Vibrational spectroscopy, a technique essential for analyzing chemical components in biological compounds, cells, organisms, tissues, and bioactivity products, plays a significant role in various fields. Its applications span many fields, from chemistry, microbiology, medicine, agriculture, and food science to forensics, botany, and environmental assessment, providing critical bioanalytical insights.
The upcoming Pittcon 2024 will feature a range of experts discussing the recent advancements in these techniques. The conference will highlight their importance in everyday life, such as in routine health exams, security, and food quality assessments. Additionally, it will explore how artificial intelligence (AI) solutions are further enhancing the capabilities and applications of vibrational spectroscopy.
Vibrational Spectroscopy Methods
Key methods of vibrational spectroscopy, such as infrared (IR), near-infrared (NIR), and Raman spectroscopy, are crucial for analyzing complex biological samples. They provide both quantitative and qualitative insights into the structure and configuration of the compounds composing these samples. A significant advantage of these techniques, contributing to their widespread use, is their non-invasive nature. This allows for rapid and sensitive analysis without the need to disrupt or alter the biological samples, making them ideal for a variety of applications.1
The advancement of portable vibrational spectroscopy devices has significantly expanded the applicability of these techniques across various disciplines, enabling onsite, real-time evaluation of biological samples, and making them particularly valuable for bioanalysis. Their use has been especially impactful in fields like forensics, pharmaceuticals, and food safety. The ability of these portable spectral devices to provide immediate, reliable, and quantitative information in real-time has proven to be a game-changer, allowing for faster decision-making and more efficient processes in these critical areas.2,3,4
With Pittcon 2024 just around the corner, the “Bioanalytics & Life Sciences” track will be a key talking point, highlighting the need for these spectroscopy techniques for developing important everyday life technologies. Advancements and challenges with spectral techniques will be discussed, along with AI’s fundamental role in furthering these advancements and addressing accompanying challenges.
Advancements and Challenges in Novel Vibrational Spectroscopy
Recent improvements in spectrometers and imaging capabilities produce big datasets with many individual data points from different sources in a much shorter time frame, providing us with a more comprehensive understanding of sample biochemical compositions. Yet, challenges arise when trying to analyze such large datasets with highly complex matrices. AI is vital in addressing these challenges, allowing us to visualize the data in a readily interpretable format, necessary for real-world, everyday life applications.5
Data-driven machine learning (ML) methods have been successfully utilized in the last several years, benefitting a wide range of domains. Algorithms developed using AI enhance the fitting and feature extraction of data analysis, providing a clearer and more reliable understanding of the chemical components of biological samples.6 As a result, research is now focused on developing these AI algorithms for the automatic extraction of significant, in-depth information from spectral readings for increased pertinence in various biological disciplines for everyday life applications.7
Artificial Intelligence and Near-Infrared Spectroscopy
Next year, the Pittcon “Novel Vibrational Spectroscopy Empowered by Artificial Intelligence” symposium will offer major insights into the recent challenges and advancements in novel vibrational spectroscopy, along with future enhancements in the application of AI for improved spectral data analysis.
Prof. Christian Huck (head of the Institute of Analytical Chemistry and Radiochemistry, University of Innsbruck, Austria) will be a keynote speaker at this symposium and will discuss how combining ML algorithms with NIR spectroscopy is enhancing the bioanalytical applications of this tool. Prof. Huck is an expert in the field, with 330 peer-reviewed papers within the field of analytical chemistry, and a co-author of the book “NIR Spectroscopy.” AI has facilitated the use of pocket-sized NIR spectroscopy devices by the general public to provide fast, reliable, real-time information on food quality and pharmaceuticals without any need for specialist expertise. Prof. Huck will also discuss the wide applicability of these combined methods in agriculture and environmental monitoring.
