• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

相似文献

1
A survey of population analysis methods and software for complex pharmacokinetic and pharmacodynamic models with examples.复杂药代动力学和药效学模型的群体分析方法及软件综述,并附实例
AAPS J. 2007 Mar 2;9(1):E60-83. doi: 10.1208/aapsj0901007.
2
Parametric and nonparametric population methods: their comparative performance in analysing a clinical dataset and two Monte Carlo simulation studies.参数和非参数总体方法:它们在分析临床数据集和两项蒙特卡罗模拟研究中的比较性能。
Clin Pharmacokinet. 2006;45(4):365-83. doi: 10.2165/00003088-200645040-00003.
3
Performance of different population pharmacokinetic algorithms.不同群体药代动力学算法的性能。
Ther Drug Monit. 2011 Oct;33(5):583-91. doi: 10.1097/FTD.0b013e318232bc61.
4
Overview of model-building strategies in population PK/PD analyses: 2002-2004 literature survey.群体药代动力学/药效学分析中模型构建策略概述:2002 - 2004年文献调查
Br J Clin Pharmacol. 2007 Nov;64(5):603-12. doi: 10.1111/j.1365-2125.2007.02975.x. Epub 2007 Aug 15.
5
Comparing the performance of FOCE and different expectation-maximization methods in handling complex population physiologically-based pharmacokinetic models.比较FOCE与不同期望最大化方法在处理复杂群体生理药代动力学模型方面的性能。
J Pharmacokinet Pharmacodyn. 2016 Aug;43(4):359-70. doi: 10.1007/s10928-016-9476-y. Epub 2016 May 23.
6
Fisher information matrix for nonlinear mixed effects multiple response models: evaluation of the appropriateness of the first order linearization using a pharmacokinetic/pharmacodynamic model.非线性混合效应多响应模型的费希尔信息矩阵:使用药代动力学/药效学模型评估一阶线性化的适用性
Stat Med. 2009 Jun 30;28(14):1940-56. doi: 10.1002/sim.3573.
7
Evaluation of the nonparametric estimation method in NONMEM VI.NONMEM VI中无参数估计方法的评估。
Eur J Pharm Sci. 2009 Apr 11;37(1):27-35. doi: 10.1016/j.ejps.2008.12.014. Epub 2008 Dec 30.
8
Pk-fit: a pharmacokinetic/pharmacodynamic and statistical data analysis software.Pk-fit:一款药代动力学/药效学及统计数据分析软件。
Comput Biomed Res. 2000 Oct;33(5):315-29. doi: 10.1006/cbmr.2000.1548.
9
Evaluation of uncertainty parameters estimated by different population PK software and methods.不同群体药代动力学软件和方法所估计的不确定性参数评估。
J Pharmacokinet Pharmacodyn. 2007 Jun;34(3):289-311. doi: 10.1007/s10928-006-9046-9. Epub 2007 Jan 10.
10
Approaches to handling pharmacodynamic baseline responses.处理药效学基线反应的方法。
J Pharmacokinet Pharmacodyn. 2008 Jun;35(3):269-83. doi: 10.1007/s10928-008-9088-2. Epub 2008 Apr 30.

