中药药代动力学研究的难点和热点

中药的药物代谢动力学(简称中药药代动力学)是借助于动力学原理，研究中草药活性成分、组分、中药单方和复方体内吸收、分布、代谢和排泄(ADME)的动态变化规律及其体内时量．时效关系，并用数学函数加以定量描述的一门边缘学科。它是中药药理学与药物代谢动力学相互结合、相互渗透而形成的。它借助于药代动力学的基本理论和方法研究中草药，中草药药代动力学的研究也为药代动力学提出了新的课题。中药特别是中药方剂十分复杂，其药代动力学的研究较通常的化学药物的药代动力学更为困难，中药药代动力学必将大大促进药代动力学向更深层次的发展。     

人工神经网络在临床药学中应用近况

目的:介绍近五年来ANN在临床药学领域的应用进展,为临床药学的数据分析、模型建立、实时控制等方面提供有效的数学方法。方法:通过介绍近年来在药学领域应用较广泛、较成功的算法和模型,对ANN在药代动力学、药效学、临床治疗药物监测( TDM)等临床药学领域的应用进行分类和评价,总结ANN在实际应用中的优点和不足。结果和结论:与传统方法比较,ANN具有潜在的优势,在临床药学领域具有良好的应用前景目的:介绍近五年来ANN在临床药学领域的应用进展,为临床药学的数据分析、模型建立、实时控制等方面提供有效的数学方法。方法:通过介绍近年来在药学领域应用较广泛、较成功的算法和模型,对ANN在药代动力学、药效学、临床治疗药物监测(TDM)等临床药学领域的应用进行分类和评价,总结ANN在实际应用中的优点和不足。结果和结论:与传统方法比较,ANN具有潜在的优势,在临床药学领域具有良好的应用前景     

临床药理学讲座(10) 药代动力学与临床用药

药代动力学是应用动力学原理研究药物在体内吸收、分布、生物转化和排泄过程的速度规律(即时间过程)的科学,并用教学方程定量地预测这些过程的性质。 它的研究内容包括:(1)找出药物浓度与时间的关系,测求有关药代动力学参数;(2)应用药代动力     

应用药物转运体的药代动力学评价

药物转运体在药代动力学方面起到非常重要的作用,它与药物的吸收、分布、排泄、药效发挥、以及药物毒性作用等密切相关。基于转运体的药物间相互作用,还能影响到临床合并治疗药物之间的药代动力学关系。本研究室已经建立了一整套的实用于药代动力学研究和药物间相互作用评价,高效表达人药物转运体蛋白的体外筛选系统,并已将其应用于新药的筛选研究。此方法的特点在于,以表达人药物转运体蛋白的宿主培养细胞为研究对象,在临床前期提供与临床试验相似的研究结果,今后必将成为药物研发领域有用的评价方法。     

生理药代动力学软件模拟技术在药物研发和评价中的应用

生理药代动力学(physiologically-based pharmacokinetic, PBPK)软件模拟技术是通过计算机软件构建模型,模拟机体生理或病理环境,用以预测药物在体内的药代动力学行为(吸收、分布、代谢、排泄)。本综述概述了生理药代动力学模型的常用功能模块、在药物早期研发和新制剂研究、食物影响药物相互作用、儿童药物研究、吸入制剂开发及仿制药一致性评价等多方面的应用,并简要介绍了常用生理药代动力学软件的特点。讨论了生理药代动力学模型的当前挑战,包括模型建立的适用范围,模型准确性评估的判断标准等方面内容。     

滴眼剂人眼部药代动力学研究的方法学探讨

滴眼剂的人眼部药代动力学研究对眼科药物的开发及评价具有重要意义。本文对滴眼剂的眼部药代动力学特征、眼部药代动力学研究的设计要点、泪液及房水中药代动力学研究的设计及实施方法进行探讨。     

抗真菌药PK/PD研究进展

药代动力学/药效学(PK/PD)结合了PK与PD的研究方法,同步研究药代动力学特征及与药效和疗效的关系,定量描述药物的效应-时间过程。PK/PD研究有利于更有效地利用现有的抗真菌药物和提高其在许多严重真菌感染时的抗菌效果。本文就抗真菌药的PK/PD研究进展进行综述。     

人工神经网络在临床药学中应用近况

目的：介绍近五年来ANN在临床药学领域的应用进展，为临床药学的数据分析。模型建立，实时控制等方面，提供有效的数学方法。方法：通过介绍近年来在药学领域应用较广泛，较成功的算法和模型。对ANN在药代动力学，药效学，临床治疗药物监测（TDM）等临床药学领域的应用进行分类和评价。总结ANN在实际应用听 优点和不足。结果和结论；与传统方法比较，ANN具有潜在的优势，在临床药学领域具有良好的应用前景。     

