The main purpose of this paper is to explore the applicability of multivariate multilevel models for bioequivalence evaluation. Using an example of a 4×4 cross-over test design in evaluating bioequivalence of homemade and imported rosiglitazone maleate tablets,this paper illustrated the multivariate-model-based method for partitioning total variances of In (AUC) and In (C_(max)) in the framework of multilevel models. It examined the feasibility of multivariate multilevel models in directly evaluating average bioequivalence (ABE),population bioequivalence (PBE) and individual bioequivalenc (IBE). Taking into account the correlation between In (AUC) and In (C_(max)) of rosiglitazone maleate tablets,the proposed models suggested no statistical difference between the two effect measures in their ABE bioequivalence via joint tests,whilst a contradictive conclusion was derived based on univariate multilevel models. Furthermore,the PBE and IBE for both In (AUG) and In(C_(max)) of the two types of tablets were assessed with no statistical difference based on estimates of variance components from the proposed models. Multivariate multilevel models could be used to analyze bioequivalence of multiple effect measures simultaneously and they provided a new way of statistical analysis to evaluate bioequivalence.

The pharmacokinetics of a long-circulating PEGylated Radix Ophiopogonis polysaccharide (ROP) was investigated in rats following i.v. or s.c. administration at three dose levels (9, 20, 50 mg x kg(-1)). A moderate coupling reaction between the hydroxyl-activated ROP and the amino-terminated mPEG was chosen to produce PEGylate ROP. The grafting degree of the prepared conjugate was 1.03, and the molecular mass of mPEG used was 20 kDa. High-performance gel permeation chromatorgraphy with fluorescein isothiocyanate prelabeling was established to determine levels of the conjugate in plasma. The results showed that the elimination half-life of the conjugate following s.c. administration was basically identical to that after iv administration. An accurate linear correlation was observed between administration doses and areas under the curve of plasma conjugate level vs. time profile, regardless of the administration route. The absolute bioavailability of the conjugate following sc administration was approximately 56%, and the mean in vivo residence time was 52.1 h, increased 2.4 times compared to those of iv administration. In general, linear pharmacokinetics was observed for the conjugate within the dose range studied, and sc should be a promising administration route for the conjugate.
Animals ; Area Under Curve ; Biological Availability ; Drug Carriers ; Drugs, Chinese Herbal ; administration & dosage ; chemistry ; isolation & purification ; pharmacokinetics ; Half-Life ; Injections, Intravenous ; Injections, Subcutaneous ; Ophiopogon ; chemistry ; Plant Roots ; chemistry ; Plants, Medicinal ; chemistry ; Polyethylene Glycols ; chemistry ; Polysaccharides ; administration & dosage ; chemistry ; isolation & purification ; pharmacokinetics ; Rats ; Rats, Sprague-Dawley

This study aims to explore the application value of multilevel models for bioequivalence evaluation. Using a real example of 2 x 4 cross-over experimental design in evaluating bioequivalence of antihypertensive drug, this paper explores complex variance components corresponding to criteria statistics in existing methods recommended by FDA but obtained in multilevel models analysis. Results are compared with those from FDA standard Method of Moments, specifically on the feasibility and applicability of multilevel models in directly assessing the bioequivalence (ABE), the population bioequivalence (PBE) and the individual bioequivalence (IBE). When measuring ln (AUC), results from all variance components of the test and reference groups such as total variance (sigma(TT)(2) and sigma(TR)(2)), between-subject variance (sigma(BT)(2) and sigma(BR)(2)) and within-subject variance (sigma(WT)(2) and sigma(WR)(2)) estimated by simple 2-level models are very close to those that using the FDA Method of Moments. In practice, bioequivalence evaluation can be carried out directly by multilevel models, or by FDA criteria, based on variance components estimated from multilevel models. Both approaches produce consistent results. Multilevel models can be used to evaluate bioequivalence in cross-over test design. Compared to FDA methods, this one is more flexible in decomposing total variance into sub components in order to evaluate the ABE, PBE and IBE. Multilevel model provides a new way into the practice of bioequivalence evaluation.
Area Under Curve ; Cross-Over Studies ; Models, Statistical ; Multilevel Analysis ; Therapeutic Equivalency

This study was aimed to investigate the changes of cytokine contents in single donor platelets (SDPs) collected by using MCS(+), Trima, Amicus blood cell separators during storage. 18 portions of SDPs were collected by MCS(+), Trima, Amicus blood cell separators, were preserved in standard condition of blood bank, the levels of cytokines such as IL-8, RANTES, CD154, TGF-beta(1) and VEGF were detected by ELISA at 1, 3, 5, 7 days during storage. The results showed that the levels of IL-8, RANTES, CD154, TGF-beta(1) and VEGF in SDPs collected by blood cell separators MCS(+), Trima, and Amicus gradually increased with prolonging of time during storage, but the increase of IL-8 level in SDPs collected by MCS(+) separator was significant difference from SDPs collected by Trime and Amicus separators (p < 0.05). It is concluded that the all collected SDPs mentioned above express IL-8, RANTES, CD154, TGF-beta(1) and VEGF during storage, and their cytokine levels show a tendency to increase with prolonging of time during storage, apheresis platelets with less leukocytes express IL-8 lower.
Blood Platelets ; metabolism ; CD40 Ligand ; blood ; Cell Separation ; methods ; Chemokine CCL5 ; blood ; Cytokines ; blood ; Humans ; Interleukin-8 ; blood ; Platelet Count ; Specimen Handling ; Transforming Growth Factor beta ; blood ; Vascular Endothelial Growth Factor A ; blood

