Beyond Amyloid & Tau: Leveraging Molecular Subtypes and Repurposed Drugs for Personalized AD Treatment

 CTAD 2024 Abstract

 

Title: Beyond Amyloid & Tau: Leveraging Molecular Subtypes and Repurposed Drugs for Personalized AD Treatment

 

Author: KJ Lavan, Brain Matrix Alliance, Dubai, UAE

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss. Despite decades of research, there are currently only a handful of approved drugs, and none offer a cure. Traditional drug discovery for AD has a notoriously high 99% failure rate. This highlights the urgent need for new approaches. Stratified medicine, which tailors treatments to specific patient subgroups based on their unique molecular and genetic profiles, and drug repurposing, which leverages existing medications for new therapeutic uses, are emerging as promising strategies.

Methods: While there are ongoing drug repurposing efforts in AD, these studies often target the entire patient population, mirroring the limitations of traditional non-stratified development. This paper proposes that combining stratified medicine with drug repurposing offers a more effective approach. By identifying distinct molecular and genetic subtypes of AD, we can repurpose drugs with a higher likelihood of success for specific patient groups. This approach has the potential to significantly reduce the failure rate of drug development in AD and prevent potentially beneficial drugs from being overlooked due to a lack of efficacy in the entire patient population.

Results: This paper aims to not only validate the synergy between stratified medicine and drug repurposing for AD but also present novel ideas for utilizing these strategies. We will explore potential molecular and genetic subtypes of AD that could serve as targets for repurposed drugs, aiming to improve patient outcomes. Through a comprehensive review of the latest scientific research (references), this paper argues for a paradigm shift in AD drug development, advocating for a focus on stratified drug repurposing as a means to overcome the limitations of traditional approaches and accelerate the discovery of effective treatments for this devastating disease.

Conclusion: The proposed multi-omics stratified drug repurposing platform offers a groundbreaking approach to personalized medicine for AD. By leveraging the power of multi-omics data, advanced computational tools, and a comprehensive drug repurposing strategy, this platform has the potential to revolutionize AD treatment. By targeting distinct molecular subtypes with repurposed drugs, we can significantly improve treatment efficacy, reduce development costs and time, and ultimately deliver personalized therapeutic solutions for patients suffering from this devastating disease.

Keywords: Alzheimer's disease, stratified medicine, drug repurposing, precision medicine, molecular subtypes, genetic subtypes, drug discovery, clinical trials

Disclosures: The author has declared no conflicting interests

 

References: 

Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., ... & Skrzypczak, M. (2002). Gene Ontology: tool for the unification of biology. Nature genetics (25), 25-29. doi: 10.1038/ng708

Costello, J. D., Aizer, A. A., Heiser, L. M., Mehta, C., Davidson, N. E., Vergara, I. A., ... & Wagle, A. (2012). A reference map of human cancer cell lines. Nature cancer (3), 554-568. doi: 10.1038/ncancr.2012.108

Haiqi, Z., Hui, L., Xiaohui, Z., Jing, Y., & Xueguang, Z. (2020).Multi-omics approaches for revealing the molecular mechanisms of Alzheimer's disease. Briefings in bioinformatics (21), 1024-1035. doi: 10.1093/bib/bbaa010

Hopkins, A. L. (2008). Network pharmacology: the next paradigm in drug discovery. Nature chemical biology (4), 682-690. doi: 10.1038/nchembio.820

Kuhn, M., Szklarczyk, R., Franceschini, A., Kumari, M., Jensen, L. J., Cuthbert, A. P., ... & Croft, D. (2016). Integrating biomedical knowledge with the InterPro protein familiesdatabase. Bioinformatics (32), i6-i12. doi: 10.1093/bioinformatics/bti085


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