Be part of launching a new scientific field - immunostimulation/ immunodynamic (IS/ID) mathematical modelling to accelerate vaccine development

疫苗一旦开发出来，就是拯救人类生命的最有效方法之一。但是，开发一种新的疫苗可能需要几十年的时间，耗资约10亿美元。目前用于确定正确疫苗剂量的科学方法是经验性的和过时的。相比之下，基于数学模型的药物开发（PK/PD）经常用于预测最佳药物剂量和使用时间表。药代动力学模型用于模拟药物随时间推移在体内的浓度，通常考虑药物的吸收、分布、代谢和排泄的4个阶段。药效学模型侧重于药物在吸收和排泄之间对身体的影响。这些工具可用于计算剂量，以将物质保持在有效浓度，而不会达到有害水平。此外，可能存在曲线下面积很重要的情况，这意味着这些身体不仅受到当前浓度的影响，而且受到整个给药历史的影响。根据各种因素，不同的模型和不同的患者效应可能与药物模型相关，疫苗剂量模型可能需要考虑类似的问题。腺病毒载体疫苗是一种新型的疫苗抗原递送方法。Ad作为载体的有效性主要是由于T细胞和抗体应答的产生，并且这种疫苗的功效已经在临床上针对各种疾病进行了试验。腺病毒构建体与修饰的安卡拉牛痘病毒（两种病毒载体）一起经常组合使用以诱导T细胞应答。然而，在了解联合使用疫苗的最佳剂量方面所做的工作很少，对接种疫苗的时间以及是否应该给予一次或多次初免或加强的了解也很少。主要重点应放在从药物开发到腺病毒疫苗开发的建模技术上。如果成功的话，这可能会启动一个新的科学领域-免疫刺激/免疫动力学（IS/ID）建模。将创建新的统计和机制模型，使用Vaccitech小鼠疫苗实验和文献的经验数据进行参数化，以帮助设计在Vaccitech进行的新的临床前和临床研究。这个项目有几个研究目标，将符合Vaccitech安置的集合。目标1：首先，我需要继续将我的数学知识应用于药代动力学和药效学模型，并对既往PK/PD工作和免疫反应有更深入的了解。这将主要通过文献围绕topic.Aim 2：第二，我们将使用现有的实验数据来创建和参数化新的统计/机理模型，以预测小鼠的疫苗剂量/免疫应答关系。目标二：第三，我们将通过预测新的经验性小鼠实验的最佳设计来改进统计/机械模型剂量-反应预测，以最大限度地提高获得的剂量-反应信息并最小化使用的小鼠数量。目标3：第四，使用异速生长比例假设和统计/机械建模，我们将根据小鼠数据对人体中最具免疫原性的剂量-反应关系进行初步预测。这些预测将在Vaccitech进行的新的经验性临床实验中进行评估。目标4：在这个博士学位期间，我们将创建的建模证据将用于改进Vaccitech腺病毒构建体和修饰的安卡拉牛痘病毒载体的人体试验的设计。除了创造新知识外，该项目还将对疫苗开发政策产生影响，并产生更广泛的经济和社会影响。如果这一领域被证明是有前途的，它可以大大减少开发疫苗所涉及的财政和时间负担。

Vaccines, once developed, are one of the most effective ways of saving human lives. But, developing a new vaccine can take decades, and cost around a billion dollars. The current scientific methods used to identify the right amount of vaccine dose are empirical and antiquated. In contrast, mathematical model-based drug development (PK/PD) is regularly used to predict the best size and schedule of drug dose to use. Pharmacokinetic models are used to model the concentration of drug in the body over time and generally consider the 4 stages of absorption, distribution, metabolism and excretion of the drug. Pharmacodynamic models focus on the effects that a drug can have on the body between absorption and excretion. These tools can be used to calculate dosage to maintain the substance at an effective concentration without reaching harmful levels. In addition, there may be cases where the area under curve is important, meaning that these body is not only affected by this present concentration but is influenced by the entire history of dosing. Dependant on various factors a different model and varying patient effects may be relevant in drug models, and vaccine dosage models would likely need to consider similar issues. Adenovirus(Ad) vector vaccines are a novel approach to vaccine antigen delivery. The effectiveness of Ad as a vector comes primarily due to the production of T-cell and antibody responses, and the efficacy of such vaccines have been clinically trialed for various diseases. Adenoviral constructs alongside modified vaccinia Ankara, two viral vectors, are often used in combination to induce T cells responses. However, minimal work has been carried out to understand the best doses of vaccines when used in combination, and there is a poor understanding of the timing of vaccination, and if one or more primes or boosts should be given. The main focus should be on modelling techniques from drug development to adenovirus vaccine development. If successful this could launch a new scientific field - immunostimulation/ immunodynamic (IS/ID) modelling. Novel statistical and mechanistic models will be created, parameterised using empirical data from Vaccitech mouse vaccine experiments and the literature, to help design new pre-clinical and clinical studies performed at Vaccitech. This project has several research aims that will coincide with a collection of Vaccitech placements. Aim 1: First, I will need to continue to adapt my mathematical knowledge towards pharmacokinetic and pharmacodynamic models and establish a greater understanding of previous PK/PD work and of the immune response. This will be primarily achieved through literature surrounding the topic.Aim 2: Second, we will use existing experimental data to create and parameterise novel statistical/mechanistic models to make predictions for the vaccine dose/immunological response relationship in mice. Aim 2: Third, we will improve the statistical/mechanistic model dose-response predictions, by making predictions for the best design of new empirical mouse experiments, to maximise the dose-response information gained and minimise the number of mice used. Aim 3: Fourth, using an allometric scaling assumption and statistical/mechanistic modelling, we will make initial predictions for the most immunogenic dose-response relationship in humans, based on the mouse data. These predictions will be evaluated in new empirical clinical experiments carried out at Vaccitech. Aim 4: Within the period of this PhD, the modelling evidence we will create will be used to improve the design of a human trial of the Vaccitech adenoviral constructs and Modified vaccinia Ankara viral vectors. In addition to the creation of new knowledge, the project has a route to impact on vaccine development policy alongside wider economic and societal impact. If this field proves promising, it could greatly reduce the financial and time burdens involved in developing vaccines.