MATLAB软件在非线性药动学参数估算中的应用

目的:利用MATLAB软件拟合非线性药动学参数。方法:采用MATLAB软件的非线性回归拟合二室模型血管外给药的药-时数据。结果:MATLAB非线性算法与3p97软件拟合得到的药动学参数一致,通过实例验证了其处理非线性药动学问题的有效性。结论:MATLAB回归分析计算准确、方便、简单,并能显示直观的拟合曲线图,适用于估算非线性药室模型的药动学参数。     

基于遗传算法的药动学参数估算

目的:利用遗传算法全局和局部搜索力强的优势,进行非线性药动学参数估算。方法:以最小二乘法建立目标函数,拟合一室模型血管外给药的药-时数据。结果:遗传算法与传统经典方法拟合的药动学参数无显著性差异(P>0.05),通过算例验证了其处理非线性药动学问题的有效性。结论:遗传算法适用于估算非线性药室模型的药动学参数。     

高斯-牛顿法拟合一室模型药物血管外给药的药动学参数的电子表格程序

目的建立一种简便的一室模型药物血管外给药的药动学参数求解方法。方法采用残数法获得药动学参数初值,根据最小二乘方原理设计获取一室模型药物血管外给药的药动学参数（A,k,Bandka）的Excel表格程序。结果实例显示该Excel表格程序的拟合效果与DAS2.1.1药动学软件一致。结论利用Excel表格求算药动学参数是一种有效而简便的方法。     

基于Excel函数求解血管外给药二室模型的药动学及隔室模型参数

目的:建立以Excel函数求解血管外给药二室模型的药动学及隔室模型参数的方法。方法:采用残数法,利用Excel函数,逐步求解药动学和隔室模型参数。结果:基于Excel函数可直观演示血管外给药二室模型的药动学及隔室模型参数计算过程,结果与教材一致。结论:本方法操作简便、界面直观、结果可靠、易于推广,可用于临床教学或实验中药动学参数的计算。     

两种软件对血管外给药一二室模型 药动学参数的拟合效果

［摘要］目的比较两种软件对血管外给药一、二室模型药动学参数的拟合效果。方法采用DAS2.0软件药动学模块和SPSS12.0软件的非线性回归方法对一系列时间 血药浓度模拟数据，以及实测数据进行拟合。结果模拟结果显示SPSS12.0非线性回归方法拟合效果优于DAS2.0软件，但实测数据的拟合结果两者一致。结论SPSS12.0和DAS2.0软件的拟合效果均良好，可以作为血管外给药一、二室模型药动学参数的拟合方法。     

运用Excel VBA程序计算静脉注射一室模型药动学参数

目的:建立自动求算静脉注射一室模型药动学参数的计算机程序。方法:运用Excel VBA程序编制求算静脉注射一室模型药动学参数的计算代码,并应用文献数据实例计算验证。结果:应用本法处理文献数据,实际计算时间不足20 s,而所得结果与文献一致。结论:运用Excel VBA程序自动求算静脉注射一室模型药动学参数较简便、快速、精确。     

应用MATLAB求算静脉注射给药的药动学参数

目的:应用MATLAB求算静脉注射给药的药动学参数。方法:利用MATLAB的inline和nlinfit命令进行非线性拟合,求解药动学参数。结果:MATLAB可方便快速求解静脉注射给药途径下的各个药动学参数,结果与3P97计算结果相当。结论:本方法操作简便、界面直观、结果可靠、易于推广,可用于临床教学或实验中药动学参数的计算。     

应用非线性混合效应模型法考察儿童疾病因素对环孢素药动学的影响

目的:考察疾病因素对于环孢素A(CsA)在儿童体内药动学的影响,促进个体化用药。方法:收集150例包括再生障碍性贫血(AA)、嗜血细胞综合征(HPS)和难治性肾病综合征(RNS)不同病种患儿的CsA血药浓度数据和临床资料。采用非线性混合效应模型法考察疾病种类因素对于CsA药动学的影响。采用Bayesian最大后验概率法获取并比较CsA在不同病种患者中药动学参数的差异。用拟合优度(goodness-of-fit)、自举法(bootstrap)、直观预测检验法(VPC)、正态化预测分布误差(NPDE)对最终模型的预测性能进行验证。结果:最终模型药动学参数的群体典型值分别为:吸收速率常数(k_a)1.22 h^-1,吸收时滞时间(T_lag)0.45 h,表观分布容积(V_d)218.18 L,口服清除率(CL)14.45 L·h^-1。拟合优度、自举验证、VPC和NPDE结果表明最终模型稳定,预测结果可靠。模型结构显示只有患者的体质量和AST值是影响CsA清除率的显著性因素。CsA在AA、HPS和RNS患者中的药动学参数差异无显著性(P>0.05)。结论:本研究成功获取了CsA在儿童AA、HPS和RNS患者中的药动学参数,上述疾病因素不会显著影响CsA在儿童体内的药动学过程。     

