A stepwise integrated multi-system to screen quality markers of Chinese classic prescription Qingzao Jiufei decoction on the treatment of acute lung injury by combining 'network pharmacology-metabolomics-PK/PD modeling'

Background: Previously, we have investigated the therapeutic mechanism of Qingzao Jiufei Decoction (QZJFD), a Chinese classic prescription, on acute lung injury (ALI), however, which remained to be further clarified together with the underlying efficacy related compounds for quality markers (Q-markers). Hypothesis/Purpose: To explore Q-markers of QZJFD on ALI by integrating a stepwise multi-system with 'network pharmacology-metabolomics- pharmacokinetic (PK)/ pharmacodynamic (PD) modeling'. Methods: First, based on in vitro and in vivo component analysis, a network pharmacology strategy was developed to identify active components and potential action mechanism of QZJFD on ALI. Next, studies of poly-pharmacology and non-targeted metabolomics were used to elaborate efficacy and verify network pharmacology results. Then, a comparative PK study on active components in network pharmacology was developed to profile their dynamic laws in vivo under ALI, suggesting Q-marker candidates. Next, quantified analytes with marked PK variations after modeling were fitted with characteristic endogenous metabolites along drug concentration-efficacy-time curve in a PK-PD modeling to verify and select primary effective compounds. Finally, Q-markers were further chosen based on representativeness among analytes through validity analysis of PK quantitation of primary effective compounds. Results: In virtue of 121 and 33 compounds identified in vitro and in vivo, respectively, 33 absorbed prototype compounds were selected to construct a ternary network of '20 components-47 targets-113 pathways' related to anti-ALI of QZJFD. Predicted mechanism (leukocytes infiltration, cytokines, endogenous metabolism) were successively verified by poly-pharmacology and metabolomics. Next, 18 measurable components were retained from 20 analytes by PK comparison under ALI. Then, 15 primary effective compounds from 18 PK markers were further selected by PK-PD analysis. Finally, 9 representative Q-markers from 15 primary effective compounds attributed to principal (chlorogenic acid), ministerial (methylophiopogonanone A, methylophiopogonanone B), adjuvant (sesamin, ursolic acid, amygdalin), conductant drugs (liquiritin apioside, liquiritigenin and isoliquiritin) in QZJFD, were recognized by substitutability and relevance of plasmatic concentration at various time points. Conclusion: 9 Q-markers for QZJFD on ALI were identified by a stepwise integration strategy, moreover, which was a powerful tool for screening Q-makers involved with the therapeutic action of traditional Chinese medicine (TCM) prescription and promoting the process of TCM modernization and scientification.