Advancements over the last few years have enhanced sensitivity, specificity, and efficiency in analytical techniques. By providing the necessary tools for the detection, identification, and quantification of substances, analytical chemistry is fundamental in medicine.
Analytical chemistry is often used for quality control and assurance in the pharmaceutical industry or to investigate chemical and biological systems to help healthcare professionals diagnose and understand diseases.
Various approaches allow the tracking of metabolic pathways to monitor the efficacy of therapeutic treatments and their impact on the body. This article highlights recent developments in analytical chemistry and applications in medicine and healthcare.
Image Credit: angellodeco/Shuterstock.com
Fundamental Principles of Analytical Chemistry in Medicine
A variety of analytical techniques contribute to new developments in medicine. Infrared and Raman spectroscopy analyze molecular compositions in biological samples. Chromatographic techniques can separate complex mixtures.
Mass spectrometry – often coupled with chromatography – enables the identification and quantification of proteins, metabolites, and pharmaceuticals.
Improvements in these techniques can allow for more accurate detection of low-abundance biomarkers and trace compounds, providing better ways to monitor health and detect disease earlier, making them invaluable in medical diagnostics.
Analytical Chemistry Trends 2025: Market Insights and Future Forecasts
Modern Applications in Medical Diagnostics
Infrared spectroscopy is a powerful technique for the analysis of complex biofluids such as blood and can be used as a screening tool to detect health conditions. In a recent study, the use of machine learning with IR spectroscopy on plasma samples enabled rapid health screening and identification of conditions such as type-2 diabetes.1
Plasma proteomics allows the estimation of thousands of proteins. Recently, the analysis of protein signatures that can be associated with health status has shown excellent results in the identification of the onset of dozens of diseases, including pulmonary fibrosis and multiple myeloma.2
Point-of-care testing (POCT) is rapidly expanding, as it is directly applicable in the field, reducing patient wait times. Thanks to their user-friendliness and rapidity, various POCT platforms, especially lateral flow immunoassays, smartphone-based biosensors, and paper-based assays, have been used for the diagnosis of infectious diseases in remote areas and underdeveloped regions.3
Lab-on-a-chip (LOC) platforms can mimic in vivo conditions and offer a deep understanding of cellular events. Recently developed LOC platforms showed promise in monitoring breast cancer progression identifying factors that contribute to cancer metastasis.4
Analytical chemist, healthcare
Analytical Chemistry in Drug Development and Pharmacology
Quality control and regulatory compliance in drug development rely heavily on analytical chemistry to ensure the safety and efficacy of pharmaceuticals. High-performance liquid chromatography (HPLC) offers high resolution and reproducibility in quantifying active pharmaceutical ingredients (APIs).
Chromatographic methods are also effective in monitoring drug levels during therapy, helping ensure the effectiveness of treatment.
HPLC and ultra-high-performance liquid chromatography (UHPLC) were used to determine the concentration of olanzapine (an antipsychotic drug for the treatment of schizophrenia) and its metabolites in blood, plasma, and serum, as well as hair and saliva.5
High-throughput screening (HTS) methods – often based on automated fluorescence or luminescence spectroscopy assays – can analyze a sample in a few seconds, allowing the screening of thousands of samples per day, which is particularly useful in the evaluation of potential drug candidates.
Metabolomics studies enable the identification of biomarkers and the development of targeted therapies in personalized medicine. Thanks to the ability to determine changes associated with both lifestyle and pathological processes, metabolomics is very promising in medicine for the development of new diagnostic tests and optimized drug therapy.6
How AI is Transforming Spectroscopy
Innovations in Medical Imaging and Spectroscopy
Magnetic resonance imaging (MRI), nuclear magnetic resonance (NMR), and positron emission tomography (PET) are techniques that provide non-invasive diagnostic insights. These imaging tools generate vast amounts of data that require efficient analysis and interpretation.
Fortunately, advancements in AI, including deep learning algorithms and convolutional neural networks, have significantly improved the accuracy and efficiency of medical image analysis, enabling rapid and accurate detection of abnormalities leading to the early identification of tumors during radiological examinations.7
In tissue analysis, fluorescence spectroscopy provides a non-invasive approach for discriminating among tissue types and assessing their molecular composition. In contrast, advancements in Raman spectroscopy have contributed to the early detection of cancer.
