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Fabrication of Three-dimensional Paper-based Microfluidic Devices for Immunoassays

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Developing point-of-need (PON) cancer biosensors using microfluidic paper-based analytical devices: recent advances.

Farnaz Bahavarnia¹, Fatemeh Nami², Mohammad Hasanzadeh³

¹Nutrition Research Center, Tabriz University of Medical Sciences Tabriz Iran.

|December 11, 2025

Summary

Microfluidic paper-based analytical devices (µPADs) and paper-based analytical devices (PADs) leverage nanomaterials for low-cost, point-of-need cancer biomarker detection. This review highlights advances in nanomaterial applications and sensing techniques for early cancer diagnosis.

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Area of Science:

Biomedical Engineering
Nanotechnology
Analytical Chemistry

Background:

Microfluidic paper-based analytical devices (µPADs) offer a low-cost platform for point-of-need (PON) biosensors.
Nanomaterials are crucial for developing sensitive cancer biomarker and cell detection methods.
Early-stage cancer diagnosis is vital for effective treatment outcomes.

Purpose of the Study:

To review recent advancements in µPADs and PADs for cancer diagnosis.
To summarize the application of various nanomaterials in cancer detection.
To explore diverse biosensing strategies and detection techniques for cancer biomarkers.

Main Methods:

Review of literature on µPADs and PADs for cancer diagnosis.
Analysis of nanomaterials (metal/metal oxide nanoparticles, magnetic nanoparticles, quantum dots, 1-3D materials).
Survey of biosensing mechanisms (immune-, apta-, geno-, peptide-, enzymatic) and detection techniques (electrochemical, optical, electrochemiluminescent, photoelectrochemical, piezoelectric).

Main Results:

µPADs and PADs integrated with diverse nanomaterials show significant potential for cancer biomarker and cell detection.
Various biosensing strategies and advanced detection techniques enable sensitive and specific cancer diagnostics.
Emerging technologies like AI and IoT are being explored to enhance PAD-based cancer diagnosis.

Conclusions:

µPADs and PADs represent a promising, cost-effective approach for early cancer diagnosis.
Further research is needed to address limitations and optimize fabrication strategies for clinical translation.
Integration of novel technologies can further improve the capabilities of paper-based diagnostic platforms.