Population pharmacokinetic analysis and dosing optimization of polymyxin B in critically ill patients.

Objectives: Since the global broadcast of multidrug-resistant gram-negative bacteria is accelerating, the use of Polymyxin B is sharply increasing, especially in critically ill patients. Unsatisfactory therapeutic effects were obtained because of the abnormal physiological function in critically ill patients. Therefore, the determination of optimal polymyxin B dosage becomes highly urgent. This study aimed to illustrate the polymyxin B pharmacokinetic characteristics by defining the influencing factors and optimizing the dosing regimens to achieve clinical effectiveness. Methods: Steady-state concentrations of polymyxin B from twenty-two critically ill patients were detected by a verified liquid chromatography-tandem mass spectrometry approach. The information on age, weight, serum creatinine, albumin levels, and Acute Physiology and Chronic Health Evaluation-II (APACHE-II) score was also collected. The population PK parameters were calculated by the non-parametric adaptive grid method in Pmetrics software, and the pharmacokinetic/pharmacodynamics target attainment rate was determined by the Monte Carlo simulation method. Results: The central clearance and apparent volume of distribution for polymyxin B were lower in critically ill patients (1.24 ± 0.38 L h-1 and 16.64 ± 12.74 L, respectively). Moreover, albumin (ALB) levels can be used to explain the variability in clearance, and age can be used to describe the variability in the apparent volume of distribution. For maintaining clinical effectiveness and lowering toxicity, 75 mg q12 h is the recommended dosing regimen for most patients suffering from severe infections. Conclusion: This study has clearly defined that in critically ill patients, age and ALB levels are potentially important factors for the PK parameters of polymyxin B. Since older critically ill patients tend to have lower ALB levels, so higher dosages of polymyxin B are necessary for efficacy.

Physiologically based pharmacokinetic-pharmacodynamic evaluation of meropenem in CKD and hemodialysis individuals.

Objective: Chronic kidney disease (CKD) has significant effects on renal clearance of drugs. The application of antibiotics in CKD patients to achieve the desired therapeutic effect is challenging. This study aims to determine meropenem plasma exposure in the CKD population and further investigate optimal dosing regimens. Methods: A healthy adult PBPK model was established using the meropenem's physicochemical parameters, pharmacokinetic parameters, and available clinical data, and it was scaled to the populations with CKD and dialysis. The differences between the predicted concentration, Cmax, and AUClast predicted and observed model values were assessed by mean relative deviations (MRD) and geometric mean fold errors (GMFE) values and plotting the goodness of fit plot to evaluate the model's performance. Finally, dose recommendations for CKD and hemodialysis populations were performed by Monte Carlo simulations. Results: The PBPK models of meropenem in healthy, CKD, and hemodialysis populations were successfully established. The MRD values of the predicted concentration and the GMFE values of Cmax and AUClast were within 0.5-2.0-fold of the observed data. The simulation results of the PBPK model showed the increase in meropenem exposure with declining kidney function in CKD populations. The dosing regimen of meropenem needs to be further adjusted according to the renal function of CKD patients. In patients receiving hemodialysis, since meropenem declined more rapidly during the on-dialysis session than the off-dialysis session, pharmacodynamic evaluations were performed for two periods separately, and respective optimal dosing regimens were determined. Conclusion: The established PBPK model successfully predicted meropenem pharmacokinetics in patients with CKD and hemodialysis and could further be used to optimize dosing recommendations, providing a reference for personalized clinical medication.

Stereoisomers of octahydrocurcumin, the hydrogenated metabolites of curcumin, display stereoselective activity on the CYP2E1 enzyme in L-02 cells.

