Review of Biomarker Sensor Technologies Ready for Widespread Use: Molecular Detection for Disease Monitoring

Electrochemical and optical sensors for detecting molecular biomarkers like metabolites through non-invasive methods in wearable devices have the greatest potential for widespread practical use in disease monitoring and management

From a scientific perspective, the growth of medical wearables depends not only on the ability to detect specific biomarkers but also on the certainty of a prognosis or a diagnosis that is based on the presence of one or a combination of biomarkers indicating the existence (or future existence) of a medical condition in the patient. The key scientific issues are twofold: the ability to identify the correlation between a single or a combination of biomarkers that would indicate the existence of a specific medical condition with sufficient certainty, and the ability to detect these biomarkers at sufficiently low concentrations.

Biomarkers are measurable indicators of some biological state or condition, serving as vital tools for early disease detection, monitoring disease progression, and evaluating therapeutic responses. The identification and validation of reliable biomarkers are crucial in the development of personalized medicine and the advancement of medical wearables.

The quest for accurate and sensitive biomarker detection has driven researchers to explore various categories of biomarkers, each with its unique characteristics and potential applications. From molecular biomarkers, such as chemical, protein, and genetic markers, to cellular biomarkers and imaging (or digital) biomarkers, the diversity of these indicators offers a wealth of opportunities for early diagnosis, prognosis, and treatment monitoring.

Here we will take a look at the broad category of these biomarkers and then provide a review of the sensor type and detection mechanisms for each category. As mentioned above we can categorize medical bio-markers in a couple of different ways. They can be broadly categorized into the following main types:

1. Molecular biomarkers
   • Chemical biomarkers (e.g. metabolites, inborn errors)
   • Protein biomarkers (e.g. glycated hemoglobin, angiotensin-converting enzyme)
   • Genetic biomarkers (e.g. DNA mutations, SNPs, karyotypes)
2. Cellular biomarkers (e.g. cell morphology, physiology)
3. Imaging biomarkers

Additionally, biomarkers can also be classified based on their applications or characteristics:

1. Susceptibility/risk biomarkers (predict likelihood of developing a disease)
2. Diagnostic biomarkers (detect or confirm presence of a disease)
3. Prognostic biomarkers (predict likelihood of clinical events in patients with the disease)
4. Predictive biomarkers (predict response to a therapeutic intervention)
5. Pharmacodynamic/response biomarkers (show that a biological response has occurred in an individual)
6. Monitoring biomarkers (monitor the disease state or exposure to a medical product/environmental agent)
7. Safety biomarkers (indicate potential adverse effects)^1,2,3

As medical wearables continue to evolve, the ability to accurately detect and identify biomarkers will be critical. By exploring the different types of biomarkers, their detection mechanisms, and their use as diagnostic and prognostic indicators with sufficient certainty, researchers can unlock new frontiers in personalized medicine and revolutionize the way we approach healthcare.

Molecular biomarkers, which include chemical biomarkers, protein biomarkers, and genetic biomarkers, can be detected using various mechanisms and techniques outlined here:

Chemical Biomarkers

Chemical biomarkers, such as metabolites and inborn errors, can be detected using the following methods:

1. Electrochemical sensors: These sensors employ electrochemical techniques like amperometry, voltammetry, or impedance spectroscopy to detect and quantify chemical biomarkers. Examples include glucose sensors and sensors for detecting metabolic disorders.^4,5
2. Optical sensors: Techniques like surface-enhanced Raman spectroscopy (SERS), colorimetric assays, and fluorescence-based methods can be used to detect chemical biomarkers optically.⁶

These detection methods can be either invasive (requiring a blood or tissue sample) or non-invasive, depending on the biofluid used for analysis. Non-invasive methods may involve analyzing biofluids like sweat, tears, or saliva using wearable sensors.⁴

Protein Biomarkers

Protein biomarkers can be detected using the following methods:

