Toward molecular classification architectures for cell-free diagnostics.

Area of Science:

• Biomedical Engineering
• Molecular Diagnostics
• Point-of-Care Testing

Background:

• Cell-free diagnostic platforms offer low-cost, deployable point-of-care testing solutions.
• Current systems primarily focus on individual analyte detection, limiting complex clinical decision-making.
• Multimarker analysis is crucial for accurate clinical diagnosis.

Purpose of the Study:

• To propose molecular classification architectures as the next translational step for cell-free diagnostics.
• To outline a framework for integrating multiple biomarker inputs into diagnostic calls.
• To identify challenges in advancing from multiplexed detection to molecular classification.

Main Methods:

• Reviewing emerging capabilities in molecular diagnostics.
• Organizing these capabilities into a three-layer molecular decision pathway.
• Evaluating the integration progress of each layer.

Main Results:

• Core molecular modules for input reformatting, state discrimination, and output classification are emerging independently.
• These essential modules currently remain unconnected within diagnostic systems.
• The preservation of decision fidelity across integrated layers is a significant challenge.

Conclusions:

• The field needs to transition from multiplexed detection to integrated molecular classification architectures.
• Developing unconnected core molecular modules into a cohesive system is critical.
• Addressing the challenge of maintaining decision fidelity is essential for clinical translation of advanced cell-free diagnostics.