引用本文的文献

1
Non-linear mixed-effects modelling and population-based model selection for I kinetics in benign thyroid disease.良性甲状腺疾病中碘动力学的非线性混合效应建模与基于群体的模型选择
EJNMMI Phys. 2025 Apr 8;12(1):37. doi: 10.1186/s40658-025-00735-6.
2
Leveraging Buprenorphine and Halofantrine as Tool Molecules to Develop a Novel Semi-Physiologically based Pharmacokinetic Model Accounting for Gastro-Intestinal Lymphatic Absorption and Enabling Cross-Species Translation.利用丁丙诺啡和卤泛群作为工具分子,开发一种新型的基于半生理学的药代动力学模型,该模型考虑了胃肠道淋巴吸收并实现跨物种翻译。
AAPS J. 2025 Mar 26;27(3):67. doi: 10.1208/s12248-025-01053-6.
3
The distinctive pharmacokinetic profile of rezafungin, a long-acting echinocandin developed in the era of modern pharmacometrics.瑞扎芬净独特的药代动力学特征,这是一种在现代药物计量学时代研发的长效棘白菌素。
J Antimicrob Chemother. 2025 Jan 3;80(1):18-28. doi: 10.1093/jac/dkae415.
4
Enabling population protein dynamics through Bayesian modeling.通过贝叶斯建模实现人口蛋白质动力学。
Bioinformatics. 2024 Aug 2;40(8). doi: 10.1093/bioinformatics/btae484.
5
Population pharmacokinetics of intravenous daptomycin in critically ill patients: implications for selection of dosage regimens.达托霉素静脉给药在重症患者中的群体药代动力学:对给药方案选择的启示
Front Pharmacol. 2024 May 2;15:1378872. doi: 10.3389/fphar.2024.1378872. eCollection 2024.
6
Advancing Precision Medicine: A Review of Innovative In Silico Approaches for Drug Development, Clinical Pharmacology and Personalized Healthcare.推进精准医学:药物研发、临床药理学和个性化医疗中创新的计算机模拟方法综述。
Pharmaceutics. 2024 Feb 27;16(3):332. doi: 10.3390/pharmaceutics16030332.
7
Population pharmacokinetic rationale for intravenous contezolid acefosamil followed by oral contezolid dosage regimens.群体药代动力学:注射用头孢洛林酯富马酸与口服头孢洛林酯给药方案的相关性。
Antimicrob Agents Chemother. 2024 Apr 3;68(4):e0140023. doi: 10.1128/aac.01400-23. Epub 2024 Feb 28.
8
Central Nervous System Antimicrobial Exposure and Proposed Dosing for Anthrax Meningitis.中枢神经系统抗菌药物暴露和炭疽性脑膜炎的推荐剂量。
Clin Infect Dis. 2024 Jun 14;78(6):1451-1457. doi: 10.1093/cid/ciae093.
9
Comprehensive stability analysis of 13 β-lactams and β-lactamase inhibitors in media, and novel supplement dosing strategy to mitigate thermal drug degradation.在介质中对 13 种β-内酰胺类抗生素和β-内酰胺酶抑制剂进行综合稳定性分析,并提出新的补充剂量策略以减轻热药物降解。
Antimicrob Agents Chemother. 2024 Mar 6;68(3):e0139923. doi: 10.1128/aac.01399-23. Epub 2024 Feb 8.
10
Population pharmacokinetics and humanized dosage regimens matching the peak, area, trough, and range of amikacin plasma concentrations in immune-competent murine bloodstream and lung infection models.人群药代动力学和基于氨基糖苷类药物血药峰浓度、药时曲线下面积、谷浓度及波动度的人优化给药方案在免疫正常的鼠血流感染和肺部感染模型中的应用。
Antimicrob Agents Chemother. 2024 Mar 6;68(3):e0139423. doi: 10.1128/aac.01394-23. Epub 2024 Jan 30.

本文引用的文献

1
Model for intracellular Lamivudine metabolism in peripheral blood mononuclear cells ex vivo and in human immunodeficiency virus type 1-infected adolescents.外周血单个核细胞离体及人类免疫缺陷病毒1型感染青少年细胞内拉米夫定代谢模型
Antimicrob Agents Chemother. 2006 Aug;50(8):2686-94. doi: 10.1128/AAC.01637-05.
2
Diazepam pharamacokinetics from preclinical to phase I using a Bayesian population physiologically based pharmacokinetic model with informative prior distributions in WinBUGS.使用WinBUGS中具有信息先验分布的贝叶斯群体生理药代动力学模型,从临床前到I期的地西泮药代动力学。
J Pharmacokinet Pharmacodyn. 2006 Oct;33(5):571-94. doi: 10.1007/s10928-006-9023-3. Epub 2006 Jun 29.
3
Pharmacokinetic-pharmacodynamic modelling: history and perspectives.药代动力学-药效学建模:历史与展望
J Pharmacokinet Pharmacodyn. 2006 Jun;33(3):227-79. doi: 10.1007/s10928-005-9002-0. Epub 2006 Jan 11.
4
Propagation of population pharmacokinetic information using a Bayesian approach: comparison with meta-analysis.使用贝叶斯方法传播群体药代动力学信息:与荟萃分析的比较。
J Pharmacokinet Pharmacodyn. 2005 Aug;32(3-4):401-18. doi: 10.1007/s10928-005-0048-9.
5
Non-linear mixed effects modeling - from methodology and software development to driving implementation in drug development science.非线性混合效应建模——从方法学与软件开发到推动药物研发科学中的应用
J Pharmacokinet Pharmacodyn. 2005 Apr;32(2):161-83. doi: 10.1007/s10928-005-0062-y. Epub 2005 Nov 7.
6
Pharmacokinetic-pharmacodynamic-efficacy analysis of efalizumab in patients with moderate to severe psoriasis.依法利珠单抗治疗中重度银屑病患者的药代动力学-药效学-疗效分析
Pharm Res. 2005 Jul;22(7):1088-100. doi: 10.1007/s11095-005-5642-4. Epub 2005 Jul 22.
7
Analysis of population pharmacokinetic data using NONMEM and WinBUGS.使用NONMEM和WinBUGS对群体药代动力学数据进行分析。
J Biopharm Stat. 2005;15(1):53-73. doi: 10.1081/bip-200040824.
8
Estimating bias in population parameters for some models for repeated measures ordinal data using NONMEM and NLMIXED.使用NONMEM和NLMIXED估计一些重复测量有序数据模型中总体参数的偏差。
J Pharmacokinet Pharmacodyn. 2004 Aug;31(4):299-320. doi: 10.1023/b:jopa.0000042738.06821.61.
9
Estimation of population pharmacokinetic parameters in the presence of non-compliance.存在不依从性情况下的群体药代动力学参数估计
J Pharmacokinet Pharmacodyn. 2003 Feb;30(1):53-81. doi: 10.1023/a:1023297426153.
10
Bayesian analysis of population PK/PD models: general concepts and software.群体药代动力学/药效学模型的贝叶斯分析:一般概念与软件
J Pharmacokinet Pharmacodyn. 2002 Jun;29(3):271-307. doi: 10.1023/a:1020206907668.

