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

Abstract

AbstractINTRODUCTIONIdentification of drug combinations that could be effective in Alzheimer’s treatment is made difficult by the 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.METHODSEstimates of the efficacy of the same drug combinations were derived from a clinical dataset and from pre-clinical data, in the form of a computational model of neuroinflammation. Standard linear regression was used to show that the two sets of estimates were correlated, and to rule out possible confounds.RESULTSThe ten highest ranking, jointly determined drug combinations most frequently consisted of COX2 inhibitors and aspirin, along with various antihypertensive medications.DISCUSSIONTen 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 clinical and pre-clinical studies.