He Yongqun
Unit for Laboratory Animal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA. Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI 48109, USA. Center for Computational Medicine and Biology, University of Michigan Medical School, Ann Arbor, MI 48109, USA. Comprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
Curr Pharmacol Rep. 2016 Jun;2(3):113-128. doi: 10.1007/s40495-016-0055-0. Epub 2016 Mar 11.
Compared with controlled terminologies (, MedDRA, CTCAE, and WHO-ART), the community-based Ontology of AEs (OAE) has many advantages in adverse event (AE) classifications. The OAE-derived Ontology of Vaccine AEs (OVAE) and Ontology of Drug Neuropathy AEs (ODNAE) serve as AE knowledge bases and support data integration and analysis. The Immune Response Gene Network Theory explains molecular mechanisms of vaccine-related AEs. The OneNet Theory of Life treats the whole process of a life of an organism as a single complex and dynamic network (, OneNet). A new "OneNet effectiveness" tenet is proposed here to expand the OneNet theory. Derived from the OneNet theory, the author hypothesizes that one human uses one single genotype-rooted mechanism to respond to different vaccinations and drug treatments, and experimentally identified mechanisms are manifestations of the OneNet blueprint mechanism under specific conditions. The theories and ontologies interact together as semantic frameworks to support integrative pharmacovigilance research.
与受控术语(如MedDRA、CTCAE和WHO-ART)相比,基于社区的不良事件本体(OAE)在不良事件(AE)分类方面具有许多优势。源自OAE的疫苗不良事件本体(OVAE)和药物神经病变不良事件本体(ODNAE)作为AE知识库,并支持数据整合与分析。免疫反应基因网络理论解释了疫苗相关AE的分子机制。生命的OneNet理论将生物体生命的全过程视为一个单一的复杂动态网络(即OneNet)。在此提出了一个新的“OneNet有效性”原则以扩展OneNet理论。作者从OneNet理论推导得出,假设一个人使用一种单一的基因型根源机制来应对不同的疫苗接种和药物治疗,并且实验确定的机制是特定条件下OneNet蓝图机制的表现形式。这些理论和本体作为语义框架相互作用,以支持综合药物警戒研究。