Automated Rapid Organic-Solvent-Free Metabolomics via Arrow–GC–MS: An Optimized Green Workflow for Human Plasma Profiling

ABSTRACT Plasma metabolomics holds strong potential for translational and clinical research, yet its routine implementation is limited by solvent-intensive workflows, extensive sample preparation, and poor scalability. Conventional GC–MS protocols, while analytically robust, rely on large sample volumes, solvent-intensive preparation, and manual handling, limiting throughput, reproducibility and scalability. Here, we introduce AROMA-GC-MS, an automated, solvent-free gas chromatography couple to mass spectrometry (GC-MS) metabolomics workflow based on headspace PAL SPME Arrow, specifically optimized for human plasma profiling under green analytical chemistry principles. Using a systematic one-factor-at-a-time optimization strategy, we established robust conditions for plasma input volume, headspace composition, incubation temperature, extraction time, and desorption parameters. The optimized AROMA-GC-MS protocol enables reproducible detection of over 100 plasma metabolites per run from only 50 µL of plasma, without organic solvent extraction or derivatization, while remaining fully compatible with routine laboratory automation. An optional Arrow-compatible MeOx–TMS derivatization step further expands the accessible chemical space, providing complementary coverage when required. By combining analytical robustness, minimal sample consumption, and a markedly reduced environmental footprint, AROMA-GC-MS offers a scalable and clinically adaptable platform that facilitates the integration of GC-MS–based metabolomics into biomedical research and future diagnostic and prognostic applications.