Title |
Applications of Immunopharmacogenomics: Predicting, Preventing, and Understanding Immune-Mediated Adverse Drug Reactions
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Published in |
Annual Review of Pharmacology & Toxicology, August 2018
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DOI | 10.1146/annurev-pharmtox-010818-021818 |
Pubmed ID | |
Authors |
Jason H Karnes, Matthew A Miller, Katie D White, Katherine C Konvinse, Rebecca K Pavlos, Alec J Redwood, Jonathan G Peter, Rannakoe Lehloenya, Simon A Mallal, Elizabeth J Phillips |
Abstract |
Adverse drug reactions (ADRs) are a significant health care burden. Immune-mediated adverse drug reactions (IM-ADRs) are responsible for one-fifth of ADRs but contribute a disproportionately high amount of that burden due to their severity. Variation in human leukocyte antigen (HLA) genes has emerged as a potential preprescription screening strategy for the prevention of previously unpredictable IM-ADRs. Immunopharmacogenomics combines the disciplines of immunogenomics and pharmacogenomics and focuses on the effects of immune-specific variation on drug disposition and IM-ADRs. In this review, we present the latest evidence for HLA associations with IM-ADRs, ongoing research into biological mechanisms of IM-ADRs, and the translation of clinical actionable biomarkers for IM-ADRs, with a focus on T cell-mediated ADRs. Expected final online publication date for the Annual Review of Pharmacology and Toxicology Volume 59 is January 6, 2019. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 36% |
Spain | 2 | 14% |
Sierra Leone | 1 | 7% |
Mexico | 1 | 7% |
France | 1 | 7% |
Bolivia, Plurinational State of | 1 | 7% |
Unknown | 3 | 21% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 9 | 64% |
Scientists | 4 | 29% |
Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 72 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 12 | 17% |
Researcher | 11 | 15% |
Other | 6 | 8% |
Student > Ph. D. Student | 5 | 7% |
Professor | 3 | 4% |
Other | 11 | 15% |
Unknown | 24 | 33% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 11 | 15% |
Biochemistry, Genetics and Molecular Biology | 9 | 13% |
Pharmacology, Toxicology and Pharmaceutical Science | 7 | 10% |
Immunology and Microbiology | 3 | 4% |
Computer Science | 2 | 3% |
Other | 10 | 14% |
Unknown | 30 | 42% |