微分法计算一室模型药物静脉滴注的药动学参数

目的:建立一种根据血药浓度线性消除的微分特征计算静脉滴注一室模型药物动力学参数的新方法。方法:通过微分方法分析单次静脉滴注一室模型药物的动力学特征,求出消除速度常数k和表观分布容积V等药动学参数。结果:模拟计算结果表明,该法具有良好的准确性。结论:以微分法计算静脉滴注给药一室模型药物的药动学参数,具有计算便捷、结果准确的优点。     

利用SPSS估算静脉给药过程的药动学参数

目的利用SPSS估算静脉给药过程的药动学参数.方法使用SPSS的非线性回归(nonlinear regression)拟合糖尿病肾病患者静脉滴注葛根素后(5mg·kg-1,60min)的药～时数据,并与3P87的拟合结果进行比较;利用源自于R2的Adjusted R2选择最佳室模型.结果SPSS估算的药动学参数准确可靠,与3P87的结果完全一致;依据统计学理论,Adjusted R2比R2更能反映模型的拟合度.结论SPSS适用于估算静脉滴注(或注射)过程的药动学参数;Adjusted R2适用于室模型的选择.     

基于Excel求解静脉注射给药隔室模型参数及药动学参数

目的:基于Excel建立一种简便的计算静脉注射给药药物动力学参数和隔室模型的方法。方法:采用残数法原理,利用Excel统计函数,逐步求解药物动力学参数和隔室模型参数。结果:基于Excel可直观演示静脉注射给药药动学参数和隔室模型参数计算过程,结果与教材一致。结论:基于残数法原理,Excel统计函数可用于临床教学或实验中药物动力学参数计算。     

基于Excel函数设计单室模型间歇静脉滴注给药方案

设计单室模型间歇静脉滴注给药方案。方法:根据药动学参数,用Excel编写程序。结果:输入t1/2、Vd、有效治疗范围等,可计算出给药时间间隔、滴注速度(k0),而且可绘制药-时曲线。结论:该方法适用于任何一种符合单室模型间歇静脉滴注给药特征的药物,可迅速得到所有结果,且简单、可靠、直观。     

常用实验设计方法的Excel实现

目的:探讨常用实验设计的Excel实现方法。方法:利用Excel函数RAND(),可得到大于等于0小于1的均匀分布随机数。使用RAND()*(b-a)+a生成a,b之间的随机实数。将随机数与受试对象的编号对应,按某种特定方式排列在Excel工作表中就可完成设计。结果:建立实验设计分组的Excel工作表后,进行常用实验设计时仅仅录入受试样本总数及需分配组数,不须再录入任何统计公式和命令,就能简单快速地得到实验设计的结论。结论:利用Excel能直观快速进行常用实验设计。     

恒速静脉滴注给药时二室模型的建立

在学习药物动力学的过程中,教材往往会给出模型、药一时曲线方程及其推导过程,但是药学本科教科书及国内相关参考书中几乎没有对恒速静脉滴注二室模型的建立进行探讨,如《生物药剂学与药物动力学》、《新编药物动力学》、《实用药物动力学》都未见有关内容。     

A Model with Separate Hepato-Portal Compartment ("First-Pass" Model): Fitting to Plasma Concentration-Time Profiles in Humans

Purpose. To demonstrate the value of "first-pass" pharmacokinetic models (FPMs) in which the hepato-portal (HP) system is kinetically separated from the central compartment in fitting pharmacokinetic data obtained after intravenous (IV) and oral administration. Methods. Plasma concentration-time profiles of an investigational drug obtained in six healthy subjects each received 4 mg as an intravenous (IV) bolus dose and 10 mg as an oral solution served as a real data example. The common three- and four-compartment models with the first-order absorption and lag time (3CM and 4CM, respectively) in which HP system is assumed to be part of the central compartment were used as alternative models. We tested also: (i) the sensitivity of the output of FPM to variations in its parameters assuming IV and oral administration; (ii) practical estimability of the FPM parameters by fitting it to 20 simulated noisy data sets; (iii) distinguishability of FPM, 3CM and 4CM by fitting them to the simulated data sets. Results. FPM was shown to give the best fit as compared to 3CM or 4CM in 5 subjects of 6. The sensitivity of FPM was sufficient for the sake of parameter estimation. The "individual" means of parameter estimates obtained after fitting simulated data did not differ significantly from the preselected values. The variance in "individual" estimates was dependent on the sampling frequency. FPM was demonstrated to be distinguishable among relevant models. Conclusions. FPM is preferable as compared to standard compartmen-tal models for drugs extensively taken up by the intestine and/or the liver, and may have a broad spectrum of applications.     