As the final hydrogenated metabolite of curcumin, octahydrocurcumin (OHC) exhibits increased powerful bioactivities. The chiral and symmetric chemical structure indicated that there were two OHC stereoisomers, (3R,5S)-octahydrocurcumin (Meso-OHC) and (3S,5S)-octahydrocurcumin ((3S,5S)-OHC), which may induce different effects on metabolic enzymes and bioactivities. Thus, we detected OHC stereoisomers from rat metabolites (blood, liver, urine and feces) after oral administration of curcumin. In addition, OHC stereoisomers were prepared and then their different influences on cytochrome P450 enzymes (CYPs) and UDP-glucuronyltransferases (UGTs) in L-02 cells were tested to explore the potential interaction and different bioactivities. Our results proved that curcumin could be metabolised into OHC stereoisomers first. In addition, Meso-OHC and (3S,5S)-OHC exhibited slight induction or inhibition effects on CYP1A2, CYP2A6, CYP2C8, CYP2C9, CYP3A4 and UGTs. Furthermore, Meso-OHC exhibited more intensive inhibition toward CYP2E1 expression than (3S,5S)-OHC, ascribed to the different mode of binding to the enzyme protein (P < 0.05), which finally induced more effective liver protection effects in acetaminophen-induced L-02 cell injury.

Changes in clinical trials of endocrine disorder and metabolism and nutrition disorder drugs in mainland China over 2010-2019.

With the improvements in relevant policies, laws, and regulations regarding drug clinical trials in China, the quantity and quality of drug clinical trials have gradually improved, and the development prospects of drug clinical trials for endocrine disorders and metabolism and nutrition disorders are promising. Based on information from the clinical trials from the online drug clinical trial registration platform of the National Medical Products Administration, we aimed to review and evaluate the development of clinical trials of drugs for endocrine disorders and metabolism and nutrition disorders in mainland China from 2010 to 2019, as well as the trends over time. A total of 861 trials were carried out on 254 types of drugs for endocrine disorders and metabolism and nutrition disorders, among which 531 (61.67%) involved endocrine disorders, and 330 (38.33%) addressed metabolism and nutrition disorders. The annual number of clinical trials has been increasing gradually, with a significant increase in 2017. Among them, the proportion of clinical trials with Chinese epidemiological characteristics was relatively large (Wu, Annual Report on Development Health Management and Health Industry in China, 2018). The largest number of trials were for diabetes drugs (55.63%), followed by trials of drugs for hyperlipidemia (19.4%) and those for hyperuricemia (7.9%). It was found that the geographical area of the leading units also showed obvious unevenness according to the analysis of the test unit data. Based on the statistics and evaluation of the data, comprehensive information is provided to support the cooperation of global pharmaceutical R&D companies and research units in China and the development of international multicenter clinical trials in China. This work additionally provides clinical trial units with a self-evaluation of scientific research competitiveness and hospital development strategies. At the same time, it provides a reference with basic data for sponsors and stakeholders in these trials to determine their development strategy goals.

Drug-target-disease network analysis of gene-phenotype connectivity for genistein in ovarian cancer.

PURPOSE: Genistein belongs to the group of isoflavones, which include powerful anticancer agents. Its antitumor properties have been intensively described in many cancers, but related studies assessing ovarian cancer are scarce. The aim of this study was to develop a new method of the underlying mechanisms of genistein's effects and broaden the perspective of targeted therapies in ovarian carcinoma. MATERIALS AND METHODS: Genistein targets were searched in the DrugBank database. Prediction of drug interactions with targets (including secondary targets) was performed with STRING database. Interaction pairs with overall score above 0.9 were recorded for protein-protein interaction (PPI) network generation based on the Cytoscape software. Genes with intense interconnections were grouped into a module. Then, PPI network modules with significance were assessed using Molecular Complex Detection (MCODE) analysis tool. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed for the critical genes. Furthermore, disease targets were searched in Comparative Toxicogenomics Database (CTD). The overlapping targets were studied using a Kaplan-Meier analysis to evaluate ovarian carcinoma survival. RESULTS: A total of 13 direct targets and 372 secondary targets were identified for genistein and further analyzed with the MCODE analysis tool to identify critical genes. The top 72 genes were further assessed with KEGG. Then, the term "ovarian cancer" was searched in CTD, and 123 genes associated only with the marker "T" or "M" were recorded. Next, seven overlapping genes (CDKN1B, PTEN, EGFR, MAPK1, MAPK3, PIK3C, and AKT1) resulting from the intersection of three pathways and 123 genes were obtained from CTD. Elevated CDKN1B amounts showed correlation with overall survival (log-rank P=0.021) according to Kaplan-Meier analysis. CONCLUSION: The current findings indicated that drug-target-disease network analysis represents a useful tool in gene-phenotype connectivity for genistein in ovarian cancer. Our result also showed that CDKN1B is worthy of further research.