Chemical Approaches for Array Based Detection of Amyloids

Abstract Amyloids are protein aggregates implicated in both physiological functions and pathological conditions, including neurodegenerative diseases. Their polymorphic nature, dynamic aggregation behavior, and isoform complexity present significant challenges for detection and characterization. Traditional lock‐and‐key sensing methods often fall short in capturing this heterogeneity. Array‐based sensing has emerged as a powerful alternative, leveraging cross‐reactive sensors and multivariate data analysis to generate distinct response patterns or “fingerprints” for amyloids. This review highlights recent advances in arrays based on chemical sensors including colorimetric, fluorescent, and nanoparticle‐based, capable of discriminating amyloid isoforms, aggregation states, and polymorphs with high sensitivity and accuracy. The integration of machine learning techniques and neural networks, which enhance pattern recognition and predictive accuracy, even in complex biological matrices, is discussed. Notably, multidimensional approaches expand the analytical power of single‐sensor systems by exploiting excitation/emission spectral diversity. These innovations underscore the potential of array‐based platforms for early diagnosis, mechanistic studies, and therapeutic monitoring of amyloid‐related diseases. As the field evolves, combining sensor diversity with advanced computational tools promises to transform amyloid detection into a scalable and clinically relevant technology.