{"id":6368,"date":"2025-07-05T19:41:21","date_gmt":"2025-07-05T10:41:21","guid":{"rendered":"https:\/\/tuat-chemphys.net\/?p=6368"},"modified":"2025-07-05T19:41:21","modified_gmt":"2025-07-05T10:41:21","slug":"%e3%82%88%e3%82%8a%e5%ae%89%e5%85%a8%e3%81%aa%e8%96%ac%e3%81%a5%e3%81%8f%e3%82%8a%e3%81%ae%e3%81%9f%e3%82%81%e3%81%ae%e3%82%b9%e3%83%9e%e3%83%bc%e3%83%88%e3%81%aa%e7%9b%a3%e8%a6%96%e6%8a%80%e8%a1%93-s","status":"publish","type":"post","link":"https:\/\/tuat-chemphys.net\/?p=6368","title":{"rendered":"\u3088\u308a\u5b89\u5168\u306a\u85ac\u3065\u304f\u308a\u306e\u305f\u3081\u306e\u30b9\u30de\u30fc\u30c8\u306a\u76e3\u8996\u6280\u8853 Smarter Monitoring for Safer Medicine Production"},"content":{"rendered":"\n

https:\/\/doi.org\/10.1248\/cpb.c24-00652<\/a><\/p>\n\n\n\n

\u3053\u306e\u7814\u7a76\u3067\u306f\u3001\u85ac\u3092\u4f5c\u308b\u5de5\u5834\u3067\u4f7f\u308f\u308c\u308b\u300c\u9023\u7d9a\u88fd\u9020\u300d\u3068\u3044\u3046\u65b9\u6cd5\u306b\u304a\u3044\u3066\u3001\u6a5f\u68b0\u306e\u7570\u5e38\u3084\u539f\u6599\u306e\u5909\u5316\u3092\u898b\u3064\u3051\u308b\u305f\u3081\u306e\u65b0\u3057\u3044\u65b9\u6cd5\u3092\u63d0\u6848\u3057\u3066\u3044\u307e\u3059\u3002\u4f7f\u308f\u308c\u3066\u3044\u308b\u306e\u306f\u300c\u591a\u5909\u91cf\u7d71\u8a08\u7684\u30d7\u30ed\u30bb\u30b9\u7ba1\u7406\uff08MSPC\uff09\u300d\u3068\u3044\u3046\u6280\u8853\u3067\u3001\u305f\u304f\u3055\u3093\u306e\u30bb\u30f3\u30b5\u30fc\u304b\u3089\u306e\u30c7\u30fc\u30bf\u3092\u307e\u3068\u3081\u3066\u5206\u6790\u3059\u308b\u3053\u3068\u3067\u3001\u7570\u5e38\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n

\u3067\u3082\u3001\u3053\u308c\u307e\u3067\u306e\u65b9\u6cd5\u3067\u306f\u300c\u9593\u9055\u3063\u3066\u7570\u5e38\u3068\u5224\u65ad\u3057\u3066\u3057\u307e\u3046\u300d\u3053\u3068\u304c\u591a\u304f\u3042\u308a\u307e\u3057\u305f\u3002\u305d\u3053\u3067\u3053\u306e\u7814\u7a76\u3067\u306f\u3001\u30c7\u30fc\u30bf\u306e\u300c\u6a19\u6e96\u5316\uff08\u30b9\u30b1\u30fc\u30ea\u30f3\u30b0\uff09\u300d\u306e\u65b9\u6cd5\u3092\u5de5\u592b\u3059\u308b\u3053\u3068\u3067\u3001\u7570\u5e38\u3092\u6b63\u3057\u304f\u898b\u3064\u3051\u308b\u7cbe\u5ea6\u3092\u9ad8\u3081\u307e\u3057\u305f\u3002<\/p>\n\n\n\n

\u306a\u305c\u3053\u306e\u7814\u7a76\u304c\u5927\u5207\uff1f<\/strong>
\u85ac\u306e\u88fd\u9020\u3067\u306f\u3001\u54c1\u8cea\u3092\u4fdd\u3064\u3053\u3068\u304c\u3068\u3066\u3082\u91cd\u8981\u3067\u3059\u3002\u7570\u5e38\u3092\u65e9\u304f\u898b\u3064\u3051\u308b\u3053\u3068\u3067\u3001\u5b89\u5168\u3067\u9ad8\u54c1\u8cea\u306a\u85ac\u3092\u5b89\u5b9a\u3057\u3066\u4f5c\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u30c7\u30fc\u30bf\u306e\u6271\u3044\u65b9\u3072\u3068\u3064\u3067\u7d50\u679c\u304c\u5927\u304d\u304f\u5909\u308f\u308b\u3053\u3068\u3092\u77e5\u308b\u3068\u3001\u79d1\u5b66\u3084\u5de5\u5b66\u306e\u9762\u767d\u3055\u3092\u611f\u3058\u3089\u308c\u308b\u304b\u3082\u3057\u308c\u307e\u305b\u3093\uff01<\/p>\n\n\n\n

