Metabolomics with chromatography-mass spectrometry is often challenging and relies on statistical tools to discern changes in a metabolome. A pooled sample strategy was proposed, consisting of (1) identification of potential marker candidates by detecting changes of metabolites in a few pooled samples between treated and control groups and (2) validation of markers of statistically significant changes with a large set of individual samples. This strategy was enabled by applying a thorough background subtraction approach based on high-resolution mass spectrometry. In a proof-of-principle study, plasma samples were generated and pooled in a 6-week investigational study to identify potential toxicological markers for an observed muscle toxicity associated with the treatment of ibipinabant in dogs. With pooled control samples as backgrounds, potential marker candidates were revealed in the background-subtracted profiles of the pooled ibipinabant-treated samples. After further cleaning with the use of mass defect filtering to exclude drug metabolites and the comparison of profiles between pooled treated samples to eliminate inconsistent peaks, the major biomarker candidates in the profiles were identified to be 19 acylcarnitines. A total of 3 of the 19 acylcarnitines were measured on the set of individual samples to allow for statistical analysis. The results confirmed the significance of acylcarnitine elevations in ibipinabant-treated dogs and indicated that the acylcarnitines could be early markers for the dog-specific toxicity. The advantages of the pooled sample strategy and its potential limitations for metabolomics are discussed.