San Diego — ASMS 2026 — June 1st, 2026 — Evosep announces the launch of Evosep Proteomics, an ecosystem designed to standardize and scale liquid chromatography–mass spectrometry (LC-MS)–based proteomics for research and pharmaceutical drug development. Success is materialized through ease of use and simplicity of comprehensive, standardized workflow solutions meeting today’s analytical requirements.
The platform combines Evokit sample preparation kits, the Evosep Lupo Sample Preparation System, and Evosep Eno into a unified sample-to-separation workflow aimed at improving reproducibility, scalability, and data consistency across proteomics studies. Building on its focus on standardized LC separation, Evosep is extending upstream into sample preparation to reduce variability and enable more interoperable, AI-ready proteomics data.
Proteomics is increasingly applied at scale, but fragmented workflows and manual variability continue to limit reproducibility and confidence in downstream analysis, particularly in pharmaceutical R&D and multi-site studies. Evosep Proteomics is intended to address these challenges by delivering standardized, low-variance proteomics output suitable for large datasets and advanced analytics.
“To fully realize AI-driven drug development, LC-MS-based proteomics must become standardized. Our users have been asking for scalable proteomics, not only as a reliable analytical tool, but as an AI-ready data foundation for the next generation of drug discovery and development,” said Morten Bern, CEO of Evosep.
Evosep Proteomics addresses this need by delivering consistent proteomic output at scale, creating a robust data foundation that enables reliable AI deployment, faster insight generation, and more confident decision-making across pharmaceutical R&D such as:
- De-risk drug development pipelines: Standardized, low-variance proteomics data that is comparable across studies and sites, supporting faster target discovery, biomarker identification, and AI-driven decisions with greater confidence.
- Accelerate New Approach Methodologies (NAMs): Reproducible proteomics readouts that strengthen non-animal, mechanism-based safety and efficacy assessments, enabling earlier candidate de-risking and improved translational reliability.
- Enable Minimal Residual Disease (MRD) applications: Consistent sample-to-separation workflows that support detection of subtle protein signatures over time, improving longitudinal monitoring and treatment response assessment in translational and clinical studies.
In both preclinical and clinical research, teams face increasing pressure to make faster, more confident decisions, yet critical biological insights often remain obscured by workflow variability and inconsistent data. LC-MS-based proteomics can reveal this hidden biology, enabling biomarker discovery and patient stratification, but only when data is reliable and comparable across studies, instruments, operators, and sites.
A key bottleneck in proteomics lies upstream. Despite advances in mass spectrometry, variability in sample preparation continues to limit data quality, comparability, and scalability, reducing confidence in downstream decisions and AI applications. Evosep Proteomics addresses this by standardizing pre-analytical workflows:
- Evosep Lupo: A dedicated platform that minimizes manual steps, reduces variability, and eliminates protocol drift, ensuring consistent sample inputs.
- Evokit sample preparation kits: Standardized kits with traceability and reproducible performance, delivering consistent MS-ready samples on Evotips.
- Workflow integration: Seamless integration with Evosep One and Evosep Eno systems enables scalable, reliable proteomics for multi-site pharmaceutical environments.
At launch, Evosep Proteomics includes Evokit Digest and Evokit QC kits, with built-in quality controls and consumable tracking to support long-term and regulated studies. With Evosep Proteomics, Evosep delivers scalable, unbiased proteomics at a target cost of approximately $10 per sample, making high-quality, reproducible proteomics accessible for routine use in research, biomarker discovery, and large-scale drug development.
