Investigation of risk factors related with drug adverse events using Biobank Japan data

DOI
  • SAMESHIMA Tomoya
    Drug Safety Research and Evaluation, Preclinical and Translational Sciences, Research, Takeda Pharmaceutical Company Limited
  • YAMANAKA Kazunori
    Drug Safety Research and Evaluation, Preclinical and Translational Sciences, Research, Takeda Pharmaceutical Company Limited
  • KOIDO Masaru
    Graduate School of Frontier Science, The University of Tokyo
  • HARA Hideto
    Drug Safety Research and Evaluation, Preclinical and Translational Sciences, Research, Takeda Pharmaceutical Company Limited
  • HASEGAWA Miyuki
    Safety Management, Global Patient Safety Evaluation Japan, Takeda Development Center Japan, Takeda Pharmaceutical Company Limited
  • NARII Nobuhiro
    Safety Management, Global Patient Safety Evaluation Japan, Takeda Development Center Japan, Takeda Pharmaceutical Company Limited
  • SAKAGUCHI Motonobu
    Safety Management, Global Patient Safety Evaluation Japan, Takeda Development Center Japan, Takeda Pharmaceutical Company Limited
  • MATSUDA Koichi
    Graduate School of Frontier Science, The University of Tokyo
  • KAMATANI Yoichiro
    Graduate School of Frontier Science, The University of Tokyo
  • SHINOZAWA Tadahiro
    Drug Safety Research and Evaluation, Preclinical and Translational Sciences, Research, Takeda Pharmaceutical Company Limited

Bibliographic Information

Other Title
  • バイオバンクジャパンデータを利用した薬剤の副作用につながるリスク因子の探索

Abstract

<p>Predicting clinical adverse events (AEs) in preclinical studies is one of the most important challenges in drug discovery. Clinical AEs are caused not only by drug properties but also by genetic and environmental background of each patient. Therefore, nevertheless toxicities were not observed in preclinical studies, safety measures are sometimes taken in clinical trials and post-marketing. Identification of risk factors that lead to specific AEs in patients are expected to identify populations with safety risk for drug treatment, thus leading to more rapid planning and implementation of safety measures. In addition, it could be possible to develop preclinical models that incorporate these risk factors and utilize them to discover drugs without safety concerns prior to clinical studies. To explore risk factors for such patients, utilization of real-world data, that is clinical information from actual sites where drugs are used, is a promising approach. To this end, we utilize data of Biobank Japan (BBJ), which is one of the largest biobanks in Japan including information of around 270,000 patients. By using BBJ, we can access not only to clinical information such as medial and prescription history, but also to genomic information including about 900,000 single nucleotide polymorphisms (SNPs). In this symposium, we will introduce our joint research activity with BBJ and discuss how to utilize biobank data to identify risk factors for adverse events from the perspective of genetics and pharmacoepidemiology.</p>

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