## 1 Introduction
These systems' purpose is to replicate the microenvironment of the human brain by comprising miniaturized brain organoids, allowing researchers to study neurodegenerative mechanisms under physiologically relevant conditions [10; 16; 18]. Due to their capability to operate with remarkably smaller concentrations of biological compounds and emulate dynamic conditions, the scientific community can study intricate biochemical interactions and disease progression with higher precision and relevance. These platforms have the potential to significantly transform the approach to addressing neurological diseases, either in their diagnosis or in the investigation of effective treatments. Moreover, advanced microfluidic devices offer distinct advantages over traditional bulkscale (macro) diagnostic setups. By operating at the microscale, these systems minimize reagent consumption, reduce operational costs, and provide precise control over experimental environments, enabling higher sensitivity and specificity in biomarker detection. They also replicate the dynamic in vivo conditions found in the human body, such as mimicking cerebrospinal fluid flow, further enhancing their relevance to physiological studies [19; 20]. When combining advanced microfluidic devices, such as BoC with biosensors, a controlled and physiologically relevant environment is created, enabling improved biomarker detection without disturbing the homeostasis of the biomodels [21; 22]. However, transitioning from macro- to microfluidic platforms poses challenges, such as maintaining signal integrity and ensuring reproducibility under flow conditions and miniaturized setups. Overcoming these obstacles is crucial, as doing so could provide valuable insights into the study of neurodegenerative diseases and the evaluation of drug efficacy. So far, as for the research conducted for the detection of AD hallmark the A\(\beta\) biomarker, few studies have directly compared biomarker detection performance across macro- and microfluidic platforms, leaving a critical gap in understanding the benefits and trade-offs of biosensing integrated with microfluidics as a platform for AD detection and monitoring. Given the scarcity of research in this area and the pressing need within the scientific community to address this neurodegenerative disorder, validating the hypothesis of integrating a biosensor for AD detection in an advanced microfluidic device would be a significant breakthrough. To achieve this scientific goal, the present study presents a proof-of-concept miniaturized sensing platform for detecting the AD-specific A\(\beta\) biomarker, using the commercial fluorophore CRNAAD-2, with high affinity for A\(\beta\) aggregates (Kd = 38 nM) [23]. CRNAAD-2 is a fluorescent probe specifically designed for A\(\beta\) in vivo bioimaging, offering high binding specificity and a robust fluorescence response, making it an ideal candidate for optical biosensing [23; 24]. The selectivity of this fluorescent probe for A\(\beta\) binding has been thoroughly characterized, both in vivo and in vitro [23; 24; 25; 26]. Previous studies have demonstrated specific binding to A\(\beta\) fibril compared to other proteins such as a-synuclein and insulin [26]. This study also included specificity binding results by immunohistochemistry and its capability for in vivo multi-spectral optoacoustic tomography (MSOT) cerebral A\(\beta\) mapping, confirming CRNAAD-2 as a suitable optical detection probe for AD. The proposed methodology involves a two-tier experimental approach: (i) the validation of CRNAAD-2's fluorescence properties and binding efficacy in a macroscale configuration, using an optical spectrophotometer to establish baseline detection performance and feasibility; (ii) the adaptation of the macroscale experiments into a microfluidic platform, designed to evaluate the respective probe's performance.