1. Immunoassays: Techniques like enzyme-linked immunosorbent assay (ELISA) and lateral flow assays rely on specific antibody-antigen interactions to detect and quantify protein biomarkers.⁶
2. Surface Plasmon Resonance (SPR): SPR-based sensors can detect protein biomarkers by measuring changes in the refractive index upon binding to immobilized ligands or antibodies.^7,6
3. Electrochemical sensors: Electrochemical techniques, such as amperometry and impedance spectroscopy, can be used to detect protein biomarkers by employing specific recognition elements like antibodies or aptamers.⁵

These methods can be invasive (requiring a blood or tissue sample) or non-invasive, depending on the biofluid used for analysis. Wearable sensors can potentially enable non-invasive detection of protein biomarkers in biofluids like sweat or tears.⁴

Genetic Biomarkers

Genetic biomarkers, such as DNA mutations, SNPs, and karyotypes, can be detected using the following methods:

1. Electrochemical sensors: Electrochemical techniques like voltammetry and impedance spectroscopy can be used to detect DNA or RNA biomarkers by employing specific recognition elements like aptamers or complementary DNA probes.^4,5
2. Optical sensors: Techniques like fluorescence-based methods and surface-enhanced Raman spectroscopy (SERS) can be used to detect genetic biomarkers by employing specific labeling or recognition elements.⁸

These methods typically require invasive sampling of blood or tissue for genetic material extraction and analysis. However, ongoing research aims to develop non-invasive methods for detecting genetic biomarkers in biofluids like urine or saliva using wearable sensors.⁴

Cellular biomarkers

The detection of cellular biomarkers is generally more challenging than molecular biomarkers, as cells are larger and more complex entities. Additionally, many cellular biomarkers may require invasive sampling methods like biopsies or blood draws. The focus is primarily on molecular biomarkers like metabolites, proteins, and genetic markers. However, the general approaches for detecting cellular biomarkers are imaging techniques, electrochemical and optical sensors.

Further research is needed to develop practical, non-invasive sensors for continuous monitoring of cellular biomarkers in wearable devices.

Imaging Biomarkers

Imaging biomarkers are typically detected using non-invasive imaging modalities and techniques. Here are some of the key detection mechanisms, technologies, and sensor types for imaging biomarkers:

1. Magnetic Resonance Imaging (MRI):
   • MRI can detect various imaging biomarkers related to tumor anatomy, physiology, and metabolism.
   • Techniques like diffusion-weighted MRI, perfusion MRI, and magnetic resonance spectroscopy can provide information about cellular density, vascular properties, and metabolic profiles, respectively.
   • MRI is a non-invasive imaging modality that does not involve ionizing radiation.
2. Positron Emission Tomography (PET):
   • PET imaging can detect molecular imaging biomarkers by using radiolabeled tracers that target specific biological processes or receptors.
   • Common PET tracers include 18F-fluorodeoxyglucose (FDG) for glucose metabolism, and radiolabeled amino acids, nucleosides, and peptides for various molecular targets.
   • PET imaging is non-invasive but involves the administration of radioactive tracers, which may have some associated risks.
3. Computed Tomography (CT):
   • CT imaging can provide anatomical and structural information, as well as detect certain imaging biomarkers related to tissue density and vascularity.
   • Advanced techniques like dual-energy CT and perfusion CT can provide additional information about tissue composition and blood flow.
   • CT imaging is non-invasive but involves ionizing radiation exposure.
4. Optical Imaging:
   • Techniques like fluorescence imaging, bioluminescence imaging, and optical coherence tomography can detect optical imaging biomarkers related to tissue composition, vascularization, and molecular targets.
   • These techniques often involve the use of exogenous contrast agents or reporter molecules, which may require invasive administration.
5. Radiomics and Artificial Intelligence (AI):
   • Radiomics involves the extraction of quantitative features from medical images, which can serve as imaging biomarkers.
   • AI algorithms, such as machine learning and deep learning, can be used to analyze these imaging features and identify patterns associated with specific diseases or treatment responses.
   • Radiomics and AI techniques are non-invasive and can be applied to various imaging modalities.

It’s important to note that many imaging biomarkers are still in the research and development stage, and their clinical validation and implementation may require further studies and regulatory approvals.

