In silico production of relative correction factor for the quantitative analysis of multi-components by single marker method.

Introduction: Traditional methods to derive experimentally-generated relative correction factors (RCFs) for the quantitative analysis of herbal multi-components by single marker (QAMS) method require reference standards and multiple validations with different instruments and columns, which hampers high throughput implementation.

Objectives: To effectively reduce the application amounts of raw material and provide higher and more stable accuracy, this study aimed to develop a method to computationally generate RCFs of herbal components.

Materials And Methods: This strategy included the published data collection, calibration curves screening, computer algorithm-based RCFs generation and accuracy validation.