REVOLUTIONIZING ALZHEIMER’S THERAPEUTICS: FROM MICROTECHNOLOGIES TO AI-DRIVEN INNOVATIONS

AKANKSHA LAHIRI; BALAMURALIDHARA V.; MANOHAR S. K.; AKHILA A. R.

doi:10.22159/ijap.2025v17i3.53726

Authors

AKANKSHA LAHIRI Department of Pharmaceutics, JSS College of Pharmacy, Mysuru, JSS Academy of Higher Education Research, Mysuru-570015, Karnataka, India https://orcid.org/0000-0002-7952-6093
BALAMURALIDHARA V. Department of Pharmaceutics, JSS College of Pharmacy, JSS Academy of Higher Education Research, Mysuru-570015, Karnataka, India
MANOHAR S. K. Department of Pharmaceutics, JSS College of Pharmacy, Mysuru, JSS Academy of Higher Education Research, Mysuru-570015, Karnataka, India https://orcid.org/0000-0003-0215-5594
AKHILA A. R. Department of Pharmaceutics, JSS College of Pharmacy, JSS Academy of Higher Education Research, Mysuru-570015, Karnataka, India https://orcid.org/0000-0003-4324-7698

DOI:

https://doi.org/10.22159/ijap.2025v17i3.53726

Keywords:

Alzheimer's disease, Artificial intelligence, Drug delivery, Clinical trials, Regulatory guidelines

Abstract

This review article dives deep into Alzheimer's Disease (AD), a progressive and incurable brain disorder. It aims to equip readers with a comprehensive understanding of AD by exploring its history, classification, causes, and risk factors. The article explores the emerging field of Artificial Intelligence (AI) and its potential to revolutionize AD management. It examines how AI can impact diagnostics, treatment strategies, and, particularly, the development of targeted therapies. AI-powered imaging tools, such as Deep Learning-based Positron Emission Tomography (PET)/Magnetic Resonance Imaging (MRI) analysis, have achieved over 90% accuracy in early AD detection by identifying subtle brain changes years before clinical symptoms appear. Machine learning models have also enhanced precision medicine by predicting patient responses to therapies with 85–92% accuracy, optimizing treatment regimens based on genetic and biomarker profiles. These novel delivery systems enhance drug efficacy, improve patient compliance, and reduce systemic toxicity, addressing key challenges in AD treatment. Future developments will focus on AI-guided personalized medicine, smart nanocarriers responsive to AD biomarkers, and AI-powered neuroprosthetics for cognitive rehabilitation. Next, it compares established management methods with the latest investigational drug therapies for AD. This analysis sheds light on promising future directions and potential breakthroughs in AD treatment. However, the article emphasizes the importance of patient safety and highlights the rigorous processes of clinical trials, and regulatory hurdles that new AD therapies and delivery systems must overcome. The review concludes by summarizing the key takeaways and identifying the most promising avenues for future research and development in AD treatment. It emphasizes the potential of these cutting-edge approaches to transform AD care and significantly improve patient quality of life.

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