Artificial Intelligence and Biosensors
Wearable biosensors provide patients with information about their biochemical dynamics to help address current shortcomings in centralized, reactive healthcare in everyday life. However, data output from such devices is challenging to analyze because of highly complex result causality. AI biosensors offer a much more precise examination of patients’ day-to-day health as they facilitate highly improved data acquisition and analysis.8
Pittcon’s “Artificial intelligence biosensor: challenges and prospects” symposium, hosted by Prof. Zhang Xueji (Vice President of Shenzhen University and Associate Editor of RSC Sensors & Diagnostics), will explain how AI is helping to bridge the gap between data acquisition and analysis for more reliable interpretations. The session will also focus on how microprocessor diagnostic algorithms confirm sensor outputs and explain how big data processing, with a self-contained space that holds historical data and the parameters, is drastically enhancing the performance of biosensors. He will also discuss embedded microprocessors with adaptive functions that can reconstruct parameters with regard to behavioral principles.
Prof. Zhang Xueji has many technological achievements within biosensor production, having created more than 30 industrialized technologies that are utilized in over 100 countries. He will provide a necessary understanding of how best to use and further develop AI biosensors, expanding the everyday use of these devices.
International Corporation Involvement
Pittcon 2024 will also be host to some of the most innovative bioanalytical corporations, including Hamamatsu Corporation and CPI International. Hamamatsu Corporation is at the forefront of photonics, advancing AI strategies to further commercialize the use of light/light-related devices for global health benefits, while CPI International has 40+ years of experience in providing and improving different spectroscopy techniques for worldwide, everyday life applications.
Discover More at Pittcon 2024
AI is greatly advancing vibrational spectroscopy applications in the biological sciences, bridging the gap between data acquisition and analysis for big datasets with complex matrices. Pittcon will host renowned leaders in this field and provide a thorough understanding of how AI is pathing the way to faster, more accurate, and informative vibrational spectroscopy results that have many everyday life applications.
If you are interested in learning more about AI vibrational spectroscopy advancements, you can find out more by visiting the Pittcon Session lineup to gain an overview of some of the talks on offer.
References and Further Reading
- Beć, K.B., Grabska, J. and Huck, C.W. 2020. Biomolecular and bioanalytical applications of infrared spectroscopy–A review. Analytica chimica acta. 1133, pp.150-177.
- Muro, C.K., Doty, K.C., Bueno, J., Halamkova, L. and Lednev, I.K. 2015. Vibrational spectroscopy: recent developments to revolutionize forensic science. Analytical chemistry. 87(1), pp.306-327.
- McVey, C., Elliott, C.T., Cannavan, A., Kelly, S.D., Petchkongkaew, A. and Haughey, S.A. 2021. Portable spectroscopy for high throughput food authenticity screening: Advancements in technology and integration into digital traceability systems. Trends in food science & technology. 118, pp.777-790.
- Deidda, R., Sacre, P.Y., Clavaud, M., Coïc, L., Avohou, H., Hubert, P. and Ziemons, E. 2019. Vibrational spectroscopy in analysis of pharmaceuticals: Critical review of innovative portable and handheld NIR and Raman spectrophotometers. TrAC Trends in Analytical Chemistry. 114, pp.251-259.
- Morais, C.L., Lima, K.M., Singh, M. and Martin, F.L. 2020. Tutorial: multivariate classification for vibrational spectroscopy in biological samples. Nature Protocols. 15(7), pp.2143-2162.
- Yang, J., Xu, J., Zhang, X., Wu, C., Lin, T. and Ying, Y. 2019. Deep learning for vibrational spectral analysis: Recent progress and a practical guide. Analytica chimica acta,.1081, pp.6-17.
- Houhou, R. and Bocklitz, T. 2021. Trends in artificial intelligence, machine learning, and chemometrics applied to chemical data. Analytical Science Advances. 2(3-4), pp.128-141.
- Jin, X., Liu, C., Xu, T., Su, L. and Zhang, X. 2020. Artificial intelligence biosensors: Challenges and prospects. Biosensors and Bioelectronics. 165, p.112412.
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