Herbal medicines are widely used for treating liver diseases and generally regarded as safe due to their extensive use in Traditional Chinese Medicine practice for thousands of years. However, in recent years, there have been increased concerns regarding the long-term risk of Herb-Induced Liver Injury (HILI) in patients with liver dysfunction. Herein, two representative Chinese herbal medicines: one—Xiao-Chai-Hu-Tang (XCHT)—a composite formula, and the other—Radix Polygoni Multiflori (Heshouwu)—a single herb, were analyzed by network pharmacology study. Based on the network pharmacology framework, we exploited the potential HILI effects of XCHT and Heshouwu by predicting the molecular mechanisms of HILI and identified the potential hepatotoxic ingredients in XCHT and Heshouwu. According to our network results, kaempferol and thymol in XCHT and rhein in Heshouwu exhibit the largest number of liver injury target connections, whereby CASP3, PPARG and MCL1 may be potential liver injury targets for these herbal medicines. This network pharmacology assay might serve as a useful tool to explore the underlying molecular mechanism of HILI. Based on the theoretical predictions, further experimental verification should be performed to validate the accuracy of the predicted interactions between herbal ingredients and protein targets in the future.

Hyperplasia of mammary glands (HMG) is common in middle‐aged women. Danlu capsules (DLCs) can effectively relieve pain and improve clinical symptoms and are safe for treating HMG. However, the active substances in DLCs and the molecular mechanisms of DLCs in HMG remain unclear. This study identified the bioactive compounds and delineated the molecular targets and potential pathways of DLCs by using a systems pharmacology approach. The candidate compounds were retrieved from the traditional Chinese medicine systems pharmacology (TCMSP) database and analysis platform. Each candidate’s druggability was analyzed according to its oral bioavailability and drug‐likeness indices. The candidate proteins and genes were extracted in the TCMSP and UniProt Knowledgebase, respectively. The potential pathways associated with the genes were identified by performing gene enrichment analysis with DAVID Bioinformatics Resources 6.7. A total of 603 compounds were obtained from DLCs, and 39 compounds and 66 targets associated with HMG were obtained. Gene enrichment analysis yielded 10 significant pathways with 34 targets. The integrated HMG pathway revealed that DLCs probably act in patients with HMG through multiple mechanisms of anti‐inflammation, analgesic effects, and hormonal regulation. This study provides novel insights into the mechanisms of DLCs in HMG, from the molecular level to the pathway level.

The amount of drug remaining after previous doses, or drug accumulation, is closely related to drug efficacy and safety. An accurate calculation of the accumulation index or ratio (Rac) is crucial for dose finding. However, in drug accumulation studies little consensus exists with regard to experimental design or data analysis. We conducted a systematic review of the literature to produce a detailed profile of drug accumulation studies of the last 30 years (1980-2011). Ninety-six articles comprising 122 studies were analyzed. A typical drug accumulation study enrolled 10 to 20 subjects randomly assigned into treatment groups of 1 or 2 dose levels to observe pharmacokinetic behaviors. The median washout period between single and multiple dosing was 7 days, and the dose interval was 1-2 elimination half-lives in non- or one-compartmental models. Generally, the number of repeated times of administration for multiple dosing was 7-14, and the median number of sampling time points was 11. Eight different methods were used to calculate Rac. The most frequently used method, in 72.9% of the studies, was to set Rac equal to the ratio of the area under a plasma concentration-time curve (AUC) during a dosage interval at steady state to the AUC of a dosage interval after the first dose, i.e., Rac = AUC0-ι,ss / AUC0-ι,1. The values of Rac in the included studies ranged from 0.85 to 18.8, and 68.03% were <2. We suggest that sample size estimation for an accumulation study should be similar to that of a bioequivalence study, and in most studies, 18-24 subjects will be needed. Appropriate calculation methods for Rac should be selected based on the experimental design and data characteristics. The crucial values for non-, weak, moderate, and strong accumulation can be set at Rac < 1.2, 1.2 ≤ Rac < 2, 2 ≤ Rac < 5, and Rac ≥ 5, respectively. Accumulations studies should also give more regard to drug metabolism and increased accumulation in kidney or liver damaged patients.

Although ginseng has long been broadly used in clinical settings around the world, few clinical trials on ginseng have been conducted. The objective of this study was to provide a comprehensive evaluation of the characteristics of ginseng clinical trials registered in the WHO International Clinical Trials Registry Platform (ICTRP) as of December 2017 regarding their frequency, design, type of ginseng, dosage, duration, condition, funding sources, and publication status. A total of 134 ginseng clinical studies were registered from 2002 to 2017, of which 60.4% were completed and 23.1% are actively recruiting participants. A large number of trials were associated with aspects of high-quality trial design. Overall, 94% of the trials employed randomized allocation to study arms, 78.4% were double-blind studies using placebo as one of the control groups, and 71% were published as completed trials. Trials whose sample size was restricted to fewer than 100 participants accounted for 74.7% of the total. Of the primary funding sources for ginseng studies, 67.2% were nonindustry organizations. The ginseng clinical trials were heterogeneous with respect to ginseng species and variety, indications, dose, duration, and participant characteristics. Clearly, stricter and methodologically suitable studies are needed to demonstrate the efficacy and safety of ginseng.

This study aimed to evaluate the clinical analgesic efficacy and identify the molecular targets of XGDP for treating primary dysmenorrhea (PD) by a network pharmacology approach. Analysis of pain disappearance rate of XGDP in PD treatment was conducted based on data from phase II and III randomized, double‐blind, double‐simulation, and positive parallel controlled clinical trials. The bioactive compounds were obtained by the absorption, distribution, metabolism, and excretion processes with oral bioavailability (OB) and drug‐likeness (DL) evaluation. Subsequently, target prediction, pathway identification, and network construction were employed to clarify the mechanisms of the analgesic effect of XGDP on PD. The pain disappearance rates in phase II and III clinical trials of XGDP in PD treatment were 62.5% and 55.8%, respectively, yielding a significant difference (P < 0.05) when compared with the control group using Tongjingbao granules (TJBG). Among 331 compounds, 53 compounds in XGDP were identified as the active compounds related to PD through OB, DL, and target prediction. The active compounds and molecular targets of XGDP were identified, and our study showed that XGDP may exert its therapeutic effects on PD through the regulation of the targets related to anti‐inflammation analgesia and central analgesia and relieving smooth muscle contraction.