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By combining enzyme-catalyzed multicolor encoding with DNA technology programmability, multidimensional miRNA inputs are converted into optical signals that can be decoded by visual inspection or spectral analysis. EnCODE uses continuous weighting for accurate digital biomarker mapping, and in 163 pancreatic cancer clinical samples achieves 96% sensitivity and 90% overall accuracy, matching conventional methods. 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Colorimetric analysis offers an intuitive readout, but colorimetric-based digital medicine remains underexplored. Here we show an Enzymatic Colorimetric Encoding-based Digital Medicine platform (EnCODE). By harnessing enzyme-catalyzed multicolor encoding in tandem with the programmability of DNA technology, EnCODE converts multidimensional miRNA information into recognizable optical signals. We demonstrate that these signals are decodable and can be interpreted by visual inspection or spectral analysis, facilitating dimensionality reduction and visualization of disease states. Additionally, EnCODE integrates a continuous weighting mechanism that enables accurate mapping of digital biomarkers. In a cohort of 163 pancreatic cancer clinical samples, EnCODE achieves 96% detection sensitivity and 90% overall accuracy—comparable to the 96% sensitivity and 91% overall accuracy with conventional molecular diagnostic methods. We increase data density through three-dimensional color encoding and hyperspectral imaging-based analysis, enabling an intuitive color-coded molecular readout.  \nBiomarker detection plays a critical role in diagnosing diseases, guiding medication, and monitoring disease progression1–3. With the development of omics technologies, an increasing number of biomarkers have been discovered and it has been proven that the joint analysis of multiple biomarkers often yields better results4–9. To harness diverse biomarker data, digital medicine has emerged, leveraging digital biomarkers to quantify and mathematically  \nintegrate multiple targets through weighted algebraic operations10. However, current multi-target assays require separate reaction tubes, increasing costs, operational complexity, and inter-well variability11,12. Integrating the concept of digital medicine with the programmability of DNA technology enables single-tube multiplex biomarker detection, addressing these limitations while maintaining analytical rigor13–15.  \n1Department of Clinical Laboratory Medicine, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China. 2School of Medicine, Tongji University, Shanghai, China. 3Institute of Precision Optical Engineering, School of Physics Science and Engineering, Tongji University, Shanghai, China. 4Department of Clinical Laboratory Medicine, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. 5Department of Clinical Laboratory Medicine, Shanghai Fourth People’s Hospital, School of Medicine, Tongji University, Shanghai, China. 6Department of Laboratory Medicine, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, China. 7These authors contributed equally: Dongsheng Mao, Chenbin Liu, Runchi Zhang. [e-mail:](e-mail: 2311069@tongji.edu.cn)[ 2311069@tongji.edu.cn](e-mail: 2311069@tongji.edu.cn);  \n[sunfenyong@263.net](sunfenyong@263.net); [xiaolizhu@tongji.edu.cn](xiaolizhu@tongji.edu.cn)  \nCurrent solutions predominantly rely on fluorescence signals, using signal type or intensity to determine the positive or negative status of the sample16–19. For instance, Han et al. developed a molecular classifier using fluorescence signals for lung cancer diagnosis via serum microRNA (miRNA)20, while Randolph Lopez","cbCaiaYFCxMwwYeD","https://ap.wps.com/l/cbCaiaYFCxMwwYeD","pdf",2153162,16,"English","# Background and motivation\n# EnCODE platform design\n## Enzymatic colorimetric encoding and DNA programmability\n## Decoding and visualization\n## Continuous weighting mechanism\n# Pancreatic cancer application and performance\n# Comparison with fluorescence-based approaches","[{\"question\":\"What problem does EnCODE address in digital medicine?\",\"answer\":\"EnCODE targets the underexplored use of colorimetric outputs in digital medicine and the limitations of current multi-target assays that often require separate reaction tubes and specialized readouts.\"},{\"question\":\"How does EnCODE convert miRNA information into readable results?\",\"answer\":\"It uses enzyme-catalyzed multicolor encoding with DNA technology to transform multidimensional miRNA signals into optical signals that can be decoded via visual inspection or spectral analysis.\"},{\"question\":\"How well does EnCODE perform for pancreatic cancer diagnosis?\",\"answer\":\"In a cohort of 163 clinical samples, EnCODE reaches 96% detection sensitivity and 90% overall accuracy, comparable to conventional molecular diagnostic methods.\"}]","Enzymatic colorimetric encoding-based digital medicine for pancreatic cancer diagnosis | PDF",1790120100]