Drug Repurposing for Effective Alzheimer's Disease Medicines: Existing Methods and Novel Pharmacoepidemiological...

Drug repurposing is a methodology used to identify new clinical indications for existing drugs developed for other indications and has been successfully applied in the treatment of numerous conditions. Alzheimer's disease (AD) may be particularly well-suited to the application of drug repurposing methods given the absence of effective therapies and abundance of multi-omic data that has been generated in AD patients recently that may facilitate discovery of candidate AD drugs. A recent focus of drug repurposing has been in the application of pharmacoepidemiologic approaches to drug evaluation. Here, real-world clinical datasets with large numbers of patients are leveraged to establish observational efficacy of candidate drugs for further evaluation in disease models and clinical trials. In this review, we provide a selected overview of methods for drug repurposing, including signature matching, network analysis, molecular docking, phenotypic screening, semantic network, and pharmacoepidemiological analyses. Numerous methods have also been applied specifically to AD with the aim of nominating novel drug candidates for evaluation. These approaches, however, are prone to numerous limitations and potential biases that we have sought to address in the Drug Repurposing for Effective Alzheimer's Medicines (DREAM) study, a multi-step framework for selection and validation of potential drug candidates that has demonstrated the promise of STAT3 inhibitors and re-evaluated evidence for other drug candidates, such as phosphodiesterase inhibitors. Taken together, drug repurposing holds significant promise for development of novel AD therapeutics, particularly as the pace of data generation and development of analytical methods continue to accelerate.