Top articles published this week include several interviews to preview the upcoming SciX Conference, a recent study using an epidermal spectroscopic scanning (ESS) device to detect skin cancer, and a news story about machine learning for meteorite classification.
This week, Spectroscopy published various articles that covered many topics in analytical spectroscopy. This week’s articles feature topics such as clinical analysis and outer space. Much attention is given to spectroscopic techniques including surface-enhanced Raman spectroscopy (SERS), machine learning, and process analytical technology (PAT), among others. Below, we’ve highlighted some of the most popular articles, according to our readers and subscribers. Happy reading!
Joseph P. Smith Named 2024 Emerging Leader in Molecular Spectroscopy by Spectroscopy Magazine
Joseph P. Smith, Director of Process R&D Enabling Technologies at Merck, has been awarded the 2024 Emerging Leader in Molecular Spectroscopy Award for his impactful work in the pharmaceutical industry. Smith’s research in vibrational and electronic spectroscopy, biocatalysis, and data analysis has advanced pharmaceutical process development, particularly in biologics and vaccines (1). Since joining Merck in 2017, he has authored 53 articles and integrated machine learning and spectroscopy into process analytical technology (PAT) (1). Smith is also recognized for his mentorship and advocacy for early-career scientists and students with disabilities (1). He will present a plenary lecture at the 2024 SciX conference.
DermaSensor Device Demonstrates Ability to Improve Detection of Skin Cancer
DermaSensor, a health technology company, recently published a study demonstrating the effectiveness of its handheld epidermal spectroscopic scanning (ESS) device in detecting skin cancer. The device was tested by primary care clinicians (PCCs) on 178 lesions, showing 90.0% diagnostic sensitivity and 60.7% specificity compared to biopsy or dermatologist assessments (2). Without the device, PCCs had lower sensitivity. The study highlights trends in analytical spectroscopy, particularly the development of portable, non-invasive tools for real-time diagnostics. These devices not only enhance clinical analysis, but they also reduce costs and are expected to improve healthcare across multiple industries (2).
At SciX 2024, Jason Dwyer from the University of Rhode Island in Kingstown, RI, will receive the American Electrophoresis Society’s Mid-Career Award for his achievements. Dwyer, an associate professor of chemistry, specializes in nanopore technology and spectroscopy. In a recent interview, he shared insights on his research and the award (3).
Machine Learning Used for Meteorite Classification to Unlock Asteroid Composition Mysteries
A new study led by the Planetary Science Institute, Mount Holyoke College, and UMass Amherst introduces machine learning (ML) to enhance asteroid composition analysis using meteorite spectra. By applying logistic regression to a dataset of 1,422 meteorite spectra, researchers achieved 92% classification accuracy, linking meteorite types to asteroid parent bodies (4). This method surpasses traditional asteroid taxonomies, providing direct mineralogical insights into asteroid compositions. The study’s ML-based approach, combined with spectroscopy, offers a robust framework for predicting asteroid compositions, deepening our understanding of the Solar System's formation and history (4). Future research aims to refine the model with expanded spectral data.
At SciX 2024, Conor L. Evans will receive the Clara Craver Award, presented by The Coblentz Society, for his contributions to applied vibrational spectroscopy. Evans, an Associate Professor at Harvard Medical School in Cambridge, Massachusetts focuses on developing optical tools for biomedical research and clinical applications. His recent work includes innovative chemical imaging techniques like S4RS (5).
AI-Powered SERS Spectroscopy Breakthrough Boosts Safety of Medicinal Food Products
April 16th 2025A new deep learning-enhanced spectroscopic platform—SERSome—developed by researchers in China and Finland, identifies medicinal and edible homologs (MEHs) with 98% accuracy. This innovation could revolutionize safety and quality control in the growing MEH market.
AI-Driven Raman Spectroscopy Paves the Way for Precision Cancer Immunotherapy
April 15th 2025Researchers are using AI-enabled Raman spectroscopy to enhance the development, administration, and response prediction of cancer immunotherapies. This innovative, label-free method provides detailed insights into tumor-immune microenvironments, aiming to optimize personalized immunotherapy and other treatment strategies and improve patient outcomes.
New AI-Powered Raman Spectroscopy Method Enables Rapid Drug Detection in Blood
February 10th 2025Scientists from China and Finland have developed an advanced method for detecting cardiovascular drugs in blood using surface-enhanced Raman spectroscopy (SERS) and artificial intelligence (AI). This innovative approach, which employs "molecular hooks" to selectively capture drug molecules, enables rapid and precise analysis, offering a potential advance for real-time clinical diagnostics.
Best of the Week: Chewing Gum with SERS, Soil Carbon Analysis, Lithium-Ion Battery Research
January 17th 2025Top articles published this week include a Q&A interview that discussed using surface-enhanced Raman spectroscopy (SERS) to investigate microplastics released from chewing gum and an article about Agilent’s Solutions Innovation Research Award (SIRA) winners.