Mathematical Models in Pharmacodynamics

药效学数学模型

• 批准号: 7094873
• 负责人: WILLIAM J. JUSKO
• 金额: $ 26.1万
• 依托单位: STATE UNIVERSITY OF NEW YORK AT BUFFALO
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-08-01 至 2010-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7094873
• 关键词: active sites; biomarker; cell cycle; drug administration rate /duration; drug interactions; drug metabolism; drug receptors; inhibitor /antagonist; mathematical model; pharmacokinetics; active sites; biomarker; cell cycle; drug administration rate /duration; drug interactions; drug metabolism; drug receptors; inhibitor /antagonist; mathematical model; pharmacokinetics

DESCRIPTION (provided by applicant): The major factors determining drug responses are the input and disposition rates controlling pharmacokinetics, drug distribution to the site of action (biophase), the mechanism of drug action in altering mediator or receptor levels, and turnover and transduction processes. A major advance in quantitating pharmacologic responses came from our recognition that diverse pharmacodynamic effects can be characterized using a family of four basic (and extended) indirect response models. These (and most) models require analysis using differential equations which usually cannot be fully solved analytically. This project seeks to characterize and quantify the general properties of drugs acting on turnover processes which are important for numerous body functions, structures, or biomarkers. Our specific aims include continued development of extended indirect models for responses generated from a precursor pool as relevant for most hormones and endogenous substances, explore multi-pool lifespan based indirect response models accounting for variability of lifespans of most cells derived from the hematopoietic system, develop advanced models for drugs with target-mediated disposition accounting for several possible control factors and turnover of reactive sites as relevant for a growing array of biotechnology products, and extend indirect response models to handle several types of drug-drug interactions which describe natural synergy and apply to many joint effects of drugs such as immunosuppressants and chemotherapeutic agents. Advanced methods of calculus and simulations will be employed to seek exact or approximate solutions or behaviors for these models, to identify how the onset, extent, return, duration, integrals of response, and steady-state of responses are controlled, to recover parameters more easily from experimental data, and to discriminate among diverse models available to describe typical data. This research addresses the considerable need in drug development for better strategies for utilizing biomarkers and for quantitating and predicting drug effects. These efforts will yield improved insights and methods for understanding and characterizing the time-course of drug responses as related to major mechanisms of physiology and pharmacologic action.

描述（由申请人提供）：确定药物反应的主要因素是控制药代动力学的输入和处置率，对作用部位的药物分布（生物相），在改变介体或受体水平方面的药物作用机制，以及转移和转导过程。定量药理学反应的重大进步来自我们认识到，可以使用四个基本（和扩展）间接反应模型的家族来表征多种药效动力学效应。这些（和大多数）模型需要使用通常无法通过分析的微分方程进行分析。该项目旨在表征和量化作用于离职过程的药物的一般特性，这对于众多身体功能，结构或生物标志物很重要。我们的具体目的包括持续开发与大多数激素和内源物质相关的前体池产生的响应的扩展间接模型，探索基于多个寿命的基于多池寿命的响应模型，这些响应模型考虑了大多数细胞的可变性，这些细胞的可变性是从造血系统中的大多数细胞的变异性，这些响应是针对多个可能的对照组生长的对立型对立的药物和转移剂量偏离型偏置因子的高级模型的，并转移了介入介于介导的群体。生物技术产品，并扩展间接反应模型，以处理几种类型的药物相互作用，这些相互作用描述了天然协同作用，并适用于药物的许多关节作用，例如免疫抑制剂和化学治疗剂。将采用微积分和模拟的先进方法来寻求这些模型的精确或近似解决方案或行为，以确定如何控制发作，程度，返回，持续时间，持续时间，响应积分和稳态响应，以更轻松地从实验数据中恢复参数，并在各种模型中区分可用的模型以描述典型数据。这项研究探讨了药物开发的大量需求，以更好地利用生物标志物以及定量和预测药物作用。这些努力将产生改进的见解和方法，以理解和表征与生理学和药理作用的主要机制有关的药物反应时间。