− この都医学研セミナーは終了しました。 −
Prof. Doo-Sup Choi
Pharmacology and Psychiatry, Samuel C. Johnson Genomics of Addiction Program, Mayo Clinic College of Medicine
|会場||東京都医学総合研究所 2階 講堂|
|世話人||池田 和隆 （精神行動医学研究分野 依存性薬物プロジェクト 参事研究員）|
Following the FDA approval of acamprosate for treatment of alcohol use disorder (AUD) in 2004 in the US, no new medications has approved for the AUD. Given the heterogeneous nature of AUD, it not surprising that the three principle FDA-approved medications, disulfram, naltrexone and acamprosate exhibit limited and variable efficacy. Several new medications are being tested from early research-based clinical trials, which may lead to add 1-2 medications in the clinical practice in the near future. While clinical community expect an increased efficacy along with other AUD-related mood improvements, it may not replace three existing medications, nor substantially overcome the limited efficacy because of diverse biological and psychological etiological backgrounds of patients who seek treatment. On the other hand, recent development of pharmaco-omics enable use to identify various biomarkers associated with drug responses. Especially, genomics and metabolomics-based biomarkers are being investigated to increase predictability of drug responses in several disorders, which may be applicable for the existing medications as well as new medications in the future. Furthermore, the combination of novel biomarkers and expanded clinical variables may permit the more precise and personalized treatment of patients with AUD. The goal of personalized medicine is to identify a single or group of measurable biological factors that are capable of identifying which patients have the highest likelihood of responding to a particular treatment intervention. Personalized medicine in AUD is still at its early stages but has first focused on pharmacogenomics biomarkers of treatment response. In my presentation, I will highlight the importance of identification of biomarkers and the development of predictive models that are capable of predicting therapeutic response to pharmacological agents for treatment of AUD could help physicians to determine which medication to prescribe for individual AUD patients, enabling personalized medicine in AUD.