Thermo Fisher Scientific Inc., the world leader in serving science, today announced a strategic collaboration with Precision Health Research, Singapore (PRECISE) to advance the PRECISE-SG100K study, one of the region’s most ambitious and diverse population-scale biobank initiatives. The collaboration reflects growing investments from national population studies looking to harness proteomics to drive insight into real-time disease biology for application in earlier detection, prevention and personalized care.
As biobanks become central to national health strategies over the next decade, the integration of multi-omic platforms and AI-driven analytics is critical. When applied to high-quality proteomic and clinical data, AI can identify complex biological patterns, improve patient stratification and accelerate the path from discovery to translational insight.
Proteomics at population scale represents one of the most powerful opportunities to understand disease in real time across the full continuum of health. By combining our deep scientific expertise with industry-leading technologies, we are helping national health leaders translate complex biological data into insights that can fundamentally transform human health.”
Marc N. Casper, Chairman and Chief Executive Officer, Thermo Fisher Scientific Inc.
Under the PRECISE-SG100K program, Thermo Fisher will deploy an integrated proteomics strategy combining its Olink® Proximity Extension Assay (PEA) platforms with the high-resolution Orbitrap Astral mass spectrometry system. Together, these technologies, along with Seer’s Proteograph® Product Suite, deliver scalable, high-sensitivity, targeted protein measurement with deep, unbiased discovery proteomics, creating a powerful framework for translating large-scale biological data into meaningful novel disease mechanism and biomarker insights.
The PRECISE-SG100K study integrates complementary proteomic technologies in parallel across a large, longitudinal population cohort, an approach that strengthens reproducibility, supports regulatory-grade evidence generation and enhances the long-term translational value. This model reflects the growing recognition of proteomics not only as a discovery tool, but as foundational research infrastructure for precision medicine.
“National biobank initiatives require technologies that deliver both breadth and precision,” said Karen Nelson, Ph.D., chief scientific officer at Thermo Fisher. “By integrating our differentiated technologies, we are enabling high-confidence biomarker identification and accelerating the path to translational application. This complementary strategy sets a new standard for multi-proteomics analysis and empowers researchers to see true disease biology with speed and at scale.”
Comparing data from Thermo Fisher’s complementary platforms with expanding public proteomic datasets from other global population-scale studies provides biobank researchers with exceptional capacity for discovery, validation and accelerated translation worldwide.
Thermo Fisher brings extensive experience supporting biobank infrastructure development and large-scale proteomics and genomics initiatives globally. The company is currently involved in some of the largest biobank efforts to date, including the UK Biobank Pharma Proteomics Project, FinnGen in Finland, and the Geisinger's MyCode Community Health Initiative in the United States. Collectively, these programs encompass analyzes of more than one million samples.
“By applying this integrated proteomics approach across our national cohort, we gain a dynamic view of disease biology within Singapore’s uniquely diverse population,” said John Chambers, Ph.D., chief scientific officer at PRECISE and lead PI of PRECISE-SG100K study. “This model strengthens our ability to uncover early molecular signals of disease, understand risk across different global communities and generate insights that can inform the future of population health.”
The study is supported by Seer, Inc., as a research collaboration partner and by Novogene, which provides laboratory services in support of sample processing and data generation.