The Degradation Process Modeling and Shelf Life Prediction of Drug
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...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2019-02-01
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| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1636 |
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| Summary: | 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 No5 loaded and bottled drugs’ shelf life predicted values are 4395 and 4747 weeks The relative errors are 0043 and 0051 And the feasibility of fusing degradation data to predict the shelf life of the monolithic drug and new drugs is verified |
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| ISSN: | 1007-2683 |