Early diagnosis of Parkinson’s disease (PD) remains fundamentally constrained by symptom-based confirmation and infrastructure-dependent imaging modalities. Although molecular biomarkers including α-synuclein species, DJ-1, and neurofilament light chain (NfL) have been extensively investigated, no scalable molecular point-of-care (POC) platform has achieved robust clinical translation. This work presents a structured, requirement-driven engineering framework for selecting an optimal POC biosensing architecture for early PD detection. Current diagnostic modalities are systematically analyzed to define the clinical gap. A MoSCoW-derived requirement catalog (DET-01-DET-13) is used to formalize analytical and deployment constraints. Salivary and bloodbased biomarker characteristics are critically evaluated with emphasis on reported concentration ranges and limits of detection (LoD). Sensor technologies including electrochemical aptasensors, FET-based biosensors, and optical platforms are comparatively assessed. Structured alignment with the ASSURED framework is applied to evaluate translational feasibility. Electrochemical multiplex aptasensing demonstrates the strongest combined compliance with analytical sensitivity, scalability, and deployment requirements. The proposed framework provides a transparent pathway from clinical diagnostic gap identification to engineering system selection.
Abdulmohsen Alobaed (Fri,) studied this question.