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Exploring the Correlation between the Cognitive Benefits of Drug Combinations in a Clinical Database and the Efficacies of the Same Drug Combinations Predicted from a Computational Model

机译:探索临床数据库中药物组合的认知益处与基于计算模型预测的相同药物组合功效之间的相关性

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摘要

Identification of drug combinations that could be effective in Alzheimer’s disease treatment is made difficult by the sheer number of possible combinations. This analysis identifies as potentially therapeutic those drug combinations that rank highest when their efficacy is determined jointly from two independent data sources. Estimates of the efficacy of the same drug combinations were derived from a clinical dataset on cognitively impaired elderly participants and from pre-clinical data, in the form of a computational model of neuroinflammation. Linear regression was used to show that the two sets of estimates were correlated, and to rule out confounds. The ten highest ranking, jointly determined drug combinations most frequently consisted of COX2 inhibitors and aspirin, along with various antihypertensive medications. Ten combinations of from five to nine drugs, and the three-drug combination of a COX2 inhibitor, aspirin, and a calcium-channel blocker, are discussed as candidates for consideration in future pre-clinical and clinical studies.
机译:由于可能的组合数量之多,很难确定可能有效治疗阿尔茨海默氏病的药物组合。当从两个独立的数据源共同确定其功效时,该分析将排名最高的那些药物组合识别为潜在治疗药物。相同药物组合的疗效评估是从认知障碍的老年受试者的临床数据集和临床前数据(以神经炎症计算模型的形式)得出的。线性回归用来表明两组估计值是相关的,并排除了混淆。排名最高的十种,共同确定的药物组合最常由COX2抑制剂和阿司匹林以及各种降压药物组成。讨论了从五种药物到九种药物的十种组合以及COX2抑制剂,阿司匹林和钙通道阻滞剂的三种药物组合,作为将来临床前和临床研究中考虑的候选药物。

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