Realize any project
you can imagine
Olink Explore HT is designed for outstanding performance at any scale of protein biomarker discovery, from tens to millions of samples. This scalability is enabled by a streamlined, automated workflow and a comprehensive software suite, all optimized for high-throughput data acquisition.
generation
with 1 instrumentation line
with 2 instrumentation lines
Revealing the truth of human disease.
Protein by protein.
Olink’s trusted proteomics solutions are helping to bridge the gap between genomics and human diseases. Population-scale studies are increasingly being used to provide comprehensive views of protein expression patterns across the diversity of human biology. Olink technology has been applied to one of the world’s largest proteomic health studies, revealing biomarkers that can predict cancer more than a decade before diagnosis.
The largest collection of next-generation proteomic data
Olink Explore enables the pioneering UK Biobank Pharma Proteomics Project. This ongoing population-scale project, backed by a pharma consortium, applied the Olink Explore platform for proteomic analysis of over 50,000 participants. To date, over 10,000 genetic associations for 1,463 proteins have been released, with more to come.
The protein data is freely available on the Olink Insight platform.
Amplify discovery.
Advance genomics.
When you combine proteomic data with genomic datasets, your statistical significance skyrockets. Olink data is designed for maximum transparency and comparability – whether you’re investigating novel drug targets or digging deeper into existing sample collections to repurpose on-market therapies.
The key to finding proteins that cause disease
Olink’s next-generation proteomics platform, renowned for its unparalleled specificity and comprehensive coverage, is the definitive choice for identifying protein Quantitative Trait Loci (pQTLs).
Learn how pQTL analysis with Olink proteomics data is revealing novel drug targets and new insights into disease pathways in the white paper, “Empower Genomics with Proteomics”.