Alzheimer’s disease (AD) is a progressive neurodegenerative disease and is the most common type of dementia. Although a considerably large amount of money has been invested in drug development for AD, no disease modifying treatment has been detected so far. In our previous work, we developed a computational method to highlight stage-specific candidate repurposed drugs against AD. In this study, we tested the effect of the top 13 candidate repurposed drugs that we proposed in our previous work in a severity stage-specific manner using an in vitro BACE1 assay and the effect of a top-ranked drug from the list of our previous work, tetrabenazine (TBZ), in the 5XFAD as an AD mouse model. From our in vitro screening, we detected 2 compounds (clomiphene citrate and Pik-90) that showed statistically significant inhibition against the activity of the BACE1 enzyme. The administration of TBZ at the selected dose and therapeutic regimen in 5XFAD in male and female mice showed no significant effect in behavioral tests using the Y-maze and the ELISA immunoassay of Aβ40. To our knowledge, this is the first time the drug tetrabenazine has been tested in the 5XFAD mouse model of AD in a sex-stratified manner. Our results highlight 2 drugs (clomiphene citrate and Pik-90) from our previous computational work for further investigation.

Background/Objectives: Multiple myeloma (MM) is a challenging, B cell malignancy characterised by the uncontrolled proliferation of plasma cells within the bone marrow. Despite significant advances in treatment options nowadays, MM remains an incurable malignancy, with the majority of patients succumbing to the disease. MM develops from a pre-malignant state known as monoclonal gammopathy of unknown significance (MGUS), which then has the potential to evolve either into smouldering (asymptomatic) multiple myeloma (SMM) or into MM. Since novel drug discovery takes years to reach the clinic, drug repurposing, which concerns the detection of existing drugs for a novel disease, can be applied. Methods: To address this critical and still unmet medical need, we present a comprehensive signature-based drug-repurposing approach using all the publicly available bulk transcriptomics datasets on mGUS, sMM, and MM. Results: Our study included an in-house scoring scheme approach enabling further filtering and prioritisation, resulting in 25 candidate repurposed drugs for mGUS, 23 for sMM, and 66 for MM. The corresponding gene targets and the related functional terms have been analysed, providing extra information for stage-specific underlying mechanisms in myeloma. Lastly, enabled by a specific computational workflow, we propose drug combinations between our top candidate repurposed drugs and FDA-approved drugs for MM. Conclusions: Together, these results deliver a stage-specific, transparent resource for MM drug repurposing and combination design, intended to accelerate translation toward earlier disease intervention and improved patient outcomes.

In the area of drug research, several computational drug repurposing studies have highlighted candidate repurposed drugs, as well as clinical trial studies that have tested/are testing drugs in different phases. To the best of our knowledge, the aggregation of the proposed lists of drugs by previous studies has not been extensively exploited towards generating a dynamic reference matrix with enhanced resolution. To fill this knowledge gap, we performed weight-modulated majority voting of the modes of action, initial indications and targeted pathways of the drugs in a well-known repository, namely the Drug Repurposing Hub. Our method, D^Re^Amocracy, exploits this pile of information and creates frequency tables and, finally, a disease suitability score for each drug from the selected library. As a testbed, we applied this method to a group of neurodegenerative diseases (Alzheimer’s, Parkinson’s, Huntington’s disease and Multiple Sclerosis). A super-reference table with drug suitability scores has been created for all four neurodegenerative diseases and can be queried for any drug candidate against them. Top-scored drugs for Alzheimer’s Disease include agomelatine, mirtazapine and vortioxetine; for Parkinson’s Disease, they include apomorphine, pramipexole and lisuride; for Huntington’s, they include chlorpromazine, fluphenazine and perphenazine; and for Multiple Sclerosis, they include zonisamide, disopyramide and priralfimide. Overall, D^Re^Amocracy is a methodology that focuses on leveraging the existing drug-related experimental and/or computational knowledge rather than a predictive model for drug repurposing, offering a quantified aggregation of existing drug discovery results to (1) reveal trends in selected tracks of drug discovery research with increased resolution that includes modes of action, targeted pathways and initial indications for the investigated drugs and (2) score new candidate drugs for repurposing against a selected disease.