Objective:To investigate the distribution and antimicrobial resistance profile of clinical bacteria isolated from blood culture in China.Methods:The clinical bacterial strains isolated from blood culture from member hospitals of Blood Bacterial Resistant Investigation Collaborative System (BRICS) were collected during January 2018 to December 2019. Antibiotic susceptibility tests were conducted with agar dilution or broth dilution methods recommended by US Clinical and Laboratory Standards Institute (CLSI). WHONET 5.6 was used to analyze data.Results:During the study period, 14 778 bacterial strains were collected from 50 hospitals, of which 4 117 (27.9%) were Gram-positive bacteria and 10 661(72.1%) were Gram-negative bacteria. The top 10 bacterial species were Escherichia coli (37.2%), Klebsiella pneumoniae (17.0%), Staphylococcus aureus (9.7%), coagulase-negative Staphylococci (8.7%), Pseudomonas aeruginosa (3.7%), Enterococcus faecium (3.4%), Acinetobacter baumannii(3.4%), Enterobacter cloacae (2.9%), Streptococci(2.8%) and Enterococcus faecalis (2.3%). The the prevalence of methicillin-resistant S. aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus were 27.4% (394/1 438) and 70.4% (905/1 285), respectively. No glycopeptide-resistant Staphylococcus was detected. More than 95% of S. aureus were sensitive to amikacin, rifampicin and SMZco. The resistance rate of E. faecium to vancomycin was 0.4% (2/504), and no vancomycin-resistant E. faecalis was detected. The ESBLs-producing rates in no carbapenem-resistance E. coli, carbapenem sensitive K. pneumoniae and Proteus were 50.4% (2 731/5 415), 24.6% (493/2001) and 35.2% (31/88), respectively. The prevalence of carbapenem-resistance in E. coli and K. pneumoniae were 1.5% (85/5 500), 20.6% (518/2 519), respectively. 8.3% (27/325) of carbapenem-resistance K. pneumoniae was resistant to ceftazidime/avibactam combination. The resistance rates of A. baumannii to polymyxin and tigecycline were 2.8% (14/501) and 3.4% (17/501) respectively, and that of P. aeruginosa to carbapenem were 18.9% (103/546). Conclusions:The surveillance results from 2018 to 2019 showed that the main pathogens of bloodstream infection in China were gram-negative bacteria, while E. coli was the most common pathogen, and ESBLs-producing strains were in majority; the MRSA incidence is getting lower in China; carbapenem-resistant E. coli keeps at a low level, while carbapenem-resistant K. pneumoniae is on the rise obviously.

Quality marker(Q-marker) is a new concept and pattern for quality control of traditional Chinese medicine(TCM),which will lead the development direction for quality control of TCM.Among them,how to characterize the overall quality attribute of TCM and its biological effect,is a critical scientific problem in the study of Q-marker.In this paper,integrated pharmacology is utilized to screen out and confirm the Q-marker from the complex system of TCM,so as to solve the critical scientific problem.System biology in vivo is firstly applied to establish the correlation of chemical fingerprints of TCM,their metabolic fingerprints,network targets,biological effects and efficacy of TCM,which is used to preliminary screen out Q-marker of TCM.Following that,a pharmacological method in vitro,including intestinal absorption in vitro coupled with bioactivity assessment,is employed to simultaneously determine the absorbed doses of TCM and evaluate their biological activity.Furthermore,data mining is utilized to establish the exact quantitative mathematic model between Q-marker of TCM and bioactivity.Meanwhile,two representative examples,including Yuanhu Zhitong tablets,Xinsuning capsules,are introduced to identify Q-marker of TCM and establish their quality standards related with bioactivity,which will be beneficial to improve the level of quality control of TCM and ensure the effectiveness and safety of clinical applications.

Objective: To systematically introduce the design of case-cohort study and the statistical methods of relative risk estimation and their application in the design. Methods: First, we introduced the basic principles of case-cohort study design. Secondly, Prentice's method, Self-Prentice method and Barlow method were described in the weighted Cox proportional hazard regression models in detail, finally, the data from the Shanghai Women's Health Study were used as an example to analyze the association between obesity and liver cancer incidence in the full cohort and case-cohort sample, and the results of parameters from each method were compared. Results: Significant association was observed between obesity and risk for liver cancer incidence in women in both the full cohort and the case-cohort sample. In the Cox proportional hazard regression model, the partial regression coefficients of the full cohort and the case-cohort sample fluctuated with the adjustment of confounding factors, but the hazard ratio estimates of them were close. There was a difference in the standard error of the partial regression coefficient between the full cohort and the case-cohort sample. The standard error of the partial regression coefficient of the case-cohort sample was larger than that of the full cohort, resulting in a wider 95% confidence interval of the relative risk. In the weighted Cox proportional hazard regression model, the standard error of the partial regression coefficient of Prentice's method was closer to the parameter estimates from full cohort than Self-Prentice method and Barlow method, and the 95% confidence interval of hazard ratio was closer to that of the full cohort. Conclusions: Case-cohort design could yield parameter results closer to the full cohort by collecting and analyzing data from sub-cohort members and patients with the disease, and reduce sample size and improve research efficiency. The results suggested that Prentice's method would be preferred in case-cohort design.
China/epidemiology* ; Cohort Studies ; Female ; Humans ; Proportional Hazards Models ; Risk ; Sample Size