Raman spectra of in vivo samples in a clinical trial showed to be a promising tool in the detection of cervical cancer in early stages, with results comparable with histopathology reports.8
Future Directions and Challenges
Automation and miniaturization are expected to make analytical techniques more accessible and efficient, facilitating widespread adoption in various healthcare settings.
However, several challenges persist, particularly regarding data management and standardization across laboratories. As analytical methods become more complex, ensuring consistency and accuracy of results is paramount.
Some of the factors that are limiting the wide adoption of POCT, despite the many advantages, are the relatively high cost of devices and the lack of standardization across different devices and tests.
Concerning HTS, the cost per analysis is also an important limitation. In addition, the rapid collection of large volumes of data must be supported by the capability to process data quickly and efficiently.
This is being addressed through the exploration of AI models, which also reduce human error and save time. However, considerations around AI-based approaches, specifically related to model interpretability and regulatory aspects, must also be addressed.
Analytical Chemistry in Personalized Medicine
Conclusion
Analytical chemistry plays a crucial role in healthcare, driving advancements in drug development, diagnostics, and therapies. In particular, the miniaturization of analytical devices in point-of-care testing and lab-on-a-chip technologies can enable rapid, on-site analysis.
Nevertheless, ongoing research and innovation are essential to overcoming challenges and improving efficiency.
Future integration with AI and machine learning holds great promise for more sophisticated techniques, enhancing medical research, diagnostics, and personalized healthcare solutions.
References
- Eissa, T., Leonardo, C., Kepesidis, K. V., Fleischmann, F., Linkohr, B., Meyer, D., Zoka, V., Huber, M., Voronina, L., Richter, L., Peters, A. & Žigman, M. (2024). Plasma infrared fingerprinting with machine learning enables single-measurement multi-phenotype health screening. Cell Reports Medicine, 5, 101625.https://doi.org/10.1016/j.xcrm.2024.101625. Available: https://www.sciencedirect.com/science/article/pii/S266637912400329X
- Carrasco-Zanini, J., Pietzner, M., Davitte, J., Surendran, P., Croteau-Chonka, D. C., Robins, C., Torralbo, A., Tomlinson, C., Grünschläger, F., Fitzpatrick, N., Ytsma, C., Kanno, T., Gade, S., Freitag, D., Ziebell, F., Haas, S., Denaxas, S., Betts, J. C., Wareham, N. J., Hemingway, H., Scott, R. A. & Langenberg, C. (2024). Proteomic signatures improve risk prediction for common and rare diseases. Nature Medicine, 30, 2489-2498.10.1038/s41591-024-03142-z. Available: https://doi.org/10.1038/s41591-024-03142-z
- Shang, M., Guo, J. & Guo, J. (2023). Point-of-care testing of infectious diseases: recent advances. Sensors & Diagnostics, 2, 1123-1144.10.1039/D3SD00092C. Available: http://dx.doi.org/10.1039/D3SD00092C
- Firatligil-Yildirir, B., Yalcin-Ozuysal, O. & Nonappa (2023). Recent advances in lab-on-a-chip systems for breast cancer metastasis research. Nanoscale Advances, 5, 2375-2393.10.1039/D2NA00823H. Available: http://dx.doi.org/10.1039/D2NA00823H
- Czyż, A., Zakrzewska-Sito, A. & Kuczyńska, J. (2024). A Review of Advances in Bioanalytical Methods for the Detection and Quantification of Olanzapine and Its Metabolites in Complex Biological Matrices. Pharmaceuticals (Basel), 17.10.3390/ph17030403.
- Trifonova, O. P., Maslov, D. L., Balashova, E. E. & Lokhov, P. G. (2023). Current State and Future Perspectives on Personalized Metabolomics. Metabolites, 13.10.3390/metabo13010067.
- Pinto-Coelho, L. (2023). How Artificial Intelligence Is Shaping Medical Imaging Technology: A Survey of Innovations and Applications. Bioengineering (Basel), 10.10.3390/bioengineering10121435.
- Hanna, K., Krzoska, E., Shaaban, A. M., Muirhead, D., Abu-Eid, R. & Speirs, V. (2022). Raman spectroscopy: current applications in breast cancer diagnosis, challenges and future prospects. British Journal of Cancer, 126, 1125-1139.10.1038/s41416-021-01659-5. Available: https://doi.org/10.1038/s41416-021-01659-5
Further Reading