Finding combinatorial drug repositioning therapy for Alzheimer's disease and related dementias

项目摘要 AD/ADRD是高度复杂的疾病，其特征在于不同的分子途径和神经病理学特征。 表型。不幸的是，这种治疗方法最多只能起到适度的效果，而且还没有新的药物被用于治疗。 自2003年以来批准。用于AD/ADRD治疗的组合药物疗法尚未被深入研究， 前景看好。我们假设，通过创新的方法找到重新定位的药物组合， 大数据的探索可能会发现有效的AD/ADRD治疗方法，在克服AD/ADRD方面具有隐含的优势。 耐药性和靶向多种生物标志物。我们将联合收割机大生物医学数据从互补的 来源，新颖和先进的信息学模型，临床领域的专业知识，以及生物学知识， 验证纳入连贯的框架，以解决AD/ADRD与潜在的组合药物疗法。中 组合药物治疗的空间呈指数级增长，更具挑战性， 与传统的单一药物模型相比， 需要小心处理我们将在两个哲学基础上开发多种计算模型。 保护伞，重点是可量化的筛选和生物学理解。我们的发现将得到验证 从细胞到老鼠的生物实验。如果成功，我们将大大推进AD/ADRD研究 使患者得到安全有效的治疗。

PROJECT SUMMARY AD/ADRD are highly complex diseases characterized by distinct molecular pathways and neuropathological phenotypes. Unfortunately, the treatment remains at best modestly effective and no new drugs have been approved since 2003. Combinatorial drug therapy for AD/ADRD treatment has not been intensively studied but it is highly promising. We hypothesize that finding repositioned drug combinations through innovative exploration of big data may uncover effective AD/ADRD treatments, with implicit advantages in overcoming drug resistance and targeting multiple biomarkers. We will combine big biomedical data from complementary sources, novel and advanced informatics models, clinical domain expertise, as well as biology knowledge and validation into a coherent framework to tackle AD/ADRD with potential combinatorial drug therapies. In an exponentially larger and more challenging space of combinatorial drug therapy, opportunities are also exponentially larger when compared with traditional single-drug models but many computational challenges need to be carefully handled. We will develop multiple computational models under two philosophical umbrellas, with focuses on quantifiable screening and biological understanding. Our findings will be validated with biological experiments from cell to mouse. If successful, we will significantly advance AD/ADRD research and benefit patients with safe and effective treatment.