Our solutions deliver the analytical specificity, sensitivity, and dynamic range you need for the analysis of complex biological samples such as plasma, serum, whole blood, urine, cerebrospinal fluid (CSF), and oral fluid. Our solutions help you cover research in protein biomarker discovery and validation, cancer research, endocrine research, therapeutic drug monitoring research, Alzheimer's, and more.
Our dedicated clinical research scientists collaborate with scientists like you every day to develop key clinical research workflows that help you advance your research. We are continually compiling comprehensive workflows with details from sample prep to data analysis along with the associated resources.
Streamline small molecule unknown identification and find real differences between samples with the NEW LC-MS software for Orbitrap mass spectrometers.
Protein analysis product categories
Discover protein biomarkers that matter using workflows for both unbiased discovery-based (untargeted) and targeted determination of changes in protein abundance.
Streamline your workflows with a variety of sophisticated separation solutions to improve your application and workflow performance.
Solutions you can trust to meet the challenges of clinical research and help you translate your research to future relevant clinical applications
Software solutions designed to solve workflow and analysis specific challenges in the clinical research laboratory
All samples require some form of preparation prior to study or analysis. We offer a variety of solutions to solve your most complex challenges.
The bridge between our technology and your clinical research application need
Dr. Sucharita Dutta, Eastern Virginia Medical School, describes how LC-HRAM Orbitrap instrument technology is changing the translational and personalized medicine research landscape.
Anne Incamps, Project Manager Mass Spectrometry Biomarkers Clinical Diagnostics, discusses how she is using Orbitrap and triple-quad technology to discover and quantify potential biomarkers in disease models.