Neeta Ratanghayra, M.Pharm
Point-of-care testing (POCT), or onsite testing, is rapidly emerging as a potential alternative to conventional laboratory-based diagnostic testing. By providing actionable information at the time and location of care, POCT allows diseases to be diagnosed at an early stage. Emerging POCT trends include the development of less invasive and more continuous testing, growth of miniaturized technologies, and the use of telemedicine for remote monitoring.
The biosensor is the most critical component of point-of-care diagnostics.1 The integration of biosensor systems into POC systems can improve patient care through real-time and remote health monitoring.
Label-based techniques are laborious and time-consuming as they require the attachment or “labeling” of target molecules with labels such as fluorescent dyes, radioisotopes, or epitope tags. This drawback makes label-based techniques impractical for use in POC applications. In contrast to label-based techniques, label-free detection methods depend on the measurement of an inherent property of the query itself, such as molecular weight (e.g. mass spectroscopy) or refractive index (e.g., surface plasmon resonance), to monitor molecular presence or activity. Label-free detection avoids interference due to tagging molecules, which aids in the rapid evaluation of biomolecular interactions in real time. By offering label-free assays with immediate results and employing small and user-friendly devices, biosensor platforms can overcome challenges faced by conventional diagnosis techniques. Additionally, the use of label-free optical sensors for point-of-care applications enables direct and multiplex analysis due to the lack of strong interference from the sample matrix (a major limitation of electrochemical sensors).
Innovative technology platforms that integrate biosensors into POC systems are currently being explored. Label-free biosensors employing impedance spectroscopy, SPR, and white light reflectance spectroscopy are being studied for the development of a more efficient and less time-consuming POCT.
Impedance biosensors are electrical biosensors that help quantify biological molecules in a sample by measuring the changes in the capacitance or resistance caused by the binding of analytes (target molecule) to an immobilized probe. The binding causes a change in the device impedance, which can be measured to quantify the corresponding analyte. Impedance biosensors may be integrated into on-chip systems and require a smaller volume of sample for the measurements compared to laboratory-based platforms. Interdigitated electrode (IDE) arrays are widely used in impedance biosensors. IDE sensors are highly sensitive and have been explored to detect DNA2 and antigen-antibody interactions.3
White light reflectance spectroscopy-based sensing platforms
White light reflectance spectroscopy (WLRS)-based sensing platforms are being explored for the detection of high or low molecular weight analytes.4 These platforms use the reflection of a broadband light beam from an engineered surface to produce an interference fringe in the visible spectrum. WLRS biosensors consist of a reflection probe and a sensing element. The reflection probe is composed of six fibers at the periphery that deliver the light to the surface, and a central fiber that collects the specular reflected light. The sensing element consists of a single layer or stack of films (made from transparent materials with different refractive indices) over a silicon substrate (with moderate reflectance). The emitted light is guided by the reflection probe vertically to the sensing element, where it is reflected by the silicon surface and by the transparent material layers of different refractive indices. The result is an interference spectrum that is collected by the central fiber of the reflection probe and passed on to the spectrometer, where it is continuously recorded. The spectra obtained can be monitored and correlated to respective analyte concentrations.
WLRS is an optical label-free method devoid of any moving optical parts and alignment needs. The non-disposable instrumentation, and the ability to work with complex matrices, make WLRS a cost-effective option. The addition of conventional microelectronic processes to WLRS, along with advanced algorithms, could be beneficial in multi-analyte determinations.
Surface plasmon resonance biosensor
Surface plasmon resonance (SPR) is a surface-sensitive spectroscopic method to probe changes in the refractive index of biosensing material at surfaces of metals. SPR is a label-free, sensitive technique to examine bio-molecular interactions. SPR has been explored for the detection of stroke biomarkers,5 monitoring of tumor antigen-serum antibody interactions, and detection of neurotoxins.
Mobile health care technologies
Smartphone-based imaging and sensing platforms are emerging as promising alternatives to complex diagnostic procedures. The portability, cost-effectiveness, and connectivity of these platforms offer several opportunities for POCT integration.
The computational power of smartphones can be useful for process control and data analysis. The optical sensing capabilities of complementary metal-oxide-semiconductor (CMOS) cameras in smartphones can also be used in imaging-based or spectrometry-based analysis.6 Imaging-based applications include flow cytometry, colorimetry, photoluminescence, and fluorophores. Spectrometry-based smartphone-integrated platforms can be used to probe reactions or changes of molecules. Another important aspect of the integration of POCT with smartphones is that it makes patient data available on a cloud-based server for telemedicine. Telemedicine provides secure access to medical records to both clinicians and patients from anywhere around the globe, which saves time for both the health care organizations and the patients.
