The article presents a comprehensive characterization of the human serum metabolome, aiming to establish a centralized reference resource for metabolite analysis in clinically important biofluids. The study combines targeted and non-targeted NMR, GC-MS, and LC-MS methods with literature mining to identify and quantify a wide range of metabolites commonly detected in human serum. The resulting Serum Metabolome Database (SMDB) contains 4229 confirmed and probable serum compounds, their concentrations, and links to disease associations. The database is freely available online and serves as a valuable resource for future research in metabolomics and blood chemistry. The study highlights the importance of considering the variability in metabolite concentrations due to factors such as age, gender, and health status, and provides a baseline for understanding the serum metabolome under normal and pathological conditions. The results also demonstrate the complementary nature of different analytical techniques, such as NMR and GC-MS, in identifying and quantifying metabolites in serum.The article presents a comprehensive characterization of the human serum metabolome, aiming to establish a centralized reference resource for metabolite analysis in clinically important biofluids. The study combines targeted and non-targeted NMR, GC-MS, and LC-MS methods with literature mining to identify and quantify a wide range of metabolites commonly detected in human serum. The resulting Serum Metabolome Database (SMDB) contains 4229 confirmed and probable serum compounds, their concentrations, and links to disease associations. The database is freely available online and serves as a valuable resource for future research in metabolomics and blood chemistry. The study highlights the importance of considering the variability in metabolite concentrations due to factors such as age, gender, and health status, and provides a baseline for understanding the serum metabolome under normal and pathological conditions. The results also demonstrate the complementary nature of different analytical techniques, such as NMR and GC-MS, in identifying and quantifying metabolites in serum.