CAREER: Virus Infection and Immune Responses: Modeling, Analysis, and Implications

该项目的目标是开发和分析数学模型，以定量研究病毒感染和免疫反应，并展示其对抗病毒治疗和疫苗接种的影响。通过实验数据验证和提供信息的数学模型为理解病毒、细胞和免疫反应之间的相互作用做出了重要贡献。然而，新的数据出现并更新了我们对这些过程背后的生物学的理解。有时，新数据的分析会产生相互矛盾的结果。该项目将开发和分析新模型，将其与实验数据进行比较，解释新数据产生的潜在差异，并解决对治疗和疫苗开发的影响。该项目的第一部分开发了多尺度模型，以研究使用新型抗病毒药物治疗的患者中的丙型肝炎病毒（HCV）动力学。这些模型包括细胞内病毒复制和细胞外细胞感染。该项目的第二部分开发了全面的免疫模型，以阐明控制艾滋病毒（一种导致人类艾滋病的病毒）的机制。将模型预测与实验数据进行比较，以确定靶细胞可用性和特定免疫机制在病毒控制中的相对作用。该项目将在病毒感染和免疫反应的定量研究中产生建模，计算和数据分析方法。多尺度病毒模型将建立一个理论框架，用于研究接受新药治疗的患者的病毒动力学，并研究耐药性的出现。这有助于开发更有效的联合治疗并提高治愈率。这种综合战略在艾滋病毒感染管理方面取得了巨大成功。在这个项目中开发的综合免疫模型将解决免疫学中的基本问题，例如， 免疫系统如何控制病毒载量，以及为什么有些猴子可以与艾滋病毒样病毒一起生活而不会发展为艾滋病。这些结果可能为未来病毒疫苗和免疫疗法的开发提供有效的策略。这种跨学科的研究将提供广泛的培训机会，从高中到研究生院的不同背景的学生。 该项目包括与实验学家的广泛合作，将为数学学生提供生物医学领域广泛的培训机会。跨学科合作还将有助于更好地向广大科学受众传播项目成果。

The objectives of this project are to develop and analyze mathematical models to quantitatively investigate virus infection and immune responses and to demonstrate their implications for antiviral treatment and vaccination. Mathematical models, validated and informed by experimental data, have made important contributions to the understanding of interactions between virus, cells, and immune responses. However, new data emerge and update our understanding of the biology underlying these processes. Sometimes the analysis of new data generates conflicting results. This project will develop and analyze new models, compare them with experimental data, explain potential discrepancies generated by new data, and address the implications to therapy and vaccine development. The first part of this project develops multi-scale models to study hepatitis C virus (HCV) dynamics in patients treated with new antiviral drugs. These models include both intracellular viral replication and extracellular cell infection. The second part of the project develops comprehensive immune models to elucidate the mechanisms in controlling HIV, a virus that causes AIDS in humans. The modeling predictions will be compared with experimental data to determine the relative roles of target cell availability and specific immune mechanisms in viral control. This project will generate modeling, computational, and data analysis methods in quantitative studies of virus infection and immune responses. The multi-scale virus models will establish a theoretical framework for studying viral dynamics in patients treated with new drugs and will investigate the emergence of drug resistance. This can help to develop more effective combination therapy and improve cure rates. Such combination strategies have achieved a great success in the management of HIV infection. The comprehensive immune models developed in this project will address fundamental questions in immunology, e.g., how the immune system controls viral load and why some monkeys can live with an HIV-like virus without progressing to AIDS. The results may suggest effective strategies for the development of future virus vaccines and immune-based therapies. This interdisciplinary research will provide extensive training opportunities to students from diverse backgrounds at levels from high school to graduate school. This project includes extensive collaborations with experimentalists which will provide mathematics students with a broad range of training opportunities in the biomedical field. The interdisciplinary collaboration will also help to improve the dissemination of the project's results to a broad scientific audience.