药代动力学和药效动力学统一模型在抗心律失常药中的应用

探讨药物的剂量一药理效应的关系,一直是临床药理学研究的主要目的。长期以来,临床药理学研究的内容大都用药代动力学来描述体内药物浓度的经时过程。一般,药物的浓度与药理效应和毒性反应密切相关。已有大量的研究事实:在给药间隔时间内,产生最大药理效应(E_(max))时,药效的经时过程不依赖于可测得的药物浓度,但在E_(max)的20～80%之间,药物浓度与药理效应呈线性关系;有些药物的药理效应,是活性代谢产物或药物的药理效应累加引起的。这些结果均说明:给药方案的设计不能只根据药代动力学的数据,必须将药代动力学(PK)和药效动力学(PD)统一地结合起来。     

基于复杂网络与代谢组学的中药药代动力学研究思考与探索

药物研发模式的转变推动了药物评价技术体系的革新。中药药代动力学研究是中药现代化研究的重要组成部分,对于创新中药及现代中药复方研发具有重要意义。中药药代动力学理论近些年虽然取得了进步,但目前尚缺乏符合中药自身特征的药代动力学研究与评价技术体系。本文扼要介绍了中药药代动力学的研究现状、代谢组学及复杂网络理论,并在此基础上提出应用代谢组学和复杂网络方法来研究多组分药代动力学(网络药动学)的设想,以期揭示中药药效物质基础和作用机制。     

Clinical application of artificial neural network (ANN) modeling to predict pharmacokinetic parameters of severely ill patients

Artificial neural network (ANN) modeling was used to evaluate the pharmacokinetics of aminoglycosides (arbekacin sulfate and amikacin sulfate) in severely ill patients. The plasma level was predicted by ANN modeling using parameters related to the severity of the patient's condition and the predictive performance was shown to be better than could be achieved using multiple regression analysis. These results indicate that there is a non-linear relationship between the pharmacokinetics of aminoglycosides and the severity of the patient's condition, and this should be taken into account when determining the dose for severely ill patients. Patients whose plasma levels are likely to fall below the effective level can be identified by ANN modeling with a predictive sensitivity and specificity superior to multivariate logistic regression analysis. The predictable range should be inferred from the data structure before the modeling in order to improve the predictive performance. The volume of distribution (Vd) in the normal range was weakly predicted by ANN modeling from the patients' data. Prediction of clearance by ANN modeling was poorer than that obtained from serum creatinine concentration by linear regression analysis. These results suggest that the input-output relationship (linear or non-linear) should be taken into account in selecting the modeling method. Linear modeling can give better predictive performance for linear systems and non-linear modeling can give better predictive performance for non-linear systems. In general, the performance of ANN modeling was superior to linear modeling for PK/PD prediction. For accurate modeling, a predictable range should be inferred from the data structure before the analysis. Restriction of the predictable region, as determined from the data structure, produced an increase in prediction performance. When applying ANN modeling in clinical settings, the predictive performance and predictable region should be investigated in detail to avoid the risk of harm to severely ill patients.     

基于Excel的药动学数据分析程序——PKSlover 1.0的编写和验证

目的:编写并验证基于Excel的药动学数据分析通用程序。方法:利用Excel的内置函数、规划求解工具和VBA语言编制包括静注1房室、静注2房室、静注3房室、非脉管1室、非脉管1室(有时滞)、非脉管2室、非脉管2室(有时滞)、非房室模型分析、生物等效性分析以及缓控释制剂体内外相关分析共10个药动学数据分析模块,结合文献数据对比利用该程序以及3P87和Win-Nonlin软件处理得到的结果。结果:成功编制简明药动学数据处理程序———PKSolver 1.0,该程序与3P87和WinNonlin软件相比,所有药动学参数求算结果和模型选择判据结果基本一致。结论:该程序可参考用于常见药动学数据分析,更多的药动学数据分析模块尚待进一步开发。     

中药药动学研究评价模式的发展

中药是一个复杂的巨系统,其药效是其中多种化学成分相互作用所产生的综合效果。中药药动学研究经历了从“单成分、单靶点”到“多成分、多靶点”的转变,相应的药动学评价模式也经历了相似的发展过程,从最初针对单体成分的药动学研究,到以单成分研究单味中药及复方的药动学,再到多组分整合药动学,以及之后的以药动学一药效学结合模式评价复方药动学。对以上中药药动学评价模式的发展进行了初步探讨。     

