Salivary Biosensors in Oral Cancer Detection: A Balanced Overview

Abstract A transformative phase in health care is under way with significant leap in clinical research, biosensing technologies, nanoparticles, embedded electronics, cloud-distributed software and services, and artificial intelligence. This current scenario describes the relevance of the term digital health and digital health technologies among the health professionals. Despite of these recent breakthroughs in early detection and diagnosis of oral cancer, it still possesses a major threat especially in developing countries like India with 60,000 new cases reported annually. Early detection and early treatment has become the motto for cancer diagnosis and the applications of biosensors in this aspect is limitless theoretically. Oral biosensors are basically receptor–transducer devices that uses biological material in the saliva to interact with an analyte embedded with the device and deliver quantitative or semi-quantitative information utilizing a biological recognition element, processed and transferred to any smart devices. They offer real time biomarker monitoring, minimal biomolecule concentration along with high sensitivity and specificity, thus reducing the possibility of false positive and false negative in testing process. This would in turn enable the opportunity to share clinical data with clinicians could enable better predictions based on innovative algorithms based on big data ultimately better diagnosis, prognosis, and treatment for the patient. This narrative reviews the developments and advancements in different saliva based biosensors used in the early detection of oral cancer. We also explain the methods used by biosensors to target different types of biomarkers and focused on biosensors that function at the molecular level.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-30
DOI
https://doi.org/10.5281/zenodo.17935152
Primary Topic
Oral Health Pathology and Treatment
Type
article
Field-Weighted Citation Impact
0.00
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article

Salivary Biosensors in Oral Cancer Detection: A Balanced Overview

Zenodo (CERN European Organization for Nuclear Research)
Oral Health Pathology and Treatment
article

Salivary Biosensors in Oral Cancer Detection: A Balanced Overview

article en

Abstract

Abstract A transformative phase in health care is under way with significant leap in clinical research, biosensing technologies, nanoparticles, embedded electronics, cloud-distributed software and services, and artificial intelligence. This current scenario describes the relevance of the term digital health and digital health technologies among the health professionals. Despite of these recent breakthroughs in early detection and diagnosis of oral cancer, it still possesses a major threat especially in developing countries like India with 60,000 new cases reported annually. Early detection and early treatment has become the motto for cancer diagnosis and the applications of biosensors in this aspect is limitless theoretically. Oral biosensors are basically receptor–transducer devices that uses biological material in the saliva to interact with an analyte embedded with the device and deliver quantitative or semi-quantitative information utilizing a biological recognition element, processed and transferred to any smart devices. They offer real time biomarker monitoring, minimal biomolecule concentration along with high sensitivity and specificity, thus reducing the possibility of false positive and false negative in testing process. This would in turn enable the opportunity to share clinical data with clinicians could enable better predictions based on innovative algorithms based on big data ultimately better diagnosis, prognosis, and treatment for the patient. This narrative reviews the developments and advancements in different saliva based biosensors used in the early detection of oral cancer. We also explain the methods used by biosensors to target different types of biomarkers and focused on biosensors that function at the molecular level.

Zenodo (CERN European Organization for Nuclear Research)
International Association for Dental Research (US)
Openalex Percentile: Top 34%
Oral Health Pathology and Treatment
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