BOSTON, MA – January 13, 2026 — TetraScience, a leader in scientific data integration and analytics, has entered into a strategic collaboration with Thermo Fisher Scientific (NYSE: TMO) to accelerate scientific data unification and artificial intelligence (AI) enablement across laboratory environments worldwide. The partnership aims to help researchers unlock deeper insights faster, improve reproducibility, and reduce time-to-discovery through enhanced data interoperability, cloud-native infrastructure, and AI-driven analytics. (Source: TetraScience)
This collaboration marks a significant milestone for both companies, reinforcing TetraScience’s mission to empower science through data and signaling Thermo Fisher’s continued focus on enabling digital transformation across life sciences, biotech, pharmaceuticals, and academic research.
Transforming Laboratory Data with TetraScience and Thermo Fisher
Scientific research has evolved rapidly in recent years, driven by high-throughput experimentation, multi-omics analysis, automation and AI-enabled workflows. However, one of the biggest challenges remains the fragmentation of laboratory data — locked inside disparate instruments, systems, and formats — making it difficult to unify and leverage meaningfully. Recognizing this gap, TetraScience and Thermo Fisher Scientific are combining forces to accelerate scientific data and AI enablement across research organizations of all sizes.
The collaborative effort focuses on two key fronts:
- Seamless Data Integration Across Lab Systems: TetraScience’s platform will connect with Thermo Fisher’s ecosystem of instruments and software, enabling researchers to automatically ingest, normalize, and harmonize data regardless of origin or format.
- AI-Ready Scientific Data Infrastructure: By organizing laboratory data into standardized, cloud-native formats, AI and machine learning (ML) models can be applied reliably — allowing deeper insights into experiments, predictive analytics, anomaly detection and optimized workflows.
As scientific research becomes ever more data-intensive, the ability to unify and operationalize data is critical. This partnership enhances TetraScience’s commitment to providing a unified data layer that accelerates discovery and innovation, while aligning with Thermo Fisher’s strategic objective to help customers harness data as a competitive advantage.
What the Collaboration Includes
The TetraScience–Thermo Fisher initiative is designed to address major blockers in laboratory data workflows. Key components of the collaboration include:
Unified Data Connectivity
TetraScience will expand its library of connectors to Thermo Fisher instruments, enabling automatic extraction and normalization of data from diverse sources such as mass spectrometers, chromatography systems, and automated sample handlers. By removing manual data wrangling, scientists can spend more time on hypothesis testing and innovation rather than data preparation.
Cloud-Native Data Platform
The unified data will be stored and managed on a secure, scalable cloud-native infrastructure, allowing real-time access, versioning, and governance. Researchers and data scientists will be able to query, visualize and analyze data across experiments and projects, enhancing reproducibility and collaboration.
AI & Machine Learning Enablement
With a standardized data foundation, advanced AI/ML models can be applied to identify patterns, predict outcomes, and deliver actionable insights. For example, anomaly detection algorithms can identify experimental irregularities faster than traditional methods, and predictive models can suggest optimized experimental parameters.
Enhanced Workflow Automation
The integration will enable trigger-based workflows that automate routine tasks — such as quality control checks, data validation, and reporting — freeing up scientists to focus on higher-value research initiatives.
Why This Partnership Matters
Bridging Data Silos in Scientific Research
One of the most persistent challenges in laboratory environments is fragmented data. Experimental results are often stored across multiple systems — instrument software, LIMS, ELN, legacy databases — making it difficult to consolidate and derive insight. This collaboration leverages TetraScience’s expertise in data harmonization and Thermo Fisher’s broad instrument footprint to knit together previously disconnected data streams into a unified, scalable framework.
Delivering AI-Ready Scientific Data
AI has the potential to revolutionize scientific discovery — but only when data is structured, consistent, and accessible. TetraScience’s cloud-native data layer standardizes scientific data at scale, enabling reliable application of AI and machine learning models. With Thermo Fisher’s ecosystem connected, the combined solution can accelerate discovery cycles and improve research outcomes across disciplines.
Supporting Reproducibility and Collaboration
Reproducibility remains a cornerstone of credible science. By unifying data sources and enabling centralized governance, the partnership helps researchers better compare results, audit processes, and collaborate across teams, departments, and institutions.
Advancing Digital Lab Transformation
The partnership reinforces the broader industry trend toward digital laboratories, where automated data flows, analytics and AI become standard components of experimental workflows. Together, TetraScience and Thermo Fisher are helping labs transition from manual, siloed systems to data-centric operations — improving speed, quality and innovation.
Leadership Perspectives
Rasheed Simons, CEO of TetraScience, highlighted the synergy between both companies:
“Scientific discovery is increasingly driven by the quality and accessibility of data. Our collaboration with Thermo Fisher reflects a shared commitment to breaking down data silos and enabling researchers with AI-ready data infrastructure. By combining TetraScience’s unified data layer with Thermo Fisher’s world-class scientific ecosystem, we are empowering labs to accelerate innovation like never before.”
A senior executive from Thermo Fisher Scientific commented:
“Thermo Fisher is focused on enabling digital transformation across scientific research. Partnering with TetraScience allows us to deepen our support for customers by providing a scalable, cloud-native data foundation that drives reproducibility, collaboration and AI-powered insights.”
Impacts Across Industries
Life Sciences
In drug discovery and development, unified data accelerates target identification, lead optimization and preclinical research by enabling cross-study comparisons and data-driven decision making.
Healthcare & Diagnostics
Clinical research and diagnostics laboratories will benefit from centralized data streams and analytics that enhance workflow efficiency, reduce errors, and support compliance with regulatory standards.
Environmental & Material Sciences
Research organizations focusing on materials, chemicals, and environmental sciences can apply AI models to large datasets, revealing insights that traditional analysis might overlook.
Academia & Research Institutions
Universities and research institutes will gain from standardized data frameworks that support collaborative research, shared resources, and reproducible experiments across laboratories and research groups.
Building a Future-Ready Scientific Data Ecosystem
The strategic collaboration between TetraScience and Thermo Fisher Scientific comes at a pivotal moment in data-driven research. As laboratories worldwide scale up data generation — from high-throughput screening to real-time monitoring — the need for unified, AI-ready data infrastructure has never been more apparent.
By enabling seamless data integration, cloud management and advanced analytics, TetraScience and Thermo Fisher are helping to shape the future of digital science — one where researchers can focus less on data logistics and more on accelerating discoveries that improve lives.
What to Expect Next
Over the coming months, the TetraScience and Thermo Fisher teams plan to:
- Expand the catalog of instrument connectors to support more Thermo Fisher systems.
- Launch joint developer tools and documentation to help labs integrate their data pipelines.
- Host co-branded webinars and workshops focused on AI-driven scientific data analytics.
- Deliver early customer use cases demonstrating improved reproducibility and accelerated insights.
The collaboration will be rolled out in phases, with initial focus on high-impact use cases in life sciences and biotechnology, followed by expansion into adjacent research domains.
About TetraScience
TetraScience is a scientific data company committed to breaking down barriers between laboratory systems and advancing research through data unification and AI enablement. TetraScience’s platform ingests, harmonizes, and standardizes data from heterogeneous sources — enabling scalable analytics, reproducibility, AI/ML model application and cross-enterprise collaboration. With a global customer base spanning biotech, pharma, materials science and academic research, TetraScience helps scientific organizations accelerate discovery and deliver innovation at scale.
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