Thermo Fisher Scientific, a global leader in scientific services, today announced a strategic partnership with Precision Health Research Singapore (PRECISE) to advance the PRECISE-SG100K study, one of the most ambitious and diverse population-scale biobank initiatives in the region. The partnership reflects increased investment from national population studies aimed at leveraging proteomics to drive insights into real-time disease biology and apply it to early detection, prevention, and personalized care.
As biobanks become central to national health strategies over the next decade, the integration of multi-omics platforms and AI-powered analytics will be critical. Applying AI to high-quality proteomics and clinical data can identify complex biological patterns, improve patient stratification, and accelerate the path from discovery to translational insights.
Population-scale proteomics represents one of the most powerful opportunities to understand disease in real time across the health continuum. By combining our deep scientific expertise with industry-leading technology, we help the nation’s health leaders transform complex biological data into insights that can fundamentally transform human health. ”
Mark N. Casper, Chairman and Chief Executive Officer, Thermo Fisher Scientific
Under the PRECISE-SG100K program, Thermo Fisher will deploy an integrated proteomics strategy that combines the Olink® Proximity Extension Assay (PEA) platform with a high-resolution Orbitrap Astral mass spectrometry system. These technologies, combined with Seer’s Proteograph® product suite, enable scalable and sensitive targeted protein measurements through deep and unbiased discovery proteomics, creating a powerful framework for translating large-scale biological data into meaningful new disease mechanism and biomarker insights.
The PRECISE-SG100K study integrates complementary proteomics technologies in parallel across a large longitudinal population cohort, an approach that enhances reproducibility, supports regulatory-grade evidence generation, and improves long-term translational value. This model reflects the growing recognition of proteomics not only as a discovery tool but also as a fundamental research infrastructure for precision medicine.
“The national biobank effort requires technology that delivers both breadth and precision,” said Dr. Karen Nelson, chief scientific officer at Thermo Fisher. “By integrating our differentiated technologies, we will enable the identification of reliable biomarkers and accelerate the path to translational applications. This complementary strategy will establish a new standard in multiproteomic analysis, allowing researchers to observe true disease biology quickly and at scale.”
Comparing data from Thermo Fisher’s complementary platforms with growing public proteomics datasets from other global population-scale studies gives biobank researchers greater ability to accelerate discovery, validation, and translation around the world.
Thermo Fisher brings extensive experience supporting biobank infrastructure development and large-scale proteomics and genomics efforts globally. The company is currently participating in some of the largest biobank initiatives to date, including the UK Biobank Pharma Proteomics Project, FinnGen in Finland, and Geisinger’s MyCode Community Health Initiative in the US. Collectively, these programs involve the analysis of over 1 million samples.
Dr. John Chambers, Chief Scientific Officer of PRECISE and Principal PI of the PRECISE-SG100K study, said, “Applying this integrated proteomics approach to the entire national cohort provides a dynamic view of disease biology within Singapore’s unique and diverse population.” “This model strengthens our ability to discover early molecular signals of disease, understand risk across diverse global communities, and generate insights that can inform the future of population health.”
This research is supported by Seer, Inc. as a research collaboration partner and Novogene, which provides laboratory services to support sample processing and data generation.
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Thermo Fisher Scientific Co., Ltd.
