The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Pharmacogenetics/genomics and personalized medicine
Abstract
Despite the marked advances in drug therapy, some patients do not respond favorably or suffer severe adverse drug effects. Pharmacogenetic studies have shown that polymorphisms of drug metabolizing enzymes, transporters and receptors contribute to variable drug response. Owing to the complexity of drug actions, a broader genomics approach aims at finding new drug targets and optimizing therapy for the individual patient. However, pharmacogenomics has made only a few inroads into clinical practice to date. This review evaluates obstacles that need to be overcome. These include the complexity of mechanisms underlying drug response, given singly or in combination, uncertainty about the genetic underpinnings of complex diseases, such as cancer, diabetes, cardiovascular and mental disorders and a lack of quantitative understanding of the scope of genetic variations, even for well-studied genes. By resolving these hurdles, pharmacogenomics will yield significant, but incremental, therapeutic advances paving the way towards personalized health care.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Slamon, D. J., Leyland-Jones, B., Shak, S., Fuchs, H., Paton, V., Bajamonde, A., Fleming, T., Eiermann, W., Wolter, J., Pegram, M., et al. (2001) · New England Journal of Medicine · doi:10.1056/nejm200103153441101 · Cited by 11,500
Lynch, T. J., Bell, D. W., Sordella, R., Gurubhagavatula, S., Okimoto, R. A., Brannigan, B. W., Harris, P. L., Haserlat, S. M., Supko, J. G., Haluska, F. G., et al. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa040938 · Cited by 11,486
Allelic Variation of Human Serotonin Transporter Gene Expression
Heils, A., Teufel, A., Petri, S., Stöber, G., Riederer, P., Bengel, D., & Lesch, K. P. (1996) · Journal of Neurochemistry · doi:10.1046/j.1471-4159.1996.66062621.x · Cited by 2,221
Metastable epialleles in mammals
Rakyan, V. K., Blewitt, M. E., Druker, R., Preis, J. I., & Whitelaw, E. (2002) · Trends in Genetics · doi:10.1016/s0168-9525(02)02709-9 · Cited by 499
Polymorphisms affecting gene regulation and mRNA processing: Broad implications for pharmacogenetics
JOHNSON, A., WANG, D., & SADEE, W. (2005) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2004.11.001 · Cited by 97
Cited by
Nanotheranostics for personalized medicine
Mura, S., & Couvreur, P. (2012) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2012.06.006 · Cited by 527
Mannermaa, E., Vellonen, K.-S., & Urtti, A. (2006) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2006.07.024 · Cited by 349
Recent Advances in light-responsive on-demand drug-delivery Systems
Linsley, C. S., & Wu, B. M. (2017) · Therapeutic Delivery · doi:10.4155/tde-2016-0060 · Cited by 265
3D printed medicines: A new branch of digital healthcare
Awad, A., Trenfield, S. J., Gaisford, S., & Basit, A. W. (2018) · International Journal of Pharmaceutics · doi:10.1016/j.ijpharm.2018.07.024 · Cited by 265
Genetic and epigenetic sex-specific adaptations to endurance exercise
Landen, S., Voisin, S., Craig, J. M., McGee, S. L., Lamon, S., & Eynon, N. (2019) · Epigenetics · doi:10.1080/15592294.2019.1603961 · Cited by 76
Metadata
- Authors
- Sadée, W., & Dai, Z.
- Venue
- Human Molecular Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-10-15
- Volume
- 14
- Issue
- suppl_2
- Pages
- R207-R214
- ISSN
- 0964-6906 (ISSN-L)
- 1460-2083
- OpenAlex
- W2147549027
- Cited by
- 227
- References
- 5
- FWCI
- 11.78
- Type
- journal article
- Language
- en
- Open access
- closed
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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Pharmacogenetics/genomics and personalized medicine. https://app.cochat.ai/papers/10.1093/hmg/ddi261
- The paper
- Sadée, W., & Dai, Z. (2005). Pharmacogenetics/genomics and personalized medicine. Human Molecular Genetics. https://doi.org/10.1093/hmg/ddi261
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.