Statistical Methods for Long-Term HIV Dynamic Modeling and Design

描述(申请人提供)：病毒动力学研究是最近艾滋病毒/艾滋病研究中最重要的进展之一，以了解艾滋病毒的发病机制和抗逆转录病毒(ARV)治疗。然而，大多数研究集中在短期病毒动力学上，其中的模型可能不适用于长期动力学。以生理为基础的数学模型和统计方法在艾滋病研究中发挥着关键作用。在长期治疗过程中，建立病毒学应答(VR)与抗逆转录病毒(ARV)治疗的关系是开发有效治疗方法的关键。这是一项具有挑战性的任务，因为一个实用的模型必须包含多种治疗因素，包括但不限于药物浓度、药物依从性、药物敏感性。病毒动力学可以通过微分方程式来模拟，但在估计和评估这种微分方程式模型的统计方法方面只有有限的发展。该项目的目标是通过具有时变系数但没有闭合形式解的微分方程组来开发病毒动力学模型，并将其应用于表征病毒的长期动力学。这一建议的目标1是：(A)研究抗逆转录病毒疗法下艾滋病毒/T细胞动力学和病毒学/免疫学反应的模型，纳入时变的药效、药代动力学、药物依从性和耐药性；(B)开发灵活的方法来拟合贝叶斯非线性混合效应模型，其中纳入了患者之间的动力学变化；这些方法的基本原理已经确立，但方法的应用在时变系数的非线性微分方程组的背景下是创新的，但没有闭合形式的解。目的2是将所开发的模型和方法应用于艾滋病临床试验，并通过模拟对模型进行评估。它将集中于：(A)验证模型和方法；(B)探索VR和药物浓度之间的药效学关系，结合药物依从性和耐药性等其他混杂因素来表征VR和药物浓度，并确定是VR的关键决定因素的临床因素；(C)评估艾滋病临床试验中使用的方案设计在产生预期反应方面的有效性，从而在剂量水平、受试者数量、结果监测的时机和频率方面指导抗逆转录病毒疗法的选择。这项拟议的研究将在临床因素在调节ARV疗法长期有效性方面的作用方面提供新的线索，从而更好地了解艾滋病毒的发病机制和长期病毒学反应，并可能在理解针对现有疗法的临床试验设计的定量评估方面取得重大进展。虽然这项提案将集中于艾滋病毒动力学，但纵向动态系统的基本概念和本项目中提出的方法一般适用于其他领域的动态系统，如PK/PD研究、生物医学和公共卫生，只要它们满足相关的技术规范--一组微分方程式。 与公共卫生有关：艾滋病流行病仍然是世界范围内严重的公共卫生威胁。HIV动态研究对了解HIV的发病机制和艾滋病患者的抗病毒治疗策略具有重要意义。该项目的总体目标是开发长期的艾滋病毒动态模型和相关的统计方法，以确定作为病毒学反应的关键决定因素的临床因素，并提供定量指导，以根据剂量水平、受试者数量、结果监测的时间和频率来选择和设计抗逆转录病毒治疗。

DESCRIPTION (provided by applicant): The study of viral dynamics is one of the most important developments in recent HIV/AIDS research for understanding HIV pathogenesis and antiretroviral (ARV) therapies. However, most studies focused on short-term viral dynamics, and the models therein may not be applicable to long-term dynamics. Physiologically-based mathematical models and statistical methods play a critical role in AIDS research. Establishing the relationship of virologic responses (VR) to antiretroviral (ARV) therapy during long-term treatment is critical to the development of effective treatments. This is a challenging task because a practical model must incorporate multiple treatment factors including, but not limited to, drug concentration, drug adherence, drug susceptibility. Viral dynamics may be modeled through differential equations, but there has been only limited development in statistical methodologies for estimating and evaluating such differential equation models. The goals of this project are to develop viral dynamic models via systems of differential equations with time-varying coefficients but without a closed-form solution, and to apply them for characterizing long-term viral dynamics. Aim 1 of this proposal is to (a) study models for long-term HIV/T-cell dynamics and virologic/immunologic responses under ARV therapies, incorporating time-varying drug efficacy, pharmacokinetics, drug adherence and drug resistance; (b) develop flexible methods for fitting Bayesian nonlinear mixed-effects models which incorporate between-patient variations in dynamics; the basic principle of these methodologies were well established, but the applications of methods are nonetheless innovative within the context of a system of nonlinear differential equations of time-varying coefficient, but without a closed-form solution. Aim 2 is to apply the models and methods developed to AIDS clinical trials and to evaluate the models through simulations. It will focus on (a) validating the models and methods; (b) exploring pharmacodynamic relationships between VR and drug concentrations characterized by pharmacokinetic parameters in conjunction with other confounding factors such as drug adherence and resistance, and identifying clinical factors that are critical determinants of VR; (c) evaluating protocol designs used in AIDS clinical trials for their effectiveness in generating desired responses, therefore guiding the selection of ARV therapies with respect to level of dosing, number of subjects, timing and frequency of outcome monitoring. The proposed research will cast new lights on HIV dynamics in terms of the roles of clinical factors in mediating the long-term effectiveness of ARV therapies, hence a better understanding of HIV pathogenesis and long-term virologic responses, and will potentially lead to significant progress in understanding quantitative evaluation of clinical trial designs in response to existing therapies. Although this proposal will concentrate on HIV dynamics, the basic concept of longitudinal dynamic systems and the proposed methodologies in this project are generally applicable to dynamic systems in other fields such as PK/PD studies, biomedicine and public health as long as they meet the relevant technical specification-a set of differential equations. PUBLIC HEALTH RELEVANCE: The AIDS epidemic remains a grave public health threat world-wide. HIV dynamic studies have contributed significantly to the understanding of HIV pathogenesis and antiviral treatment strategies for AIDS patients. The overall goal of this project is to develop long-term HIV dynamic models and associated statistical methods for identifying clinical factors that are critical determinants of virological responses and for providing quantitative guidance to select and design antiretroviral treatments with respect to level of dosing, number of subjects, timing and frequency of outcome monitoring.