Zhu Qian, Jiang Guoqian, Wang Liwei, Chute Christopher G
Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA.
Stud Health Technol Inform. 2013;192:1125.
Dozens of drug terminologies and resources capture the drug and/or drug class information, ranging from their coverage and adequacy of representation. No transformative ways are available to link them together in a standard way, which hinders data integration and data representation for drug-related clinical and translational studies. In this paper, we introduce our preliminary work for building a standardized drug and drug class network that integrates multiple drug terminological resources, using Anatomical Therapeutic Chemical (ATC) and National Drug File Reference Terminology (NDF-RT) as network backbone, and expanding with RxNorm and Structured Product Label (SPL). The network consists of 39,728 drugs and drug classes. We calculated and compared structure similarity for each drug/drug class pair from ATC and NDF-RT, and analyzed constructed drug class network from chemical structure perspective.
数十种药物术语和资源涵盖了药物和/或药物类别信息，其覆盖范围和表述的充分性各不相同。目前尚无变革性方法能够以标准方式将它们联系在一起，这阻碍了与药物相关的临床和转化研究的数据整合及数据呈现。在本文中，我们介绍了构建标准化药物和药物类别网络的初步工作，该网络整合了多种药物术语资源，以解剖学治疗学化学分类系统（ATC）和国家药品文件参考术语（NDF-RT）作为网络主干，并通过RxNorm和结构化产品标签（SPL）进行扩展。该网络由39,728种药物和药物类别组成。我们计算并比较了来自ATC和NDF-RT的每对药物/药物类别的结构相似性，并从化学结构角度分析了构建的药物类别网络。
