Advancing healthcare through laboratory on a chip technology: Transforming microorganism identification and diagnostics

Table 1 Comparison of laboratory-on-a-chip technology with traditional methods for microorganism identification

Aspect	Laboratory-on-a-chip	Traditional methods
Speed of identification	Rapid results within minutes to hours	Longer turnaround time (hours to days)
Sensitivity and specificity	High sensitivity and specificity	Variable sensitivity and specificity depending on method and sample quality
Portability	Compact and portable devices	Laboratory-based equipment requiring specialized facilities
Sample size	Minimal sample volume required	Larger sample volume often needed
Automation	Automated processes for streamlined workflow	Manual handling of samples with potential for human error
Cost	Initial investment may be higher but cost-effective over time	Lower initial cost but higher operational costs
Integration with other technologies	Easily integrated with biosensors, artificial intelligence, and data analytics	Limited integration capabilities with other technologies
Accessibility	Suitable for use in remote or resource-limited settings	Reliant on centralized laboratories, limiting accessibility

Table 2 Applications and potential expansions of laboratory-on-a-chip technology

Application	Description
Clinical diagnostics	Rapid point-of-care testing for infectious diseases, biomarker analysis, and chronic disease monitoring
Epidemiology and public health	Real-time monitoring of infectious disease outbreaks, tracking of pathogen transmission, and mass screening in remote or resource-limited settings
Personalized medicine	Tailored treatments based on rapid identification of pathogens, biomarkers, and patient-specific responses to therapies
Environmental monitoring	Detection of pathogens, toxins, and pollutants in water and air, ensuring safety and environmental protection
Food safety	Monitoring of foodborne pathogens and contaminants, quality control in food processing, and compliance with safety standards
Biomedical research	Single-cell analysis, organ-on-a-chip models, and disease modeling for drug testing and understanding disease mechanisms
Agriculture	Soil and crop health monitoring, livestock disease detection, and ensuring food security through improved agricultural practices