Salivary nanobiosensors for oral diseases: from biomarker discovery to clinical translation in precision dentistry

INTRODUCTION: Current diagnostic approaches to oral disease have limitations, highlighting the need for rapid, sensitive, and accessible technologies for routine clinical use. Biosensors can evaluate a wide range of biomarkers in oral conditions, including periodontal diseases, oral cancer, dental caries, oral infections, and peri-implant diseases. AREAS COVERED: We present a clinical perspective on salivary biosensors for oral diseases, focusing on biomarker discovery and technological advances, with particular emphasis on challenges and solutions. Integrating biosensors with artificial intelligence, smartphones, and digital health platforms holds promise for saliva-based diagnostics in modern dentistry. These technologies support continuous monitoring through teledentistry, thereby facilitating precision dentistry. Bridging the gap between laboratory innovation, clinical validation, regulatory approval, and commercialization will be essential for the broader adoption of oral biosensors. EXPERT OPINION: The use of wearable intraoral and portable POC biosensors could increase their clinical applicability in the future. Current limitations include long sensor response times, the computational demands of data processing, and reduced model performance across diverse patient populations. Future efforts should focus on efficient on-device data analysis and on developing robust systems that incorporate advances in both material and digital technologies, while ensuring manufacturability, user comfort, and sustained patient compliance.

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Publication Details

Journal
Expert Review of Molecular Diagnostics
Published
2026-10-06
DOI
https://doi.org/10.1080/14737159.2026.2745670
Primary Topic
Biosensors and Analytical Detection
Type
article
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article

Salivary nanobiosensors for oral diseases: from biomarker discovery to clinical translation in precision dentistry

Nooshin Mohtasham, Camellia Kianbakht, Maryam Ghelichli, Amir Attaran Khorasani et al.
Expert Review of Molecular Diagnostics
Biosensors and Analytical Detection
article

Salivary nanobiosensors for oral diseases: from biomarker discovery to clinical translation in precision dentistry

Nooshin Mohtasham, Camellia Kianbakht, Maryam Ghelichli, Amir Attaran Khorasani, Jamshid Hashemi, Kioumars Maraghehmoghaddam
article en

Abstract

INTRODUCTION: Current diagnostic approaches to oral disease have limitations, highlighting the need for rapid, sensitive, and accessible technologies for routine clinical use. Biosensors can evaluate a wide range of biomarkers in oral conditions, including periodontal diseases, oral cancer, dental caries, oral infections, and peri-implant diseases. AREAS COVERED: We present a clinical perspective on salivary biosensors for oral diseases, focusing on biomarker discovery and technological advances, with particular emphasis on challenges and solutions. Integrating biosensors with artificial intelligence, smartphones, and digital health platforms holds promise for saliva-based diagnostics in modern dentistry. These technologies support continuous monitoring through teledentistry, thereby facilitating precision dentistry. Bridging the gap between laboratory innovation, clinical validation, regulatory approval, and commercialization will be essential for the broader adoption of oral biosensors. EXPERT OPINION: The use of wearable intraoral and portable POC biosensors could increase their clinical applicability in the future. Current limitations include long sensor response times, the computational demands of data processing, and reduced model performance across diverse patient populations. Future efforts should focus on efficient on-device data analysis and on developing robust systems that incorporate advances in both material and digital technologies, while ensuring manufacturability, user comfort, and sustained patient compliance.

Expert Review of Molecular Diagnostics
Islamic Azad University, Tehran (IR), Mashhad University of Medical Sciences (IR), Golestan University of Medical Sciences (IR)
Openalex Percentile: Top 23%
Biosensors and Analytical Detection
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