Toward molecular classification architectures for cell-free diagnostics

Cell-free diagnostics have advanced as low-cost, deployable platforms for point-of-care testing, yet most systems are still designed around individual analyte detection rather than the multimarker decision-making that clinical diagnosis demands. This review proposes that the next translation step is moving from multiplexed detection toward molecular classification architectures, converting multiple biomarker inputs into sample-to-answer diagnostic calls without external computation. To frame this, we organize emerging capabilities into a three-layer molecular decision pathway and evaluate how far each layer has progressed toward integration. Core molecular modules for input reformatting, combinatorial state discrimination, and output classification are individually emerging but remain unconnected, and we identify the preservation of decision fidelity across layers as the central translational challenge for the field.