Antibody-drug conjugates (ADCs) are among the most promising—and analytically demanding—modalities in biopharma today. By combining large, heterogeneous antibodies with chemically labile payloads and linkers, ADCs introduce a level of structural complexity that challenges conventional analytical workflows. It also poses the challenge that the very features you need to measure are often the easiest to lose during analysis.
Imagine having a tech expert at your fingertips to solve computer issues or a fitness trainer guiding you through workouts from the comfort of your home. In today’s fast-paced world, the ability to provide and receive service and support remotely is no longer a luxury but a necessity. Whether it’s troubleshooting a software issue, repairing a device, offering customer assistance, or enjoying the convenience of telehealth as a private individual, remote capabilities have revolutionized how businesses operate and how individuals get help
Unplanned downtime is a formidable adversary that businesses across various industries strive to minimize. Defined as the unexpected interruption of regular operations, unplanned downtime can wreak havoc on productivity, profitability and customer satisfaction. In this article, we delve into the causes of unplanned downtime, its far-reaching consequences and strategies to mitigate its impact.
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.
Antibody-drug conjugates (ADCs) have emerged as one of the fastest-growing classes of biotherapeutics, combining the targeting specificity of monoclonal antibodies with the potency of cytotoxic payloads. However, this unique architecture also introduces significant analytical complexity. From drug-to-antibody ratio (DAR) distributions and charge variants to conjugation sites and structural modifications, ADCs present multiple, interconnected sources of heterogeneity that must be understood to ensure product quality and performance.
In a recent webinar, Ming Gao, Ph.D., Senior Research Chemist at Mérieux NutriSciences, explored the growing challenge of cereulide contamination in food products and the analytical strategies needed to detect this heat-stable toxin at trace levels. The session examined how LC-MS/MS can help laboratories overcome the limitations of traditional microbiological screening and meet emerging regulatory requirements.
In this interview, Andy Wilcox, Senior Market Development Manager, Aftermarket and Software, speaks with Susanna Baqué, Senior Director of Global Customer Experience, about how SCIEX Now gives customers one connected digital workspace to manage instruments, reduce time spent searching for information, resolve issues faster and keep their laboratory running more efficiently and with greater confidence.
As therapeutic pipelines continue to diversify, bioanalysis is being asked to do more than ever before. From small molecules to complex biologics, today’s scientists must generate high‑quality, reliable data across a growing range of molecule types and workflows, often under increasing time pressure.