Pharmacogenomics

For the journal, see Pharmacogenomics (journal).
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Pharmacogenomics, often abbreviated "PGx," is the study of the role of the genome in drug response. Its name (pharmaco- + genomics) reflects its combining of pharmacology and genomics. Pharmacogenomics analyzes how the genetic makeup of a patient affects their response to drugs.[1] It deals with the influence of acquired and inherited genetic variation on drug response, by correlating DNA mutations (including point mutations, copy number variations, and structural variations) with pharmacokinetic (drug absorption, distribution, metabolism, and elimination), pharmacodynamic (effects mediated through a drug's biological targets), and/or immunogenic endpoints.[2][3][4]

Pharmacogenomics aims to develop rational means to optimize drug therapy, with regard to the patients' genotype, to achieve maximum efficiency with minimal adverse effects.[5] It is hoped that by using pharmacogenomics, pharmaceutical drug treatments can deviate from what is dubbed as the "one-dose-fits-all" approach. Pharmacogenomics also attempts to eliminate trial-and-error in prescribing, allowing physicians to take into consideration their patient's genes, the functionality of these genes, and how this may affect the effectiveness of the patient's current or future treatments (and where applicable, provide an explanation for the failure of past treatments).[6][7] Such approaches promise the advent of precision medicine and even personalized medicine, in which drugs and drug combinations are optimized for narrow subsets of patients or even for each individual's unique genetic makeup.[8][9]

Whether used to explain a patient's response (or lack of it) to a treatment, or to act as a predictive tool, it hopes to achieve better treatment outcomes and greater efficacy, and reduce drug toxicities and adverse drug reactions (ADRs). For patients who do not respond to a treatment, alternative therapies can be prescribed that would best suit their requirements. In order to provide pharmacogenomic recommendations for a given drug, two possible types of input can be used: genotyping, or exome or whole genome sequencing.[10] Sequencing provides many more data points, including detection of mutations that prematurely terminate the synthesized protein (early stop codon).[10]

  1. ^ Ermak G (2015). Emerging Medical Technologies. World Scientific. ISBN 978-981-4675-80-2.
  2. ^ Johnson JA (November 2003). "Pharmacogenetics: potential for individualized drug therapy through genetics". Trends in Genetics. 19 (11): 660–666. doi:10.1016/j.tig.2003.09.008. PMID 14585618. S2CID 15195039.
  3. ^ "Center for Pharmacogenomics and Individualized Therapy". Unc Eshelman School of Pharmacy. Retrieved 2014-06-25.
  4. ^ "overview of pharmacogenomics". Up-to-Date. May 16, 2014. Retrieved 2014-06-25.
  5. ^ Becquemont L (June 2009). "Pharmacogenomics of adverse drug reactions: practical applications and perspectives". Pharmacogenomics. 10 (6): 961–969. doi:10.2217/pgs.09.37. PMID 19530963.
  6. ^ Sheffield LJ, Phillimore HE (May 2009). "Clinical use of pharmacogenomic tests in 2009". The Clinical Biochemist. Reviews. 30 (2): 55–65. PMC 2702214. PMID 19565025.
  7. ^ Hauser AS, Chavali S, Masuho I, Jahn LJ, Martemyanov KA, Gloriam DE, Babu MM (January 2018). "Pharmacogenomics of GPCR Drug Targets". Cell. 172 (1–2): 41–54.e19. doi:10.1016/j.cell.2017.11.033. PMC 5766829. PMID 29249361.
  8. ^ "Guidance for Industry Pharmacogenomic Data Submissions" (PDF). U.S. Food and Drug Administration. March 2005. Retrieved 2008-08-27.
  9. ^ Squassina A, Manchia M, Manolopoulos VG, Artac M, Lappa-Manakou C, Karkabouna S, et al. (August 2010). "Realities and expectations of pharmacogenomics and personalized medicine: impact of translating genetic knowledge into clinical practice". Pharmacogenomics. 11 (8): 1149–1167. doi:10.2217/pgs.10.97. PMID 20712531.
  10. ^ a b Huser V, Cimino JJ (2013). "Providing pharmacogenomics clinical decision support using whole genome sequencing data as input". AMIA Joint Summits on Translational Science Proceedings. AMIA Joint Summits on Translational Science. 2013: 81. PMID 24303303.