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: 9927445
• 负责人: Erwing Fabian Cardozo Ojeda
• 金额: $ 46.41万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH 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/9927445
• 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; Data; Dose; Drug Kinetics; Encapsulated; Fostering; Fred Hutchinson Cancer Research Center; Gene-Modified; Genetic Variation; Goals; HIV; HIV Infections; HIV antiretroviral; HIV therapy; Health; Home environment; Human; Immunologics; Individual; Infrastructure; Infusion procedures; Ingestion; Interruption; Intervention; Investigation; 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; Translations; Treatment Efficacy; United States National Institutes of Health; Vaccination; Vaccine Therapy; Viral; Virus Replication; antiproliferative agents; antiretroviral therapy; care costs; collaboratory; combinatorial; control theory; curative treatments; design; 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; stem cells; synthetic antibodies; theories; 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.

项目摘要 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活，但 需要每天服用药丸，以避免进展为艾滋病和进一步的艾滋病毒传播。多种治疗 目前正在考虑采取战略，以实现对艾滋病毒的功能性治愈。然而，迄今为止，没有一种单一的方法 获得了足够的HIV功能性治愈的效力。因此，越来越多的人认为， 需要多管齐下。本建议的目的是确定最佳和可行的 使用经数据验证的研究性治疗方法的组合， 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的 治疗组合的机制，通过将观察到的动力学和效力与各种可量化的 结果测量。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， 将目前正在研究的治疗性干预措施的结果数据纳入可能的竞争机制， 包括不同储库细胞亚群的水平、病毒量、病毒多样性和病毒反弹的时间。 模型选择理论将被用来确定最简约的模型，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，以进行计算机模拟。 实验我们将列出所有合理的治疗方法组合，并对每种组合进行建模。我们 将通过使用 从拟合获得的参数化和通过调整包括给药的每种治疗的参数， 日程安排和治疗顺序。这一建议是重要的，因为测试所有可能的组合， 这些方法是不切实际的，非常耗时且昂贵。无法严格评估所有 潜在办法是实现最佳结果的一个关键障碍。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，在这个框架中， 考虑干预措施，并与确定最有可能的联合治疗的潜力进行比较。 将实现功能性治愈。