Analysis of Differential Resistance Emergence Risk for Differential Treatment App

描述（由申请人提供）：该项目将开发基于模型的HIV治疗转换方法，通过同时考虑病毒和原病毒基因组成以及总病毒载量对这种风险的贡献，将后续治疗失败的风险降至最低。使用先前失败的抗病毒方案的成分，患者的病毒载量将为新的抗病毒方案“预先调节”，以最大限度地提高其成功的可能性。这种方法在几个重要方面不同于前面的方法。它侧重于尚未产生多重耐药病毒的患者的治疗转换，对于这些患者，仍然存在潜在成功的抗病毒方案。它不仅将已知的抗病毒药物之间交叉耐药的发生率纳入其风险计算，而且还根据患者使用抗病毒药物的历史，了解显性耐药菌株之间的遗传距离。这些治疗方法将基于艾滋病毒准种动态的数学模型和不同治疗应用计划期间各种病毒株之间的竞争，以及耐药性出现的数学模型。这些模型将用于开发实验室和临床实验，作为实施这些技术的未来工作。基于模型的算法治疗切换时间表应通过降低引入之前存在的耐药病毒的风险，显著降低后续抗病毒治疗失败的风险。公共卫生相关性：如果成功，这项研究将提供一种方法来减少由于耐药病毒导致的艾滋病毒治疗失败的发生率。这有可能延长成千上万艾滋病毒感染者的预期寿命，并改善他们的生活质量。该方法的应用还可以降低人群中多重耐药病毒的总体发病率。

DESCRIPTION (provided by applicant): This project will develop model-based approaches to therapy switching for HIV which minimize the risk of subsequent treatment failures by simultaneously considering the contributions of the viral and proviral genetic makeup and the total viral load to this risk. Using components of previously failed antiviral regimens, the patient's viral load will be "pre-conditioned" for the new antiviral regimen, to maximize its possibility of success. This approach differs from the previous approaches in several important ways. It focuses on therapy switches in patients who have not yet developed multi-drug resistant virus, for whom potentially successful antiviral regimens still exist. It incorporates into its calculation of risk not only the known incidences of cross-resistance between antiviral drugs, but also the knowledge of genetic distance between dominant resistant strains, based on the patient's history of antiviral use. These approaches to treatment will be based on mathematical models of HIV quasispecies dynamics and the competition between various viral strains during different treatment application schedules, as well as mathematical models of resistance emergence. These models will be used to develop laboratory and clinical experiments as future work to implement these techniques. The model- based algorithmic therapy-switching schedules should significantly reduce the risk of failure of subsequent antiviral therapy by reducing the risk of resistant virus pre-existing its introduction. PUBLIC HEALTH RELEVANCE: If successful, this research will provide a method to reduce the incidence of HIV treatment failure due to resistant virus. This has the potential to extend the life expectancy of thousands of people infected with the HIV virus, and to improve their quality of life. Application of this method may also reduce the overall incidence of multi-drug resistant virus in the population.