 2025Article
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- Unlocking Genetic Profiles with a Programmable DNA-Powered Decoding Circuit.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Maturing pharmacogenomic factors deliver improvements and cost efficiencies.Cambridge prisms. Precision medicine · 2023Review
- Development of the pharmacogenomics and genomics literacy framework for pharmacists.Human genomics · 2021Article
- Role of Environmental Genetics in Preventive Medicine: An Interview with Daniel W. Nebert, MS, MD.The Yale journal of biology and medicine · 2021Article
- Direct-to-Consumer Nutrigenetics Testing: An Overview.Nutrients · 2020Review
- Impact of Polypharmacy on Candidate Biomarker miRNomes for the Diagnosis of Fibromyalgia and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Striking Back on Treatments.Pharmaceutics · 2019Article
- Pharmacogenetics of asparaginase in acute lymphoblastic leukemia.Cancer drug resistance (Alhambra, Calif.) · 2019Review
- Needles, Haystacks and Next-Generation Genetic Sequencing.Health matrix (Cleveland, Ohio : 1991) · 2018Article
- Perspective on the Genetic Response to Antiparasitics: A Review Article.Iranian journal of parasitologyReview
Corrections and comments
- Erratum issued
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
Pharmacogenomics (PGx), a substantial component of "personalized medicine", seeks to understand each individual's genetic composition to optimize drug therapy -- maximizing beneficial drug response, while minimizing adverse drug reactions (ADRs). Drug responses are highly variable because innumerable factors contribute to ultimate phenotypic outcomes. Recent genome-wide PGx studies have provided some insight into genetic basis of variability in drug response. These can be grouped into three categories. [a] Monogenic (Mendelian) traits include early examples mostly of inherited disorders, and some severe (idiosyncratic) ADRs typically influenced by single rare coding variants. [b] Predominantly oligogenic traits represent variation largely influenced by a small number of major pharmacokinetic or pharmacodynamic genes. [c] Complex PGx traits resemble most multifactorial quantitative traits -- influenced by numerous small-effect variants, together with epigenetic effects and environmental factors. Prediction of monogenic drug responses is relatively simple, involving detection of underlying mutations; due to rarity of these events and incomplete penetrance, however, prospective tests based on genotype will have high false-positive rates, plus pharmacoeconomics will require justification. Prediction of predominantly oligogenic traits is slowly improving. Although a substantial fraction of variation can be explained by limited numbers of large-effect genetic variants, uncertainty in successful predictions and overall cost-benefit ratios will make such tests elusive for everyday clinical use. Prediction of complex PGx traits is almost impossible in the foreseeable future. Genome-wide association studies of large cohorts will continue to discover relevant genetic variants; however, these small-effect variants, combined, explain only a small fraction of phenotypic variance -- thus having limited predictive power and clinical utility.
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What OpenQuestion holds
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.