Technology readiness level (TRL)

Based on the information reviewed here, an assessment of the technology readiness levels (TRLs) and practicality of different sensing mechanisms for widespread use in wearable biosensors are given below. Molecular Biosensors:

1. Electrochemical sensors for detecting chemical biomarkers (e.g. metabolites, electrolytes):
   • These are among the most mature technologies, with TRLs of 8-9⁹.
   • Continuous glucose monitoring devices using electrochemical sensors are already commercially available, indicating high practicality for widespread use.
2. Optical sensors (colorimetry, fluorescence, SERS) for chemical/protein biomarkers:
   • These are at TRL 7-8, having been demonstrated in operational environments but may still require further validation¹⁰.
   • Practicality is relatively high, but may have lower sensitivity/selectivity compared to electrochemical sensors for some analytes.
3. Techniques for detecting protein biomarkers (immunoassays, SPR):
   • These are at TRL 4-6, having been validated in lab environments but requiring further development for practical applications¹¹.
   • Lower practicality for widespread use currently due to challenges in integration into wearable devices.
4. Techniques for genetic biomarker detection (electrochemical, optical):
   • Likely at TRL 3-4, proven at concept level but needing substantial further development¹¹.
   • Low practicality for widespread use currently due to sensitivity, selectivity, and sample preparation challenges.

Cellular Biosensors:

• The search results do not provide specific TRL information for cellular biomarker detection techniques.
• Techniques like microscopy, flow cytometry, and electrochemical/optical sensors with specific recognition elements could potentially be used, but would likely require invasive sampling methods.
• Overall practicality for widespread use in wearables is currently low due to the complexity of cellular biomarkers and the need for further research and development.

Imaging Biosensors:

• Imaging modalities like MRI, PET, CT, and optical imaging are well-established for detecting various imaging biomarkers, with TRLs likely in the range of 7-9 for many applications.
• These techniques are non-invasive but may involve ionizing radiation (CT, PET) or administration of contrast agents/tracers.
• While highly practical in clinical settings, their integration into wearable devices for continuous monitoring is currently limited, and further miniaturization efforts are needed.

In summary, electrochemical and optical sensors for detecting molecular biomarkers like metabolites and proteins appear to be the most practical and ready for widespread use in wearable devices today, with TRLs of 7-9. However, the detection of other biomarker types, such as cellular and genetic markers, as well as the integration of imaging techniques into wearables, still requires significant research and development efforts to reach higher TRLs and practical implementation.

Takeaway:

Based on this review, the key takeaway is that electrochemical and optical sensors for detecting molecular biomarkers like metabolites (e.g., glucose, lactate), electrolytes, and physiological parameters are currently the most practical and ready for widespread use in wearable devices.

These wearable biosensors primarily employ the following sensing mechanisms:

1. Electrochemical sensors: Techniques like amperometry, voltammetry, and impedance spectroscopy are well-established for detecting chemical biomarkers such as glucose, lactate, and electrolytes. Continuous glucose monitoring devices using electrochemical sensors are already commercially available and widely used for diabetes management.
2. Optical sensors: Techniques like colorimetry, fluorescence, and surface-enhanced Raman spectroscopy (SERS) can be used to detect molecular biomarkers optically, although they may have lower sensitivity and selectivity compared to electrochemical sensors for certain analytes.

The electrochemical and optical sensors for molecular biomarkers have reached technology readiness levels (TRLs) of 7-9, meaning they have been demonstrated in operational environments and are ready for practical applications.

While still limited in the number and types of biomarkers they can detect, these wearable biosensors have shown promising applications in monitoring chronic conditions like diabetes, cardiovascular diseases, and metabolic disorders. They enable continuous, real-time tracking of relevant biomarkers, which can aid in early disease detection, monitoring disease progression, and evaluating therapeutic responses.

However, the detection of other biomarker types, such as proteins, cellular biomarkers, and genetic markers, is still in the early research stages and requires significant further development to reach higher TRLs and practical implementation in wearable biosensors.

Overall, the potential of wearable biosensors for non-invasive, continuous monitoring of molecular biomarkers are highlighted, but must also emphasize the need for ongoing research to expand their capabilities and address current limitations in sensitivity, selectivity, and the range of detectable biomarkers.