Predicting targeted- and immunotherapeutic response outcomes in melanoma with single-cell Raman Spectroscopy and AI
Kai Chang, Mamatha Serasanambati, Baba Ogunlade, Hsiu-Ju Hsu, James Paul Agolia, Ariel Stiber, Jeffrey Gu, Jay Chadokiya, Grayson E. Rodriguez, Prabhjeet Singh, Saurabh Sharma, Amanda Gonçalves, Ojasvi Verma, Fareeha Safir, Nhat Vu, , Jennifer A. Dionne
This paper uses single-cell Raman spectroscopy and machine learning to predict therapeutic response in melanoma, achieving >96% accuracy in cell line classification and 91% accuracy in patient drug resistance inference.
bioRxiv · May 16, 2025 · PreprintCancer Biology