食品安全质量检测学报
食品安全質量檢測學報
식품안전질량검측학보
FOOD SAFETY AND QUALITY DETECTION TECHNOLOGY
2015年
1期
354-360
,共7页
丰伟刚%赵瑜%赵宗阁%洪建文%罗卓雅%尹利辉
豐偉剛%趙瑜%趙宗閣%洪建文%囉卓雅%尹利輝
봉위강%조유%조종각%홍건문%라탁아%윤리휘
大数据%生产质量监控系统%电子监管网%不良反应监测中心%药品监管大数据中心
大數據%生產質量鑑控繫統%電子鑑管網%不良反應鑑測中心%藥品鑑管大數據中心
대수거%생산질량감공계통%전자감관망%불량반응감측중심%약품감관대수거중심
big data%production quality control system%electronic supervision network%adverse drug reaction supervision center%big data center of drug supervision
本文概述了大数据的概念,讨论了利用大数据推进药品“智慧监管”的议题,为药品监管部门提高监管效率提供参考。从药品生产、流通、使用等环节系统分析了大数据在我国药品监管领域的应用现状。国家、省级药品监管、检验单位以及生产企业都在积极探索大数据在药品监管中的应用,出现了许多效果明显的实例,但大数据的建设和应用方面还存在诸多问题。针对这些问题,本文提出了相应的解决方案。药品监管部门需完善顶层设计,建设药品监管大数据中心,整合各系统资源,采用“合成作战”模式,同时加快相关法律法规及政策的出台,形成善用“大数据”成就药品智慧监管的新局面。
本文概述瞭大數據的概唸,討論瞭利用大數據推進藥品“智慧鑑管”的議題,為藥品鑑管部門提高鑑管效率提供參攷。從藥品生產、流通、使用等環節繫統分析瞭大數據在我國藥品鑑管領域的應用現狀。國傢、省級藥品鑑管、檢驗單位以及生產企業都在積極探索大數據在藥品鑑管中的應用,齣現瞭許多效果明顯的實例,但大數據的建設和應用方麵還存在諸多問題。針對這些問題,本文提齣瞭相應的解決方案。藥品鑑管部門需完善頂層設計,建設藥品鑑管大數據中心,整閤各繫統資源,採用“閤成作戰”模式,同時加快相關法律法規及政策的齣檯,形成善用“大數據”成就藥品智慧鑑管的新跼麵。
본문개술료대수거적개념,토론료이용대수거추진약품“지혜감관”적의제,위약품감관부문제고감관효솔제공삼고。종약품생산、류통、사용등배절계통분석료대수거재아국약품감관영역적응용현상。국가、성급약품감관、검험단위이급생산기업도재적겁탐색대수거재약품감관중적응용,출현료허다효과명현적실례,단대수거적건설화응용방면환존재제다문제。침대저사문제,본문제출료상응적해결방안。약품감관부문수완선정층설계,건설약품감관대수거중심,정합각계통자원,채용“합성작전”모식,동시가쾌상관법율법규급정책적출태,형성선용“대수거”성취약품지혜감관적신국면。
The article overviewed the concept of“big data”and the issues of using big data to promote drug smarter supervision, which provided a reference for improving the efficiency of supervision for the drug regulatory departments. The application of big data in the field of pharmaceutical regulation was analyzed from the links of production, circulation, and medication, etc. As national and provincial drug administrations, inspections and enterprises were actively exploring the application on drug supervision by using of the big data, there had been many good instances which showed obvious efficient. However, there were still a lot of problems on big-data construction and application. This article provided some appropriate suggestions of solutions. In conclusion, drug regulatory departments need to improve top-level design, build big-data centers for drug supervision, integrate various system resources, apply the “co-operations” mode, and accelerate the introduction of relevant laws and regulations. Finally a new situation of drug smarter regulation by using big data will be created.