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Omics and Drug Response
Abstract
A new generation of technologies commonly named omics permits assessment of the entirety of the components of biological systems and produces an explosion of data and a major shift in our concepts of disease. These technologies will likely shape the future of health care. One aspect of these advances is that the data generated document the uniqueness of each human being in regard to disease risk and treatment response. These developments have reemphasized the concept of personalized medicine. Here we review the impact of omics technologies on one key aspect of personalized medicine: the individual drug response. We describe how knowledge of different omics may affect treatment decisions, namely drug choice and drug dose, and how it can be used to improve clinical outcomes.
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Metadata
- Authors
- Meyer, U. A., Zanger, U. M., & Schwab, M.
- Affiliations
- University of Basel (CH)
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology (DE)
- Universitätsklinikum Tübingen (DE)
- Venue
- Annual Review of Pharmacology and Toxicology
- Publisher
- Annual Reviews
- Published
- 2013-01-06
- Volume
- 53
- Issue
- 1
- Pages
- 475-502
- ISSN
- 0362-1642 (ISSN-L)
- 1545-4304
- OpenAlex
- W2098156682
- Cited by
- 157
- References
- 196
- Citations by year
- 2026: 3 · 2025: 9 · 2024: 6 · 2023: 5 · 2022: 10 · 2021: 5 · 2020: 12 · 2019: 17 · 2018: 10 · 2017: 15 · 2016: 12 · 2015: 17 · 2014: 17 · 2013: 14
- FWCI
- 1.58
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Annual Review of Pharmacology and Toxicology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Robert Bosch Stiftung
- Bundesministerium für Bildung und Forschung
- National Institutes of Health
- National Human Genome Research Institute
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Keywords
- omics technologies, drug response, personalized medicine, pharmacogenomics, drug selection, drug dosing, treatment response variability, clinical outcomes, precision medicine
- MeSH terms
- Animals, Humans, Pharmacogenetics, Genomics, Precision Medicine
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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