Topical Oral Cavity Pharmacokinetic Modeling of a Stannous Fluoride Dentifrice: An Unusual Two Compartment Model

A pharmacokinetic model was developed describing the pharmacokinetics of stannous fluoride in human subjects after oral topical application of a stannous fluoride dentifrice. Twenty subjects participated in an investigation of an experimental dentifrice. Subjects rinsed their mouths with the experimental dentifrice slurry. Saliva and plaque samples were obtained from the subjects at various times up to 6 h after administration. Samples were analyzed for total tin content, used as an analytical marker for the active stannous fluoride ingredient, using a graphite furnace atomic absorption spectrometer. The modeling indicates that there is an obvious kinetic relationship between saliva and plaque compartments and that stannous fluoride is very well retained in and slowly released from plaque (and oral surfaces) into saliva. Additionally, both compartments are simultaneously loaded during administration unlike typical systemic drug behavior, and the elimination rate “constant” from the central compartment (saliva) changes due to changes in salivary flow. Stannous fluoride is cleared from saliva rapidly but very well retained in gingival plaque. The model with simultaneous loading of plaque and saliva describes these observations and may account for the prolonged antiplaque and antigingivitis benefits of stannous fluoride. © 2009 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 98:3862–3870, 2009     

影响阻抗法测心输出量的参数及其临床应用

通过理论推导和临床应用证实了阻抗法测心输出量的3个重要参数,即血液电阻率、基础阻抗和阻抗值变化量对于心输出量的计算的重要影响。     

迭代二步法估算维拉帕米的群体药动学参数

目的 :为临床合理应用维拉帕米提供依据。方法 :53例高血压患者口服维拉帕米片 ,采用荧光分光光度法测定血浆中维拉帕米浓度 ,用迭代二步法估算维拉帕米的群体药动学参数 ,并与传统二步法的结果比较。结果 :迭代二步法估算维拉帕米的CL为(189 3±59 3)ml/(h·kg) ,Vd 为 (1 420±0 231)L/kg ,T1/2 为 (5 74±1 90)h ,与传统二步法拟合的结果基本一致。结论 :迭代二步法能较好地估算出维拉帕米的群体及个体药动学参数 ,可用于预测血药浓度及优化个体给药方案。     

A Compartment Model for the Membrane-Coated Fiber Technique Used for Determining the Absorption Parameters of Chemicals into Lipophilic Membranes

PURPOSE: The purpose of this work was to develop a compartment model for the membrane-coated fiber (MCF) technique for determining the absorption parameters of chemicals into lipophilic membranes. METHODS: A polymer membrane coated onto a section of inert fiber was used as a permeation membrane in the MCF technique. When MCFs were immersed into a donor solution, the compounds in the solution partitioned into the membrane. At a given permeation time, a fiber was removed from the solution and transferred into a gas chromatography injector for quantitative analysis. The permeation process of a given chemical from the donor phase into the membrane was described by a one-compartment model by assuming first-order kinetics. RESULTS: A mathematical model was obtained that describes the cumulative amount of a chemical permeated into the membrane as a function of the permeation time in an exponential equation. Two constants were introduced into the compartment model that were clearly defined by the physiochemical parameters of the system (a kinetic parameter and the equilibrium absorption amount) and were obtained by regression of the experimental data sampled over a limited time before equilibrium. The model adequately described the permeation kinetics of the MCF technique. All theoretical predictions were supported by the experimental results. The experimental data correlated well with the mathematical regression results. The partition coefficients, initial permeation rate, uptake, and elimination rate constants were calculated from the two constants. CONCLUSIONS: The compartment model can describe the absorption kinetics of the MCF technique. The regression method based on the model is a useful tool for the determination of the partition coefficients of lipophilic compounds when it takes too long for them to reach permeation equilibrium. The kinetic parameter and the initial permeation rate are unique parameters of the MCF technique that could be used in the development of quantitative structure-activity relationship models.