This study focuses on improving how we detect problems in pharmaceutical continuous manufacturing\u2014a modern method for making medicines. The researchers used a technique called Multivariate Statistical Process Control (MSPC), which analyzes data from many sensors to spot unusual behavior.<\/p>\n\n\n\n

However, previous methods often gave false alarms. This study found that by adjusting how the data is scaled (standardized), the system can more accurately detect real issues\u2014like changes in machine settings or raw materials\u2014without being confused by small, harmless fluctuations.<\/p>\n\n\n\n

Why is this research important?<\/strong>
In medicine production, ensuring consistent quality is critical. Detecting anomalies early helps prevent defective products and keeps patients safe. This shows how smart data handling can make a big difference in real-world technology!<\/p>\n\n\n\n

\"\"
Process Flow of Continuous Wet Granulation Process \u9023\u7d9a\u6e7f\u5f0f\u9020\u7c92\u30d7\u30ed\u30bb\u30b9\u306e\u30d7\u30ed\u30bb\u30b9\u30d5\u30ed\u30fc<\/figcaption><\/figure>\n\n\n\n

Journal: Chemical and Pharmaceutical Bulletin
Volume 73 (2025) Issue 3\/Regular Article https:\/\/doi.org\/10.1248\/cpb.c24-00652<\/a>
Highly Precise Anomaly Detection Using Multivariate Statistical Process Control with Appropriate Scaling of Input Variables in Pharmaceutical Continuous Manufacturing<\/strong>
Takuya Oishi, Takuya Nagato, Chikara Tsujikawa, Takuya Minamiguchi, Sanghong Kim<\/p>\n\n\n\n

<\/p>\n\n\n\n

This study proposes improved scaling methods for Multivariate Statistical Process Control (MSPC) to enhance anomaly detection in pharmaceutical continuous manufacturing. By applying these methods to wet granulation and fluidized bed drying processes, the researchers demonstrated that appropriate scaling\u2014based on combined datasets or domain knowledge\u2014significantly reduces false positives and improves detection accuracy. The MSPC models successfully identified both equipment-related and raw-material-related anomalies, offering a practical framework for real-time monitoring and quality assurance in pharmaceutical production.<\/p>\n\n\n\n

\u672c\u7814\u7a76\u3067\u306f\u3001\u88fd\u85ac\u306e\u9023\u7d9a\u88fd\u9020\u306b\u304a\u3051\u308b\u7570\u5e38\u691c\u51fa\u7cbe\u5ea6\u3092\u5411\u4e0a\u3055\u305b\u308b\u305f\u3081\u306b\u3001\u591a\u5909\u91cf\u7d71\u8a08\u7684\u30d7\u30ed\u30bb\u30b9\u7ba1\u7406\uff08MSPC\uff09\u306e\u30b9\u30b1\u30fc\u30ea\u30f3\u30b0\u624b\u6cd5\u3092\u6539\u826f\u3057\u307e\u3057\u305f\u3002\u63d0\u6848\u624b\u6cd5\u3092\u6e7f\u5f0f\u9020\u7c92\u304a\u3088\u3073\u6d41\u52d5\u5c64\u4e7e\u71e5\u30d7\u30ed\u30bb\u30b9\u306b\u9069\u7528\u3057\u3001\u30ad\u30e3\u30ea\u30d6\u30ec\u30fc\u30b7\u30e7\u30f3\u30c7\u30fc\u30bf\u3068\u975e\u6b63\u5e38\u30c7\u30fc\u30bf\u306e\u7d44\u307f\u5408\u308f\u305b\u3001\u307e\u305f\u306f\u30d7\u30ed\u30bb\u30b9\u306b\u95a2\u3059\u308b\u5c02\u9580\u77e5\u8b58\u306b\u57fa\u3065\u304f\u30b9\u30b1\u30fc\u30ea\u30f3\u30b0\u306b\u3088\u308a\u3001\u8aa4\u691c\u51fa\u7387\u306e\u4f4e\u6e1b\u3068\u691c\u51fa\u7cbe\u5ea6\u306e\u5411\u4e0a\u3092\u5b9f\u8a3c\u3057\u307e\u3057\u305f\u3002MSPC\u30e2\u30c7\u30eb\u306f\u3001\u88c5\u7f6e\u306e\u7570\u5e38\u3060\u3051\u3067\u306a\u304f\u539f\u6599\u306e\u5909\u5316\u3082\u691c\u51fa\u53ef\u80fd\u3067\u3042\u308a\u3001\u88fd\u85ac\u88fd\u9020\u306b\u304a\u3051\u308b\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u76e3\u8996\u3068\u54c1\u8cea\u4fdd\u8a3c\u306e\u5b9f\u7528\u7684\u306a\u67a0\u7d44\u307f\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

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