Background: Many pharmacologic studies record data as binary, yes-or-no, variables with analysis using logistic regression. In a previous study, it was shown that estimates of C50, the drug concentration associated with a 50% probability of drug effect, were unbiased, whereas estimates ofγ, the term describing the steepness of the concentration-effect relationship, were biased when sparse data were naively pooled for analysis. In this study, it was determined whether mixed-effects analysis improved the accuracy of parameter estimation. Methods: Pharmacodynamic studies with binary, yes-or-no, responses were simulated and analyzed with NONMEM. The bias and coefficient of variation of C50 and γ estimates were determined as a function of numbers of patients in the simulated study, the number of simulated data points per patient, and the “true” value of γ. In addition, 100 sparse binary human data sets were generated from an evaluation of midazolam for postoperative sedation of adult patients undergoing cardiac surgery by random selection of a single data point (sedation score vs. midazolam plasma concentration) from each of the 30 patients in the study. C50 andγwere estimated for each of these data sets by using NONMEM and were compared with the estimates from the complete data set of 656 observations. Results: Estimates of C50 were unbiased, even for sparse data (one data point per patient) with coefficients of variation of 30-50%. Estimates ofγwere highly biased for sparse data for all values ofγ greater than 1, and the value ofγwas overestimated. Unbiased estimation ofγrequired 10 data points per patient. The coefficient of variation ofγestimates was greater than that of the C50 estimates. Clinical data for sedation with midazolam confirmed the simulation results, showing an overestimate ofγwith sparse data. Conclusion: Although accurate estimations of C50 from sparse binary data are possible, estimates ofγare biased. Data with 10 or more observations per patient is necessary for accurate estimations ofγ.

Enterohepatic recirculation (EHR) occurs via biliary excretion and intestinal reabsorption of a drug. Drug recycling through EHR can lead to a change in pharmacokinetic (PK) properties, such as reduced clearance (CL), extended half-life (T1/2) and increased plasma exposure (AUC). As a result, EHR may prolong the pharmacological effect of drugs. In the present study, the compound (Cpd A) was found to exhibit EHR in Rhesus monkeys associated with a reduction in CL (from 3.8 to 0.33Lh−1, IV; from 2.3 to 0.4Lh−1, PO), and an increase in T1/2 (from 0.9 to 18 h, IV) and in AUC (from 1.5 to 17.4gh/mL, IV; from 2.8 to 16.3gh/mL, PO), by comparing the PK in the monkeys via the interruption of EHR (bile-duct cannulation) with that in the intact monkeys. A population four-compartment model was constructed based on recirculation loops incorporating all possible inputs (bile secretion, a lag-time model for gall bladder emptying, routes and amounts of a single dose administration) to fully evaluate the EHR of Cpd A. The plasma concentrations versus time profiles predicted from the model had a good fit to the values observed in the subjects and were further simulated with 90% confidence interval to demonstrate its utility. Thus, the model could be applied as a useful tool to evaluate the drugs or compounds that undergo EHR in different species.

Aim To investigate the population pharmacokinetics of propofol administered by TCI in Chinese elderly patients. Methods Thirtytwo patients with ASA Ⅰ-Ⅱ, 65-82 years old, undergoing selective lower abdominal operation were studied. Propofol was administered by target-controlled infusion with Marsh parameter. The target plasma concentration was 3μg·mL-1. Radial arterial blood samples were collected and analyzed by reversed phase HPLC with fluorescence detection. Population pharmacokinetic modeling was performed using NONMEM. Inter-individual variability and intraindividual variability of propofol were estimated for clearances and volumes of distribution. The effects of age, body weight, lean body mass, gender, height, hemoglobin, total protein, albumin, creatinine, alanine aminotransferase (ALT), and aspartate aminotransferase (AST) were investigated. The effects of coadministered opioid drugs were also studied. Results The pharmacokinetics of propofol in the Chinese elderly patients was best described by a three-compartment open model. Lean body mass was found to be a covariate for system clearance at significant level (P＜01005). The clearance decreased linearly with age as well ( P < 01005) . The apparent volume of distribution for deep peripheral compartment (V3 ) was influenced by gender. Elderly female patients showed a higher value for V3 . Conclusion 　The pharmacokinetics of propofol administered by TCI in Chinese elderly patients can be well described by a threecompartment open model . Inclusion of age , lean body mass and gender as covariates significantly improved the model . To ensure the accuracy and precision of target2controlled infusion , the population pharmacokinetic model applied to the individual patient should be adjusted reasonably.

目的 以环孢菌素（CSA）为模型药物，在NONMEM程序构建的群体药动学模型的基础上，通过EXCEL实现个体化给药。方法 以群体药动学模型为基础，采用1～2个实测的血药浓度点在EXCEL中运用最小二乘法估算每位病人个体间差异值。根据给药剂量、病人个体信息、个体间差异值和残留随机效应值进一步计算得出预测血药浓度值和预测血药浓度变异范围。结果 由实测的p0（谷浓度）为基础估算个体间差异值，进而得到的预测血药浓度与观测值拟合较好，优于采用p2（给药后2h浓度）、或p0加p2时所得的结果。结论在群体药动学系统分析的基础上，运用EXCEL通过1个血药浓度实测值可以实现个体化给药。