{"title":"人工智能在医药产品配方中的未来","authors":"L. Singh, R. Tiwari, S. Verma, V. Sharma","doi":"10.2174/2210303109666190621144400","DOIUrl":null,"url":null,"abstract":"\n\nConventional approach of formulating a new dosage form is a comprehensive\ntask and uses various sources like man, money, time and experimental efforts. The use of AI can help\nto obtain optimized pharmaceutical formulation with desired (best) attributes. AI minimizes the use of\nresources and increases the understanding of impact, of independent variable over desired dependent\nresponses/variables.\n\n\n\nThus, the aim of present work is to explore the use of Artificial intelligence in designing\npharmaceutical products as well as the manufacturing process to get the pharmaceutical product of desired\nattributes with ease. The review is presenting various aspects of Artificial intelligence like Quality\nby Design (QbD) & Design of Experiment (DoE) to confirm the quality profile of drug product, reduce\ninteractions among the input variables for the optimization, modelization and various simulation tools\nused in pharmaceutical manufacturing (scale up and production).\n\n\n\nHence, the use of QbD approach in Artificial intelligence is not only useful in understanding\nthe products or process but also helps in building an excellent and economical pharmaceutical product.\n","PeriodicalId":11310,"journal":{"name":"Drug Delivery Letters","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The Future of Artificial Intelligence in Pharmaceutical Product Formulation\",\"authors\":\"L. Singh, R. Tiwari, S. Verma, V. Sharma\",\"doi\":\"10.2174/2210303109666190621144400\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n\\nConventional approach of formulating a new dosage form is a comprehensive\\ntask and uses various sources like man, money, time and experimental efforts. The use of AI can help\\nto obtain optimized pharmaceutical formulation with desired (best) attributes. AI minimizes the use of\\nresources and increases the understanding of impact, of independent variable over desired dependent\\nresponses/variables.\\n\\n\\n\\nThus, the aim of present work is to explore the use of Artificial intelligence in designing\\npharmaceutical products as well as the manufacturing process to get the pharmaceutical product of desired\\nattributes with ease. The review is presenting various aspects of Artificial intelligence like Quality\\nby Design (QbD) & Design of Experiment (DoE) to confirm the quality profile of drug product, reduce\\ninteractions among the input variables for the optimization, modelization and various simulation tools\\nused in pharmaceutical manufacturing (scale up and production).\\n\\n\\n\\nHence, the use of QbD approach in Artificial intelligence is not only useful in understanding\\nthe products or process but also helps in building an excellent and economical pharmaceutical product.\\n\",\"PeriodicalId\":11310,\"journal\":{\"name\":\"Drug Delivery Letters\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Drug Delivery Letters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2174/2210303109666190621144400\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Pharmacology, Toxicology and Pharmaceutics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Drug Delivery Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/2210303109666190621144400","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Pharmacology, Toxicology and Pharmaceutics","Score":null,"Total":0}
The Future of Artificial Intelligence in Pharmaceutical Product Formulation
Conventional approach of formulating a new dosage form is a comprehensive
task and uses various sources like man, money, time and experimental efforts. The use of AI can help
to obtain optimized pharmaceutical formulation with desired (best) attributes. AI minimizes the use of
resources and increases the understanding of impact, of independent variable over desired dependent
responses/variables.
Thus, the aim of present work is to explore the use of Artificial intelligence in designing
pharmaceutical products as well as the manufacturing process to get the pharmaceutical product of desired
attributes with ease. The review is presenting various aspects of Artificial intelligence like Quality
by Design (QbD) & Design of Experiment (DoE) to confirm the quality profile of drug product, reduce
interactions among the input variables for the optimization, modelization and various simulation tools
used in pharmaceutical manufacturing (scale up and production).
Hence, the use of QbD approach in Artificial intelligence is not only useful in understanding
the products or process but also helps in building an excellent and economical pharmaceutical product.