A method and system for determining the content of volatile components in a high-activity transdermal patch
By optimizing resource allocation through dynamic hierarchical clustering and ensemble regression modeling, the accuracy and efficiency issues of detecting volatile components in highly active transdermal patches were resolved, achieving high-precision and high-stability detection results.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHEJIANG DINGTAI PHARMA
- Filing Date
- 2026-04-14
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies have low accuracy and efficiency in detecting the content of volatile components in highly active transdermal patches, and poor adaptability, making it difficult to meet the data requirements of complex and ever-changing drug samples.
By employing dynamic hierarchical clustering, ensemble regression modeling, and multi-batch data fusion mechanisms, and through dynamically adjusting the sample batch size, hierarchical clustering in multidimensional feature space, ensemble model training, and consistency verification, resource allocation is optimized to improve detection accuracy and stability.
It achieves high-throughput, high-precision, and high-stability detection of volatile components, adapts to complex and ever-changing drug sample data, and improves the accuracy and efficiency of detection.
Smart Images
Figure CN122409933A_ABST