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）：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。量化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进一步分析扩展的间接响应模型（有和没有前体隔室），用于在单剂量研究中无法预测的多剂量给药后的响应；持续开发基于多个寿命的间接反应模型，以模仿造血和其他细胞分化级联，以改变自然细胞的营业额或寿命；针对药物作用改变靶向细胞，药物与内源性配体竞争以及药物结合机制的靶标介导的药物处置的先进药效学模型的开发，其本质上是变构的或不竞争的。以及基于机制的过境隔室药效学模型的开发和评估，这些模型可以模仿细胞信号转导级联，桥梁分子生物学以及宏观尺度的药物学反应，重点是抗癌药物。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（通量）和响应的稳态，以更轻松地从实验数据中恢复有意义的参数，并在实验数据中更容易地辨别有意义的模型，以描述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，以理解和表征与生理和药理作用机制相关的主要药物和系统特异性特性相关的药物反应时间。 公共卫生相关性：确定药物反应强度和时间课的主要因素与身体处理药物的处理方式，作用的药理机理以及生理结构和功能的更新有关。这些药物和系统特性很复杂。该建议旨在利用数学和计算机建模来提高对药物如何引起其影响的理解。这样的努力使大量信息能够有效地探索新药物，并提供改善当前药物治疗各种疾病的方法的方法。