复方盐酸二甲双胍格列吡嗪片在健康人体的药动学

目的:研究复方盐酸二甲双胍格列吡嗪片在健康中国人体内的药动学特征。方法:12位受试者(男女各半)在不同试验周期分别口服不同盐酸二甲双胍、格列吡嗪制剂。用HPLC-UV方法测定血浆中盐酸二甲双胍及格列吡嗪浓度。结果:试验所得各药动学参数与文献报道基本一致。经过统计学分析,复方盐酸二甲双胍格列吡嗪片中二成分与单独服用盐酸二甲双胍片及格列吡嗪片相比主要药动学参数差异无显著性,多剂量服药与单次服药相比主要药动学参数差异无显著性。结论:复方盐酸二甲双胍格列吡嗪片中两组分之间在体内不存在相互作用,多剂量服药与单次服药相比其体内药物动力学过程不发生改变。     

Development of gene drug delivery systems based on pharmacokinetic studies.

A series of pharmacokinetic studies following systemic or local administration for the development of delivery systems for gene drugs, such as plasmid DNA and oligonucleotides, are reviewed. The pharmacokinetics of gene drugs after intravenous injection into mice was evaluated based on clearance concepts. Pharmacokinetic analysis revealed that the overall disposition characteristics of the gene drug itself were determined by the physicochemical properties of its polyanionic DNA. Based on these findings, liver cell-specific carrier systems via receptor-mediated endocytosis were successfully developed by optimizing physicochemical characteristics. On the other hand, the pharmacokinetics of gene drugs after intratumoral injection were assessed in a tissue-isolated tumor perfusion system. The relationship between the physicochemical properties of gene drug delivery systems and intratumoral pharmacokinetics was determined and the therapeutic effect was also discussed in relation to pharmacokinetics. Collectively, it was demonstrated that a rational design of gene drug delivery systems that can control their in vivo disposition is possible by means of pharmacokinetic studies at whole body, organ and cellular levels.     

多组分、多靶点中药整体药代动力学研究的思考与探索

中药药代动力学研究是中药现代化研究链上一个不可分割的重要组成部分,在创新中药及现代复方中药研发中发挥着重要作用,但目前尚缺乏符合中药自身特征的药代动力学研究与评价技术体系,对于中药药代动力学学科关键科学问题的认识不够清晰。本文扼要概述了本课题组近年来在中药多组分整合药代动力学、体内外物质组分析、基于机制的方剂组分配伍规律研究及中药有效成分药代动力学研究进展,并试从面向中药现代化研究实际需求的角度,分析和讨论了中药药代动力学学科的关键科学问题,以期能够起到“抛砖引玉”的作用,共同促进我国中药药代动力学研究水平的提高。     

Population pharmacokinetic analysis of letrozole in Japanese postmenopausal women

Purpose  

Letrozole is an orally active aromatase inhibitor for the treatment of breast cancer. The objectives of this study were to examine the pharmacokinetic profile of letrozole in Japanese subjects and to identify factors that influence variability in the pharmacokinetics of letrozole using population pharmacokinetic (PPK) analysis.     

Pharmacokinetics and safety of golimumab, a fully human anti-TNF-alpha monoclonal antibody, in subjects with rheumatoid arthritis

Golimumab is a fully human antitumor necrosis factor alpha (TNF-alpha) monoclonal antibody that is being developed for intravenous and subcutaneous administration. To assess the pharmacokinetics and safety of the intravenous formulation of golimumab, 36 adult subjects with rheumatoid arthritis were randomly assigned to receive a single infusion of placebo or golimumab (0.1, 0.3, 1, 3, 6, or 10 mg/kg). Serum concentrations of golimumab were determined using a validated enzyme-linked immunosorbent assay method. In addition to the noncompartmental analysis and compartmental modeling, a population pharmacokinetics analysis using NONMEM was also conducted. Both the maximum serum concentration and the area under the serum concentrationtime curve appeared to increase in a dose-proportional manner. The median half-life ranged from 7 to 20 days. A 2-compartment population pharmacokinetic model adequately described the pharmacokinetics of golimumab. The following pharmacokinetic parameters (typical value [% coefficient of variation]) were estimated from the population pharmacokinetic model: clearance (CL: 0.40 [10.1%] L/d), volume of distribution in the central compartment (V(c): 3.07 [6.4%] L), intercompartmental clearance (Q: 0.42 [15.5%] L/d), and volume of distribution in the peripheral compartment (V(p): 3.68 [11.8%] L). Interindividual variability of the pharmacokinetic parameters was quantified for CL (44.3%), V(c) (25.5%), Q (44.6%), and V(p) (44.6%). Residual variability was estimated to be 15.0%. Body weight was found to be an important covariate on V(c). Golimumab was generally well tolerated. The pharmacokinetics of golimumab appeared to be linear over the dose range evaluated in this study.