Mathematical Models in Pharmacodynamics

药效学数学模型

• 批准号: 8324873
• 负责人: WILLIAM J. JUSKO
• 金额: $ 32.38万
• 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 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8324873
• 关键词: Advanced Development; Affect; Antineoplastic Agents; Behavior; Binding; Biological; Biological Markers; Calculi; Cells; Complex; Computer Simulation; Data; Data Set; Development; Disease; Dose; Drug Delivery Systems; Drug Kinetics; Drug effect disorder; Equation; Evaluation; Excision; Family; Goals; Hematopoietic; Homeostasis; Ligands; Link; Longevity; Mediating; Mediator of activation protein; Methodology; Methods; Modeling; Molecular Biology; Nature; Pattern; Pharmaceutical Preparations; Pharmacodynamics; Pharmacologic Actions; Pharmacotherapy; Physiological; Physiology; Plasma; Process; Production; Property; Regimen; Research; Research Design; Signal Transduction; Site; Solutions; Structure; System; Systems Biology; Testing; Therapeutic; Time; base; drug distribution; drug mechanism; experience; improved; insight; mathematical model; meetings; pharmacodynamic model; public health relevance; receptor; research study; response; simulation

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 quantifying 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 further analysis of extended indirect response models (with and without precursor compartments) for responses following multiple dose administration that are not predictable from single- dose studies; continued development of multiple-pool lifespan-based indirect response models that mimic hematopoietic and other cellular differentiation cascades for drugs capable of altering the turnover or life-span of natural cells; development of advanced pharmacodynamic models of target-mediated drug disposition for systems where drug action alters the turnover of target-expressing cells, drug competes with endogenous ligands, and the mechanism of drug binding is allosteric or noncompetitive in nature; and the development and evaluation of mechanism-based transit compartment pharmacodynamic models that can emulate cellular signal transduction cascades and bridge molecular biology and macro- scale pharmacodynamic responses with a focus on anticancer drugs. Advanced methods of calculus and simulations will be employed to seek exact or approximate solutions or behaviors of these models to identify how the onset, extent, return, duration, integrals of response (flux), and steady-states of response are controlled, to recover meaningful parameters more easily from experimental data, and to discriminate among diverse models available to describe typical data sets. These efforts will yield improved insights and methods for understanding and characterizing the time-course of drug responses as related to major drug- and system-specific properties manifesting from mechanisms of physiology and pharmacologic action. PUBLIC HEALTH RELEVANCE: The major factors determining the intensity and time-course of drug responses are related to how the body processes the drug, pharmacologic mechanisms of action, and turnover of physiologic structures and functions. These drug and system properties are complex. This proposal seeks to utilize mathematical and computer modeling to improve the understanding of how drugs elicit their effects. Such efforts enable the integration of large amounts of information to efficiently explore new drug targets and provide methods for improving utilization of current drugs for treating various diseases.

描述（由申请人提供）：决定药物反应的主要因素是控制药代动力学的输入和处置速率、药物分布到作用位点（生物相）、改变介质或受体水平的药物作用机制以及周转和转导过程。量化药理反应的重大进展来自于我们认识到可以使用四个基本（和扩展）间接反应模型来表征不同的药效效应。这些（以及大多数）模型需要使用微分方程进行分析，而微分方程通常无法完全解析求解。该项目旨在表征和量化作用于周转过程的药物的一般特性，这对于许多身体功能、结构或生物标志物很重要。我们的具体目标包括进一步分析扩展的间接反应模型（有或没有前体隔室），以了解单剂量研究无法预测的多剂量给药后的反应；继续开发基于多池寿命的间接反应模型，模拟造血和其他细胞分化级联，寻找能够改变自然细胞更新或寿命的药物；为药物作用改变靶标表达细胞的周转、药物与内源配体竞争以及药物结合机制本质上是变构或非竞争性的系统开发靶标介导的药物处置的先进药效学模型；开发和评估基于机制的转运室药效学模型，该模型可以模拟细胞信号转导级联并桥接分子生物学和宏观药效学反应，重点关注抗癌药物。将采用先进的微积分和模拟方法来寻求这些模型的精确或近似解决方案或行为，以确定如何控制响应的开始、程度、返回、持续时间、响应积分（通量）和响应稳态，以恢复更容易地从实验数据中提取有意义的参数，并区分可用于描述典型数据集的各种模型。这些努力将产生改进的见解和方法，用于理解和表征与生理学和药理作用机制表现出来的主要药物和系统特定特性相关的药物反应的时间过程。 公共卫生相关性：决定药物反应强度和时程的主要因素与身体如何处理药物、药理作用机制以及生理结构和功能的更新有关。这些药物和系统的特性很复杂。该提案旨在利用数学和计算机模型来增进对药物如何产生作用的理解。这些努力使得整合大量信息能够有效地探索新的药物靶点，并为提高现有药物治疗各种疾病的利用率提供方法。