摘要
目的:通过分析全国药物临床试验机构备案和试验承接现状,探索新备案机构的发展策略和方向。方法:以2021年12月31日前进行药物临床试验备案的医疗机构为研究对象,汇总其2020年1月1日至2021年12月31日期间登记的药物临床试验,从多个维度分析备案机构数量变化趋势及临床试验开展现状。结果:自备案制度实施至2021年底,共有270家新备案机构完成备案,占总备案机构数量的23.6%。然而,仅有不到10%的临床试验选择在新备案机构开展,且新备案机构的备案专业与临床试验需求存在供需失衡的情况。结论:药物临床试验机构备案管理的实施有效地促进了医疗和临床试验资源的释放,但新备案机构整体利用度仍有较大提升空间。新备案机构可从提升自身能力、调整专业发展策略等方向提高新备案机构的认知度、利用度,推动我国临床研究产业持续发展。
Objectives:By analyzing the registration status and the implementation of clinical trials in drug clinical trial institutions,this paper aims to explore the development strategy and direction of newly registered institutions.Methods:Taking drug clinical trial institutions registered before 31 December 2021 as the study subjects,this paper analyzed their drug clinical trials registered from January 1,2020 to December 31,2021.The trend of the number of registered institutions and the status of clinical trials were analyzed from various aspects.Results:Since the implementation of the clinical trial institution registration system,there are a total of 270 newly registered institutions,accounting for 23.6%of the total number of institutions.However,only less than 10%of clinical trials were conducted at newly registered institutions,and there was an imbalance between the new institution supply and clinical trial demand.Conclusion:The implementation of registration system has effectively promoted the release of medical and clinical trial resources,but the overall utilization rate of newly registered institutions still has much room for improvement.New institutions can increase their recognition and utilization by enhancing their own capabilities and adjusting specialty development strategies to promote the sustainable development of clinical research industry in China.
作者
石真玉
霍乐淳
周姚
张庆
SHI Zhen-yu;HUO Le-chun;ZHOU Yao;ZHANG Qing(Center of Clinical Operations Excellence,IQVIA RDS(Shanghai)Co.,Ltd.;China Pharmaceutical University)
出处
《中国食品药品监管》
2023年第3期50-57,共8页
China Food & Drug Administration Magazine
关键词
药物研发
临床试验
机构建设
数据分析
drug development
clinical trial
institutional development
data analysis