We implement a machine learning classification of similar proteins by PCA mixed with multipeak fitting on SERS spectra for effective discrimination based on valid biological differences.

Unique characteristics of SERS including the possibility to reveal the compositional and structural content of trace amounts of biological samples without any pre‐treatment, depict this technique as a promising label‐free alternative to standard analytical methods. Despite significant advancements, current SERS substrates for biomolecule detection suffer from a number of issues still impeding their routine usage and commercial exploitation, including complex and expensive fabrication procedures and scarce standardization perspectives. Herein a combined bottom up/top down scheme based on flow‐through method plus laser patterning is proposed to prepare dot arrays of silver nanowires on a hydrophobic substrate for catching the analyte content from a minute amount of liquid sample and its rapid SERS inspection. As a consequence, a simple spot‐on analysis specifically adapted for reliable identification and characterization of molecules of biomedical interest is made possible. Our attempt may represent a concrete chance for progressing SERS toward widespread commercially viable sensing applications including diagnostics at the point‐of‐need settings and on‐site analyses.