Nanoscale Sensor Technologies for Disease Detection via Volatolomics

Area of Science:

• Biomedical Engineering
• Analytical Chemistry
• Nanotechnology

Background:

• Delayed diagnoses and ineffective treatments hinder disease management.
• There is a critical need for cost-effective, minimally invasive early detection technologies.
• Volatolomics, analyzing volatile organic compounds (VOCs) in body fluids, presents a promising diagnostic avenue.

Purpose of the Study:

• To review advances in nanomaterial-based sensors and AI for volatolomics-based disease detection.
• To discuss technological challenges and confounding factors in VOC analysis.
• To highlight future perspectives for volatolomics in diagnostics.

Main Methods:

• Review of current literature on nanomaterial sensors for VOC detection.
• Analysis of artificially intelligent sensing arrays for disease monitoring.
• Discussion of sensor selection criteria based on target VOCs and limitations.

Main Results:

• Nanomaterial-based sensors and AI arrays show potential for early disease detection and monitoring.
• Technological gaps and confounding factors in VOC testing are identified.
• Sensor selection strategies and limitations for volatolomics are discussed.

Conclusions:

• Volatolomics, utilizing VOC profiles, offers a powerful approach for early disease detection.
• Nanomaterial sensors and AI are key enablers for advancing volatolomics in diagnostics.
• Addressing technological challenges will pave the way for widespread clinical application.