退化过程建模及药品货架寿命预测
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摘要
药品货架寿命的有效预测是药品安全管理的关键问题。针对传统的退化过程建模不能考虑同批产品中个体差异的问题,提出一种有效融合先验退化数据和现场退化数据的方法,可对单片药品及新药品进行货架寿命预测。依据先验信息确定模型的参数,引入Bayes融合现场退化数据进行参数更新,在此基础上对单片药品进行货架寿命预测。结果表明,瓶装和片装的五号药片的货架寿命预测值分别为43.95周和47.47周,与试验值的相对误差分别为0.043和0.051。验证了利用融合现场退化数据对单片药品及新药品货架寿命预测方法的可行性。
The shelf life prediction of drug is the key problem of drug safety management. To solve the problem of individual difference in the same batch cannot be considered during the traditional degradation process modeling, an effective method is proposed to fuse priori degenerate data with site degraded data which can predict shelf life for the monolithic drug and new drugs. Determining the distribution of model parameters based on prior information, fusion of field data to update parameters by Bayes. On this basis, predict the shelf life of the monolithic drug. The results show that the No.5 loaded and bottled drugs' shelf life predicted values are 43.95 and 47.47 weeks. The relative errors are 0.043 and 0.051. And the feasibility of fusing degradation data to predict the shelf life of the monolithic drug and new drugs is verified.
The shelf life prediction of drug is the key problem of drug safety management. To solve the problem of individual difference in the same batch cannot be considered during the traditional degradation process modeling, an effective method is proposed to fuse priori degenerate data with site degraded data which can predict shelf life for the monolithic drug and new drugs. Determining the distribution of model parameters based on prior information, fusion of field data to update parameters by Bayes. On this basis, predict the shelf life of the monolithic drug. The results show that the No.5 loaded and bottled drugs' shelf life predicted values are 43.95 and 47.47 weeks. The relative errors are 0.043 and 0.051. And the feasibility of fusing degradation data to predict the shelf life of the monolithic drug and new drugs is verified.
引文
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[14] 邱荣华, 巨孔亮, 董友耕,等. 基于性能退化的小子样电主轴可靠性试验研究[J]. 中国机械工程, 2016, 27(20):2738.
[15] 晁代宏,马静,陈淑英. 应用多元性能退化量评估光纤陀螺贮存的可靠性[J]. 光学精密工程,2011(1):35.
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[20] SHAO J. and CHOW S.C. Constructing Release Targets for Drug Products:A Bayesian Decision Theory Approach[J]. Journal of the Royal Statistical Society, 1991,40(3):381.
[2] 林丽花. 强化病区高危药品安全管理的效果观察[J]. 中国药物经济学,2016,11(8):191.
[3] 郭建英,孙永全,于晓洋. 可靠性增长技术发展动态诠释[J]. 哈尔滨理工大学学报,2011,16(2):1.
[4] 朱显辉,师楠,田德文,等. PWM驱动电机可靠性研究发展及展望[J]. 哈尔滨理工大学学报, 2014,19(4):22.
[5] 胡姚刚,李辉,廖兴林,等. 风电轴承性能退化建模及其实时剩余寿命预测[J]. 中国电机工程学报,2016,20(6):1643.
[6] FREITAS M A,DE TOLEDO M LG,Colosimo E A. Using Degradation Data to Assess Reliability:A Case Study on Train Wheel Degradation[J]. Quality and Reliability Engineering International,2009,25(5):607.
[7] 周月阁,叶雪荣,翟国富. 基于性能退化和Monte-Carlo仿真的系统性能可靠性评估[J]. 仪器仪表学报,2014(5):1185.
[8] XU A.,TANG Y. Objective Bayesian Analysis for Linear Degradationmodels[J]. Communications in Statistics-Theory and Methods,2012,41(21):4034.
[9] GEBRAEEL N Z,LAWLEY M A,Rong L,Jennifer K. Residual-Life Distributions from Component Degradation Signals:A Bayesian Approach[J].IIE Transactions, 2005, 37(6): 543.
[10] GEBRAEEL N. Sesory-updated Residual Life Distributions for Components with Exponential Degradation Patterns[J]. IEEE Transactions on Automation Science and Engineering,2006,3(4):382.
[11] ELWANY A.,GEBRAEEL N.Real-time Estimation of Mean Remaining Life Using Sensor-based Degradation Models[J].Journal of Manufacturing Science and Engineering,2009,131(5):51.
[12] KAISER K A,GEBRAEEL N Z. Predictive Maintenance Management Using Sensor Degration Models[J].IEEE Transaction on Systems,Man and Cybernetics,Part A:Systems and Humans,2009,39(4):840.
[13] CHEN N.,TSUI K.L. Condition Monitoring and Remaining Useful Life Prediction Using Degration Signals:Revisited[J]. IIE Transactions,2013,45(9):939.
[14] 邱荣华, 巨孔亮, 董友耕,等. 基于性能退化的小子样电主轴可靠性试验研究[J]. 中国机械工程, 2016, 27(20):2738.
[15] 晁代宏,马静,陈淑英. 应用多元性能退化量评估光纤陀螺贮存的可靠性[J]. 光学精密工程,2011(1):35.
[16] 蔡忠义, 陈云翔, 张诤敏,等. 基于比例失效率退化模型的可靠性评估方法[J]. 系统工程与电子技术, 2015, 37(8):1943.
[17] 王华伟,高军,吴海桥. 基于Bayes模型平均的航空发动机可靠性分析[J]. 航空动力学报,2014(2):305.
[18] 彭宝华,周经伦,潘正强. Wiener过程性能退化产品可靠性评估的Bayes方法[J]. 系统工程理论与实践, 2010(3): 543.
[19] 王笑琴. 常温保存的药品存放于冷藏处对药效的影响[J]. 医疗装备,2016(18):112.
[20] SHAO J. and CHOW S.C. Constructing Release Targets for Drug Products:A Bayesian Decision Theory Approach[J]. Journal of the Royal Statistical Society, 1991,40(3):381.