复杂药代动力学和药效学模型的群体分析方法及软件综述,并附实例

A survey of population analysis methods and software for complex pharmacokinetic and pharmacodynamic models with examples.

作者信息

Bauer Robert J, Guzy Serge, Ng Chee

机构信息

Pharmacokinetics, Pharmacodynamics, and Bioinformatics, XOMA (US) LLC, Berkeley, CA 94710, USA.

出版信息

AAPS J. 2007 Mar 2;9(1):E60-83. doi: 10.1208/aapsj0901007.

DOI:10.1208/aapsj0901007
PMID:17408237
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2751305/
Abstract

An overview is provided of the present population analysis methods and an assessment of which software packages are most appropriate for various PK/PD modeling problems. Four PK/PD example problems were solved using the programs NONMEM VI beta version, PDx-MCPEM, S-ADAPT, MONOLIX, and WinBUGS, informally assessed for reasonable accuracy and stability in analyzing these problems. Also, for each program we describe their general interface, ease of use, and abilities. We conclude with discussing which algorithms and software are most suitable for which types of PK/PD problems. NONMEM FO method is accurate and fast with 2-compartment models, if intra-individual and interindividual variances are small. The NONMEM FOCE method is slower than FO, but gives accurate population values regardless of size of intra- and interindividual errors. However, if data are very sparse, the NONMEM FOCE method can lead to inaccurate values, while the Laplace method can provide more accurate results. The exact EM methods (performed using S-ADAPT, PDx-MCPEM, and MONOLIX) have greater stability in analyzing complex PK/PD models, and can provide accurate results with sparse or rich data. MCPEM methods perform more slowly than NONMEM FOCE for simple models, but perform more quickly and stably than NONMEM FOCE for complex models. WinBUGS provides accurate assessments of the population parameters, standard errors and 95% confidence intervals for all examples. Like the MCPEM methods, WinBUGS's efficiency increases relative to NONMEM when solving the complex PK/PD models.

摘要

本文概述了当前的群体分析方法,并评估了哪些软件包最适合各种药代动力学/药效学(PK/PD)建模问题。使用程序NONMEM VI测试版、PDx-MCPEM、S-ADAPT、MONOLIX和WinBUGS解决了四个PK/PD示例问题,并对这些程序在分析这些问题时的合理准确性和稳定性进行了非正式评估。此外,我们还描述了每个程序的一般界面、易用性和功能。最后,我们讨论了哪些算法和软件最适合哪种类型的PK/PD问题。如果个体内和个体间差异较小,NONMEM FO方法对于二室模型准确且快速。NONMEM FOCE方法比FO方法慢,但无论个体内和个体间误差大小,都能给出准确的群体值。然而,如果数据非常稀疏,NONMEM FOCE方法可能会导致值不准确,而拉普拉斯方法可以提供更准确的结果。精确期望最大化(EM)方法(使用S-ADAPT、PDx-MCPEM和MONOLIX执行)在分析复杂的PK/PD模型时具有更高的稳定性,并且对于稀疏或丰富的数据都能提供准确的结果。对于简单模型,MCPEM方法的执行速度比NONMEM FOCE慢,但对于复杂模型,其执行速度比NONMEM FOCE更快且更稳定。WinBUGS为所有示例提供了群体参数、标准误差和95%置信区间的准确评估。与MCPEM方法一样,在解决复杂的PK/PD模型时,WinBUGS相对于NONMEM的效率会提高。