Mathematical modeling of optimal therapeutic combinations for HIV cure

HIV治愈最佳治疗组合的数学模型

基本信息

批准号：
10540716
负责人：
Joshua Tisdell Schiffer
金额：
$ 46.59万
依托单位：
FRED HUTCHINSON CANCER CENTER
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-12-16 至 2024-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10540716
关键词：
Achievement Acquired Immunodeficiency Syndrome Acute Adult Aftercare Agreement CAR T cell therapy CD4 Positive T Lymphocytes Caring Cell Therapy Cells Characteristics Chronic Clinic Clinical Trials Collaborations Combined Modality Therapy Consensus Consumption Creativeness Data Dose Drug Kinetics Encapsulated Experimental Designs Fostering Fred Hutchinson Cancer Research Center Gene Modified Genetic Variation Goals HIV HIV Infections HIV antiretroviral HIV therapy Health protection Home Human Immunologics Individual Infrastructure Infusion procedures Ingestion Interruption Intervention Kinetics Link Longevity Lymphocyte Military Personnel Mission Modeling Outcome Outcome Measure Pattern Peptide antibodies Persons Probability Public Health Research Research Personnel Running Safety Schedule Site Testing Therapeutic Time Training Treatment Efficacy United States National Institutes of Health Vaccination Vaccine Therapy Viral Virus Replication antiproliferative agents antiretroviral therapy collaboratory combinatorial control theory cost curative treatments effective intervention experimental study gene therapy gene transplantation for gene therapy in silico in vivo innovation mathematical model multimodality nanoparticle nonhuman primate pill prevent process optimization programs response simulation social stigma stem cells synthetic antibodies theories translational therapeutics transmission process treatment duration viral rebound

项目摘要

PROJECT SUMMARY Antiretroviral therapy (ART) suppresses HIV replication and allows a normal lifespan for infected persons, but daily pill ingestion is required to avoid progression to AIDS and further HIV transmission. Multiple therapeutic strategies are being considered to achieve a functional cure for HIV. However, to date, no single approach has achieved sufficient potency for an HIV functional cure. Therefore, there is increasing agreement that an HIV cure will require a multi-pronged approach. This proposal has the objective to identify optimal and feasible combinations of investigational therapeutic approaches to achieve functional cure of HIV using data-validated mathematical models. Our hypothesis is that data-validated mathematical models can identify specific mechanisms of therapeutic combinations, by linking observed kinetics and potency with various quantifiable outcome measures. Our specific aims will validate this hypothesis by fitting different mathematical models that encapsulate competing possible mechanisms to outcome data from curative interventions currently under study, including levels of different reservoir cellular subset, viral quantities, viral diversity and time to viral rebound. Model selection theory will be used to identify the most parsimonious models that reliably explain experimental results. We will use the most parsimonious model that recapitulated the data from each study to perform in silico experiments. We will list all plausible combinations of therapeutic approaches and model each combination. We will create combinatorial dose-response curves by running simulations for each combination by using the parameterization obtained from the fits and by tuning the parameters for each therapy including dosing, scheduling, and order of treatment. This proposal is significant because testing all possible combinations of approaches is impractical, excessively time consuming and expensive. The inability to rigorously assess all potential approaches is a critical barrier to achieve optimal outcomes. Therefore, our proposal is innovative because we propose a rigorous, quantitative framework in which plausible combinations of available interventions are considered and compared with the potential to identify which combination therapies most likely will achieve a functional cure.

项目摘要抗逆转录病毒疗法（ART）抑制了HIV复制，并允许感染者正常的寿命，但需要每日药丸摄入以避免发展为艾滋病和进一步的艾滋病毒传播。多重治疗正在考虑实现艾滋病毒功能治疗的策略。但是，迄今为止，没有一种方法获得了足够的效力来治愈HIV功能。因此，越来越同意艾滋病毒治愈将需要多管齐全的方法。该建议的目标是确定最佳和可行使用数据验证的研究性治疗方法的组合以实现HIV的功能治疗数学模型。我们的假设是数据验证的数学模型可以识别特定通过将观察到的动力学和效力与各种可量化的效力联系起来的治疗组合机制结果措施。我们的具体目的将通过拟合不同的数学模型来验证这一假设封装竞争可能的机制，以从目前正在研究的治疗干预措施中结果数据，包括不同储层细胞子群的水平，病毒量，病毒多样性以及病毒反弹的时间。模型选择理论将用于识别最简约的模型，这些模型可靠地解释实验结果。我们将使用最简约的模型，该模型概括了每项研究的数据以在计算机中执行实验。我们将列出治疗方法的所有合理组合和每种组合的模型。我们将通过使用该组合来创建组合剂量响应曲线从拟合中获得的参数化并通过调整每种疗法的参数，包括给药，日程安排和治疗顺序。该提案很重要，因为测试所有可能的组合方法是不切实际的，耗时且昂贵的。无法严格评估所有潜在方法是实现最佳结果的关键障碍。因此，我们的建议是创新的因为我们提出了一个严格的定量框架，其中可用的合理组合考虑了干预措施，并将其与识别最有可能结合疗法的潜力进行了比较将实现功能性治疗。