Investigation into the pharmacokinetic–pharmacodynamic model of Zingiberis Rhizoma/Zingiberis Rhizoma Carbonisata and contribution to their therapeutic material basis using artificial neural networks

Abstract

Zingiberis Rhizoma (ZR) and Zingiberis Rhizoma Carbonisata (ZRC) are two varieties of processed ginger, which are widely used in traditional Chinese medicine (TCM) and exhibit varying drug efficacy. In this study, an Artificial Neural Network (ANN) model was developed for simultaneously characterizing the pharmacokinetics (PK) and pharmacodynamics (PD) of ZR/ZRC. In order to evaluate the relative contribution of the ZR/ZRC drug concentration of its main components to its drug efficacy, connection weights method and Mean Impact Value (MIV) have been introduced. The results have shown that sequences of the contribution value calculated by these two methods was same overall and indicated that the active components of ZR and ZRC exhibited opposite drug efficacy after processing. In conclusion, ANN was found to be a powerful tool that linked PK and PD profiles of ZR/ZRC with multiple components; it also provided a simple method to identify and rank the relative contribution of each to the multiple therapeutic effects of the drug.