Qing Zhu1, Jing Ding1, Wenxia Ren1, Yangdui Mao1, Wen Wang2. 1. Zhejiang Pharmaceutical College, Ningbo, 15100. 2. Center for Medical Device Evaluation in Zhejiang Province, Hangzhou, 311100.
Abstract
OBJECTIVE: To modify the monitoring process and means of adverse events in vitro diagnostic reagents,improve the quantity and quality of adverse events reported in vitro,and reduce the workload of regulatory authorities,eventually ensure the safety and effectiveness of in vitro diagnostic reagents. METHODS: The pre-filtering risk assessment system based on BP neural network was used to evaluate the adverse events of in vitro diagnostic reagents.According to the evaluation results,the administrative supervision departments took corresponding countermeasures. RESULTS: The BP neural network learned the historical data,and the risk evaluation results of the adverse events were basically consistent with the expert group. CONCLUSIONS: BP neural network can be used to evaluate the risk of adverse events and achieve risk signal aggregation of adverse events.
OBJECTIVE: To modify the monitoring process and means of adverse events in vitro diagnostic reagents,improve the quantity and quality of adverse events reported in vitro,and reduce the workload of regulatory authorities,eventually ensure the safety and effectiveness of in vitro diagnostic reagents. METHODS: The pre-filtering risk assessment system based on BP neural network was used to evaluate the adverse events of in vitro diagnostic reagents.According to the evaluation results,the administrative supervision departments took corresponding countermeasures. RESULTS: The BP neural network learned the historical data,and the risk evaluation results of the adverse events were basically consistent with the expert group. CONCLUSIONS:BP neural network can be used to evaluate the risk of adverse events and achieve risk signal aggregation of adverse events.
Entities:
Keywords:
BP neural network; adverse events; in vitro diagnostic reagents; pre-filtering; risk assessment