Wearable and implantable devices
Wearable and implantable devices enable continuous, longitudinal health monitoring outside the hospital or health care facility. Wearable and implantable technologies sense various disease parameters and can either transfer data to a remote center or automatically perform a function based on what the sensors are reading. This latter feature is especially beneficial for chronic disease and wellness monitoring. The most significant advances in wearable and implantable devices are in the field of diabetes, with a number of devices being developed or commercialized for continuous glucose monitoring (CGM). Besides CGMs, wearables and implantables to monitor cardiac parameters are also available. For example, mobile cardiac outpatient telemetry (MCOT) monitors cardiac patients in real time during normal daily activities, using built-in detection algorithms and cellular technology. The system also helps to detect and capture significant arrhythmic events, even when no symptoms are experienced.
Non-invasive diagnostic techniques have long been desired for several reasons. Invasive methods are not suitable for continuous monitoring. The pain and risk of infection with invasive techniques act as potential barriers to its use. Moreover, invasive methods are time-consuming and pose the risk of needle stick injuries. Non-invasive techniques offer real-time painless measurements of disease-related parameters without the risk of infection. Near-infrared scanning and volatolomics are two innovative examples of non-invasive POCT. Near-infrared spectroscopy is a non-ionizing, inexpensive monitoring and imaging technique that uses near-infrared light to probe tissue optical properties. A portable brain scanner (Infrascanner) is a well-known application of near-infrared to detect traumatic brain injury with intracranial bleeding. The device helps screen individuals who need immediate referral for a CT scan and neurosurgical intervention.
Volatolomics is the study of chemical processes involving volatile organic compounds (VOCs)—metabolites produced as a result of disease processes that alter the normal physiological and metabolic pathways occurring within the disease-affected tissues. Several complex chemical-detection technologies that employ metabolomic approaches to disease diagnostics, with complex instruments such as gas chromatography-mass spectroscopy (GC-MS) and nuclear magnetic resonance (NMR) spectroscopy, have been used to identify disease-associated VOC-metabolites.
The measurement of VOCs by an electronic nose (or e-nose) is an innovative example of volatolomics. Electronic noses are portable sensor systems made up of chemical cross-reactive sensor arrays. The sensors help in characterizing patterns of breath volatile compounds and have algorithms for breath print classification. Enoses provide real-time data and, in conjunction with NMR-based metabolomics of exhaled breath condensate, can identify patients with respiratory diseases such as asthma, chronic obstructive pulmonary disease (COPD), and lung cancer.
Challenges of POCT
Point-of-care technologies are valuable tools for population health, precision medicine, disease prevention, and chronic disease management. However, POCT still faces these potential hurdles:
- POCT errors can be a major source of error compared to other laboratory errors. In a traditional laboratory, issues related to hemolyzed specimens, insufficient specimen, or incorrect specimen can be easily detected; however, the same issues are difficult to detect in POC settings due to non-adherence to standard procedures and use of uncontrolled reagents.
- POCT is generally undertaken by non-laboratory clinical staff, who are primarily involved in delivery of patient care. If incorrectly performed, POCT may present a risk to patient care and its inappropriate use may lead to substantial cost of patient care.
- Rural regions often lack access to the requisite technology for smooth implementation of POCT. There is also often a lack of trained staff to perform the tests and carry out the subsequent diagnoses in rural areas.
- There are security concerns over privacy of personal data with mobile health care technologies. The requirement of international cloud computing standards and the management of big data can also be daunting.
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2. Berdat, Daniel, et al. "Label-free detection of DNA with interdigitated micro-electrodes in a fluidic cell." Lab on a Chip 8.2 (2008): 302-308.
3. Taylor, Richard F., Ingrid G. Marenchic, and Richard H. Spencer. "Antibody-and receptor-based biosensors for detection and process control." Analytica Chimica Acta 249.1 (1991): 67-70.
4. Koukouvinos, Georgios, et al. "Development and bioanalytical applications of a white light reflectance spectroscopy label-free sensing platform." Biosensors 7.4 (2017): 46.
5. Harpaz, Dorin, et al. "Point-of-care surface plasmon resonance biosensor for stroke biomarkers NT-proBNP and S100β using a functionalized gold chip with specific antibody." Sensors 19.11 (2019): 2533.
6. Geng, Zhaoxin, et al. "Recent progress in optical biosensors based on smartphone platforms." Sensors 17.11 (2017): 2449.