Innovation in mass spectrometry does not happen in isolation. Some of the most impactful scientific advances emerge from highly specialized research communities – proteomics experts developing new peptide identification workflows, metabolomics researchers curating spectral databases, toxicologists building compound libraries, and biopharma scientists creating novel characterization methods.

Unlike traditional monoclonal antibodies, ADCs combine an antibody backbone with linker chemistry and a cytotoxic payload. This multi-component architecture introduces overlapping layers of heterogeneity, including drug-to-antibody ratio (DAR) distributions, charge variants, post-translational modifications, and structural changes at both the intact and subunit levels. Across ADC development, these characteristics are considered critical quality attributes that must be characterized, understood, and monitored.

For years, metabolomics researchers have faced a frustrating reality: modern high-resolution mass spectrometers can detect tens of thousands of molecular features, yet only a fraction can be confidently identified. The challenge is no longer finding molecules. It is generating the high-quality MS/MS data needed to confidently assign structures and extract meaningful biological insights.