Case Study: Renowned Biopharmaceutical Company accelerates metabolomics insights with Elucidata’s Polly PeakML

Polly PeakML Accelerates Biological Insight Derivation from Untargeted Metabolomics Analysis

Renowned Biopharmaceutical Company, a leader in therapies for rare genetic diseases, needed a faster and more reliable way to classify untargeted metabolomics data for ML-based analysis. Their challenge was noisy peaks, manual and subjective peak curation, and computationally intensive processing that slowed down efforts to uncover biologically meaningful signals.

Elucidata addressed this with Polly PeakML, its machine-learning-based peak classification solution integrated into the metabolomics workflow. By automatically classifying peak groups as real signal or noise, Elucidata helped the customer achieve ~94% accuracy, 120x faster processing than an expert, and 2.5x more metabolic features identified, while improving correlation in curated data and enabling clearer pathway and biomarker discovery.