PUBLICATION BY MATTHIAS MAGOOLA, CHEMIST
Abstract
Alzheimer’s disease (AD) remains a significant challenge in the field of neurodegenerative disorders, even nearly a century after its discovery, due to the elusive nature of its causes. The development of multi-target drug strategies has emerged as a promising approach to address the complexities of AD and related conditions.
The role of the immune system in AD has gained considerable interest, with nanobodies representing a new frontier in biomedical research. Advances in antibody targeting against amyloid-β (Aβ) and the use of messenger RNA (mRNA) for genetic translation have revolutionized antibody production and drug development, opening new possibilities for treatment.
Despite these advancements, conventional AD treatments such as Cognex, Exelon, Razadyne, and Aricept often have limited long-term effectiveness, highlighting the need for innovative solutions.
This necessity has led to the integration of advanced technologies like artificial intelligence (AI) and machine learning (ML) into the drug discovery process for neurodegenerative diseases. These technologies identify therapeutic targets and optimize lead compounds, offering a more effective approach to tackling the challenges of Alzheimer’s disease and related conditions.
