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Information Theory-Guided Detection of Biomarkers Using Programmable Aptamer Arrays
Amit Eshed1,2, Alexander A Green1,2,3
1Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA.
Medrxiv : the Preprint Server for Health Sciences
|December 8, 2025
Summary
Researchers developed a novel nucleic acid device, the Concentration Detector Array (CDA), for point-of-care diagnosis. This device accurately classifies nucleic acid concentrations, improving early disease detection like non-small cell lung cancer.
Area of Science:
- Biomolecular Engineering
- Molecular Diagnostics
- Bioinformatics
Background:
- Endogenous nucleic acid biomarkers show promise for disease prediction, yet point-of-care (PoC) diagnostic devices are lacking.
- Diagnosing based on endogenous biomarkers is complex due to reliance on concentration shifts from healthy baselines.
Purpose of the Study:
- To develop a nucleic acid device for precise quantification and classification of endogenous biomarkers at the point-of-care.
- To create information theory-based diagnostic strategies for efficient patient profiling using minimal tests, specifically for non-small cell lung cancer detection.
Main Methods:
- Introduction of the Concentration Detector Array (CDA), a nucleic acid device utilizing channel-activated thresholds for target nucleic acid identification and concentration binning.
- Implementation of consensus voting and error correction methods for robust CDA performance, achieving high binning classification accuracy (AUC = 0.945-0.955).
- Development of probability distribution functions (PDFs) for prognostic microRNAs (miRNAs) and integration with miRNA-sensing CDAs for diagnostic strategies.
Main Results:
- CDAs demonstrated excellent binning classification performance with high AUC values.
- A library of miRNA-sensing CDAs and PDF models was created, enabling information theory-based diagnostic strategies.
- The divergence maximization strategy identified patient profiles effectively in a single test, learning information faster than other methods.
Conclusions:
- The Concentration Detector Array (CDA) offers a promising platform for sensitive and specific point-of-care nucleic acid biomarker detection.
- Information theory-based diagnostic strategies, particularly divergence maximization, enhance diagnostic efficiency by minimizing the number of tests required.
- This approach addresses the diagnostic gap in diseases like non-small cell lung cancer, paving the way for improved patient stratification and management.
