BioMarkers
Biological Markers and Health Outcomes
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This project explores how the human body’s natural markers—such as fingerprints, nails, sweat, and hair—can reveal powerful insights about health and behavior. By analyzing these biomarkers, we can identify unique biological signatures that correspond to specific conditions, exposures, and risks.
At the core of the project is a large-scale data effort that matches health outcomes with distinctive biomarker patterns. Using artificial intelligence and advanced computational methods, we are able to detect subtle signals that traditional approaches often miss.
This allows us not only to predict and assess health conditions but also to recognize signs of drug usage or exposure to drug production environments.
How can biomarker testing meaningfully contribute to the healthcare and security spheres?
For healthcare, the ability to rapidly read biomarkers could lead to earlier diagnoses, personalized treatment, and improved patient outcomes. For security, it offers new tools to detect illicit activity, monitor public health threats, and provide faster responses in high-risk environments.
By combining big data, AI, and biomarker science, this project seeks to advance our understanding of the human body and expand the possibilities of health and security innovation.
Patents Filled:
“Detection of Fentanyl in Human Nails Using ATR-FTIR Spectroscopy Combined with Machine Learning for Toxicological Analysis.”
“Detection of Fentanyl in Human Nails Using Raman Spectroscopy Combined with Machine Learning for Toxicological Analysis.”
Presentation on Physiological Markers:
Published Papers:
Mindy Greco, Morgan Eldridge, Emilynn Banks, Lenka Halámková, and Jan Halámek. Metabolite Monitoring Concept for the Biometric Identification of Individuals from the Skin Surface.
Mindy Hair, Adrianna Mathis, Erica Brunelle, Lenka Halamkova, and Jan Halamek. Metabolite Biometrics for the Differentiation of Individuals.
Erica Brunelle, Brenna Thibodeau, Alyssa Shoemaker, and Jan Halamek. Step toward Roadside Sensing: Noninvasive Detection of a THC Metabolite from the Sweat Content of Fingerprints.
Mindy E. Hair, Ryan Gerkman, Adrianna I. Mathis, Lenka Halamkova, and Jan Halamek. Noninvasive Concept for Optical Ethanol Sensing on the Skin Surface with Camera-Based Quantification.
Aubrey Barney, Vaclav Trojan, Radovan Hrib, Ashley Newland, Jan Halámek, & Lenka Halámková. (2025). From spectra to signatures: Detecting fentanyl in human nails with ATR–FTIR and machine learning. Sensors, 25(227). https://doi.org/10.3390/s25010227
Bilkis Mitu, Vaclav Trojan, Radovan Hrib, & Lenka Halámková. (2024). Attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) analysis of human nails: Implications for age determination in forensics. Journal of Forensic Sciences, 70, 150–160. https://doi.org/10.1111/1556-4029.15641
Vrunda Rania, Ashley Newland, Lenka Halámková, Vaclav Trojan, Radovan Hřib, & Jan Halámek. (2024). ACS Omega, 9(38), 40234-40241. https://doi.org/10.1021/acsomega.4c06655
Bilkis Mitu, Vaclav Trojan, Lenka Halámková. (2023) Sex Determination of Human Nails Based on Attenuated Total Reflection Fourier Transform Infrared Spectroscopy in Forensic Context. Sensors, 23, 9412. https://doi.org/10.3390/s23239412.
Bilkis Mitu, Migdalia Cerda, Radovan Hrib, Vaclav Trojan, Lenka Halámková. (2023) Attenuated Total Reflection Fourier Transform Infrared (ATR FT-IR) spectroscopy For Forensic Screening of Long-Term Alcohol Consumption from Human Nails. ACS Omega, 8, 24, 22203–22210. https://doi.org/10.1021/acsomega.3c02579.
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