New SERS Platform Enhances Real-Time Detection of Cardiovascular Drugs in Blood

In a recent study, a team of researchers from Harbin Medical University and the Research Unit of Health Sciences and Technology (HST) in Finland has developed a powerful new tool for detecting cardiovascular drugs in blood with improved sensitivity and speed. This study, which was published in Biosensors and Bioelectronics, presented a surface-enhanced Raman spectroscopy (SERS) platform that uses artificial intelligence (AI) analysis and “molecular hook” technology to improve clinical diagnostics (1). The study’s findings show how advances in technology can result in improved patient outcomes, especially those with cardiovascular diseases.

According to the American Heart Association, cardiovascular diseases, which include strokes and heart disease, claimed more lives in the United States than any type of cancer (2). By tracking eight factors, which include smoking, healthy diet, physical activity, sleep health, control of cholesterol, blood pressure, and blood sugar, and body weight, the American Heart Association determines the overall heart health of the country and tracks country-wide trends (2).

Abstract image of a man with chest pain. Health concept. Background with selective focus and copy space. Generated by AI. | Image Credit: © top images - stock.adobe.com

However, the data do show that cardiovascular health is a major problem in the United States. As a result, numerous drug manufacturers have created, tested, and developed various types of drugs to help alleviate symptoms and improve a patient’s overall health. Some of these type of drugs include the following: Angiotensin-converting enzyme (ACE) inhibitors and angiotensin receptor blockers (ARBs), which widen the blood vessels to increase blood flow; beta blockers, which help control the heart rate and ensure it doesn’t beat too quickly; aldosterone antagonists, which are designed to lower blood pressure; and diuretics, which help the body rid itself of extra fluids that are accumulated by patients afflicted with heart failure (3).

Although these drugs have been mostly effective in helping patients with heart issues, one of the biggest ongoing challenges in the industry is detecting these medications in the bloodstream. The cause of this issue is interference from large biomolecules, such as hemoglobin and serum proteins, which hinder traditional methods from detecting these medications in a patient’s bloodstream.

In their study, the research team tried to solve this issue through the development of their SERS platform. To build their platform, the researchers used self-assembled silver nanoparticles (Ag NPs) and DNA-based molecular hooks that selectively captured small-molecule drugs while excluding larger interfering biomolecules (1). Their approach was to use the nanoparticles to attract and bind small-drug molecules. By doing so, they were able to isolate the signal without interference from proteins and other large molecules (1).

One of the key aspects of this SERS platform is the A13 molecule. In their platform, the A13 molecule served two purposes. First, it drove the self-assembly of Ag NPs; second, it also served as an efficient hook to capture drugs such as dobutamine hydrochloride and milrinone from blood samples (1). The system also incorporates calcium ions, which induce aggregation of the nanoparticles to create dense “hotspot” regions, which are defined as localized zones of high electromagnetic field intensity that greatly enhance the Raman signal of captured molecules (1).

The design of this SERS platform was also important for the analysis. It allowed for detection limits of 10 picograms per milliliter (pg/mL) for dobutamine hydrochloride and 10 nanograms per milliliter (ng/mL) for milrinone (1). These limits are significantly below therapeutic thresholds; as a result, it allows clinicians to monitor trace drug levels with improved precision (1).

The last key aspect of this SERS platform is how the team used artificial intelligence (AI) to great effect. The researchers automated the analysis of the Raman spectra by using AI-based recognition algorithms. This allowed them to distinguish drug-specific signals even in complex biological matrices in a significantly reduced amount of time (1). Automating spectral analysis has emerged as one way researchers can quicken clinical diagnostics, which is even more helpful for emergency and intensive care settings.

However, the researchers cautioned that more work needs to be done on their research. For example, the SERS platform is currently unable to quantify drugs across a wide concentration range. Therefore, the system needs to be modified to expand its range so it can analyze high drug concentrations (1).

That being said, the insights gained from this study are important because of what was learned about how to use spectroscopy in clinical diagnostic applications. The ability to monitor cardiovascular drugs in real time with such specificity could lead to more precise dosing, reduce the risk of adverse drug reactions, and improve treatment outcomes for patients with heart conditions (1). As personalized medicine becomes increasingly central to healthcare, innovations like this SERS-AI hybrid platform will continue to emerge to help solve the most concerning health problems.

References

1. Wei, Q.; Zhou, L.; Sun, J.; et al. Rapid Detection of Drugs in Blood Using “Molecular Hook” Surface-enhanced Raman Spectroscopy and Artificial Intelligence Technology for Clinical Applications. Biosens. Bioelectron. 2025, 267, 116855. DOI: 10.1016/j.bios.2024.116855
2. American Heart Disease, 2025 Heart Disease and Stroke Statistics Update Fact Sheet. AHA.org. Available at: https://www.heart.org/en/-/media/PHD-Files-2/Science-News/2/2025-Heart-and-Stroke-Stat-Update/2025-Statistics-At-A-Glance.pdf?sc_lang=en (accessed 2025-05-12).
3. American Heart Association, Medications Used to Treat Heart Failure. AHA.org. Available at: https://www.heart.org/en/health-topics/heart-failure/treatment-options-for-heart-failure/medications-used-to-treat-heart-failure#:~:text=Beta%20blockers%20(also%20known%20as,Inderal%20LA%2C%20and%20InnoPran%20XL) (accessed 2025-05-12).