Mathematical modeling of optimal therapeutic combinations for HIV cure

HIV治愈最佳治疗组合的数学模型

• 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
• 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

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.

项目总结 抗逆转录病毒疗法(ART)抑制艾滋病毒复制，使感染者能够正常生存，但 需要每天服用避孕药，以避免发展为艾滋病和进一步的艾滋病毒传播。多重治疗 目前正在考虑实现艾滋病毒功能性治愈的战略。然而，到目前为止，还没有单一的方法 为艾滋病毒的功能性治愈提供了足够的效力。因此，越来越多的人同意艾滋病毒的治愈方法 将需要多管齐下。这项建议的目的是确定最佳和可行的 使用数据验证的研究治疗方法的组合来实现艾滋病毒的功能性治愈 数学模型。我们的假设是，经过数据验证的数学模型可以识别特定的 联合治疗的机制，通过将观察到的动力学和效力与各种可量化的 结果衡量标准。我们的具体目标将通过拟合不同的数学模型来验证这一假设 概括了相互竞争的可能机制，以从目前正在研究的治疗干预措施中产生数据， 包括不同存储细胞亚群的水平、病毒数量、病毒多样性和病毒反弹时间。 模型选择理论将被用来确定能够可靠地解释实验的最简约的模型 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，并在计算机上执行 实验。我们将列出所有看似合理的治疗方法组合，并为每种组合建模。我们 将创建组合剂量反应曲线，方法是使用 从FITS和通过调整包括剂量的每个治疗的参数获得的参数化， 日程安排和治疗顺序。这项建议意义重大，因为测试所有可能的组合 方法是不切实际的，过于耗时和昂贵。无法严格评估所有 潜在的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、量化的框架，在这个框架中，可用 考虑干预措施，并将其与确定哪种组合疗法最有可能的可能性进行比较 将实现一种功能性治愈。