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Pharmacogenomics (a portmanteau of pharmacology and genomics) is the technology that analyses how genetic makeup affects an individual's response to drugs.[1] It deals with the influence of genetic variation on drug response in patients by correlating gene expression or single-nucleotide polymorphisms with a drug's efficacy or toxicity.[2] By doing so, pharmacogenomics aims to develop rational means to optimize drug therapy, with respect to the patients' genotype, to ensure maximum efficacy with minimal adverse effects.[3] Such approaches promise the advent of "personalized medicine"; in which drugs and drug combinations are optimized for each individual's unique genetic makeup.[4][5]

Drug metabolism

There are several known genes which are largely responsible for variances in drug metabolism and response. The most common are the cytochrome P450 (CYP) genes, which encode enzymes that influence the metabolism of more than 80 percent of current prescription drugs.[6][7] Codeine, clopidogrel, tamoxifen, and warfarin are examples of medications that follow this metabolic pathway. Patient genotypes are usually categorized into predicted phenotypes. For example, if a person receives one *1 allele each from mother and father to code for the CYP2D6 gene, then that person is considered to have an extensive metabolizer (EM) phenotype. An extensive metabolizer is considered normal. Other CYP metabolism phenotypes include: intermediate, ultra-rapid, and poor. In theory, each phenotype is based upon the allelic variation within the individual genotype. However, several genetic events can influence a same phenotypic trait, and establishing genotype-to-phenotype relationships can thus be far from consensual with many enzymatic patterns. For instance, the influence of the CYP2D6*1/*4 allelic variant on the clinical outcome in patients treated with Tamoxifen remains debated today. In oncology, genes coding for DPD, UGT1A1, TPMT, CDA involved in the pharmacokinetics of 5-FU/capecitabine, irinotecan, 6-mercaptopurine and gemcitabine/cytarabine, respectively, have all been described as being highly polymorphic. A strong body of evidence suggests that patients affected by these genetic polymorphisms will experience severe/lethal toxicities upon drug intake, and that pre-therapeutic screening does help to reduce the risk of treatment-related toxicities through adaptive dosing strategies.[8]


Pharmacogenomics has applications in illnesses like cancer, cardiovascular disorders, depression, bipolar disorder, attention deficit disorders, HIV, tuberculosis, asthma, and diabetes.

In cancer treatment, pharmacogenomics tests are used to identify which patients are most likely to respond to certain cancer drugs. In behavioral health, pharmacogenomic tests provide tools for physicians and care givers to better manage medication selection and side effect amelioration. Pharmacogenomics is also known as companion diagnostics, meaning tests being bundled with drugs. Examples include KRAS test with cetuximab and EGFR test with gefitinib. Beside efficacy, germline pharmacogenetics can help to identify patients likely to undergo severe toxicities when given cytotoxics showing impaired detoxification in relation with genetic polymorphism, such as canonical 5-FU.[9]

In cardio vascular disorders, the main concern is response to drugs including warfarin, clopidogrel, beta blockers, and statins.

Many people take medications called SSRIs, or selective serotonin reuptake inhibitors, for different psychiatric disorders. Many of the medications are metabolized by CYP450 enzymes, including fluoxetine, paroxetine, and citalopram.

See also


  1. Ermak G., Modern Science & Future Medicine (second edition), 164 p., 2013
  2. Wang L (2010). Pharmacogenomics: a systems approach. Wiley Interdiscip Rev Syst Biol Med 2 (1): 3–22.
  3. Becquemont L (June 2009). Pharmacogenomics of adverse drug reactions: practical applications and perspectives. Pharmacogenomics 10 (6): 961–9.
  4. (2005). Guidance for Industry Pharmacogenomic Data Submissions. (PDF) U.S. Food and Drug Administration. URL accessed on 2008-08-27.
  5. Squassina A, Manchia M, Manolopoulos VG, Artac M, Lappa-Manakou C, Karkabouna S, Mitropoulos K, Del Zompo M, Patrinos GP (August 2010). Realities and expectations of pharmacogenomics and personalized medicine: impact of translating genetic knowledge into clinical practice. Pharmacogenomics 11 (8): 1149–67.
  6. Hart SN, Wang S, Nakamoto K, Wesselman C, Li Y, Zhong XB (January 2008). Genetic polymorphisms in cytochrome P450 oxidoreductase influence microsomal P450-catalyzed drug metabolism. Pharmacogenet. Genomics 18 (1): 11–24.
  7. Gomes AM, Winter S, Klein K, Turpeinen M, Schaeffeler E, Schwab M, Zanger UM (April 2009). Pharmacogenomics of human liver cytochrome P450 oxidoreductase: multifactorial analysis and impact on microsomal drug oxidation. Pharmacogenomics 10 (4): 579–99.
  8. Lee SY, McLeod HL (January 2011). Pharmacogenetic tests in cancer chemotherapy: what physicians should know for clinical application.. J Pathol 223 (1): 15–27.
  9. Ciccolini J, Gross E, Dahan L, Lacarelle B, Mercier C (October 2010). Routine dihydropyrimidine dehydrogenase testing for anticipating 5-fluorouracil-related severe toxicities: hype or hope?. Clin Colorectal Cancer 9 (4): 224–8.

Further reading

External links


Genomics topics
Genome project | Glycomics | Human Genome Project | Proteomics
Chemogenomics | Structural genomics | Pharmacogenetics | Pharmacogenomics | Toxicogenomics
Bioinformatics | Cheminformatics | Systems biology
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