\u300c2021\u5800\u5834\u96c5\u592b\u8cde\u300d\u306e\u6388\u8cde\u5f0f\u3092\u958b\u50ac\u3001\u82e5\u624b\u7814\u7a76\u8005\u3092\u9855\u5f70 – HORIBA<\/a><\/figcaption><\/figure><\/div>\n\n\n\nIn recent years, the development of new technologies to improve the efficiency of pharmaceutical production has been required. As part of this effort, the development of technology to convert from “batch production” to continuous production has been promoted. In order to realize continuous production, real-time monitoring of drug information in the production process is indispensable. However, it is often difficult to directly measure drug quality in real time. In addition, conventional methods for predicting the quality of a pharmaceutical product from the near-infrared spectrum have drawbacks such as a decrease in prediction accuracy over time, and there have been problems in their use in production processes.<\/p>\n\n\n\n
Dr. Kim developed a new data analysis method using data science technology with the aim of developing a method for stably and accurately predicting the quality of pharmaceuticals from the near-infrared (NIR) spectrum. Real-time quality control and control using this method is expected to not only reduce costs, but also reduce environmental impact and accident risk, thereby improving the efficiency of the pharmaceutical production process.<\/p>\n\n\n\n
(Batch Production is a production method in which each process is independent, and the product is sampled after the end of one process to verify quality and then transferred to the next process.)<\/p>\n","protected":false},"excerpt":{"rendered":"
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