약물유전학과 개인별 맞춤약물요법

Pharmacogenetics: A Principle for the Personalized Pharmacotherapy

  • 신재국 (인제대학교 의과대학 약리학교실 및 부산/일산백병원 임상약리센터)
  • Shin, Jae-Gook (Department of Phamacology, Inje University College of Medicine and Clinical Phamacology Center, Pusan/Ilsan Paik Hospital)
  • 발행 : 2002.06.30

초록

Individual variation in drug response is one of major issues in clinical practice and of a drug development. These variation can range from therapeutic failure to adverse or even fatal effects of drugs in some patients. The incidence of serious and fatal adverse drug reactions (ADRs) has been reported to be 6.7% and 0.32% of hospitalized patients in USA, respectively. The risk for therapeutic failure or toxicity of a drug in an individual patient is determined by the interaction of genes and environment. Environmental factors include drug-drug interactions, patient's age, weight, renal and liver dysfunction, or other disease factors or clinical variables such as smoking and alcohol consumption. Many of these environmental factors have long been considered in determining the individualized dose regimen in conventional pharmacotherapeutics. However, inherited individual variability of drug responses has been left as a so called 'idiosyncrasy' that are not predictable by physicians. Recently, the rapid development of pharmacogenetics/pharmacogenomics provide us extensive informations regarding on the genetic background on the wide inter-individual variation of drug responses, which is expected to lead to the era of personalized pharmacotherapy. Pharmacogenetics is a science that is interesting to the inherited variants of genes related to pharmacokinetics (drug metabolizing enzymes, drug transporters etc.) and pharmacodynamics (receptor, ion channel, target enzyme etc.), which are associated to the susceptibility of an individual to the higher risk of ADR or therapeutic failure. This review addresses the role of pharmacogenetics/pharmacogenomics in relation to wide interindividual variation of drug responses and to the possible contribution to the prediction of personalized pharmacotherapy.

키워드