Bioptimus Launches STELA: World's Largest Spatial Biology Atlas to Power AI-Driven Precision Medicine
核心洞察
Bioptimus (搜索) announced the launch of STELA, the world's largest clinically linked spatial biology atlas, aiming to profile up to 100,000 patient specimens across three continents.
The initiative represents a 20-fold increase in scale over existing spatial biology atlases and will serve as the data backbone for M-Optimus, the first multimodal world model of biology.
Strategic partnerships with 10x Genomics (搜索) and Broad Clinical Labs (搜索) will leverage the Xenium spatial transcriptomics platform and high-throughput laboratory capabilities to generate standardized, AI-ready datasets.
Bioptimus (搜索), a global AI biotech company, announced the launch of its Spatial Tissue Embedding Learning Atlas (STELA), a multinational initiative that aims to create the world's largest clinically linked spatial biology atlas. The project, anchored by strategic partnerships with 10x Genomics (搜索) and Broad Clinical Labs (搜索), represents a significant leap forward in biological AI infrastructure, targeting the profiling of up to 100,000 patient specimens across three continents.
Unprecedented Scale and Scope
STELA represents a 20-fold increase in scale over existing spatial biology atlases available today. The initiative will integrate high-resolution spatial transcriptomics, matched histopathology imaging, multi-omics data including genomics, transcriptomics and proteomics, alongside longitudinal clinical records. Starting with oncology (搜索) and immunology (搜索) tissue samples, the atlas will span the United States, Europe, and Asia.
"Today, most patients' diagnostic data is used to inform decisions for only that individual. We envision a world where every patient can contribute insights to better inform the care and treatment outcomes of future patients," said Jean Philippe Vert, PhD, Co-Founder and CEO of Bioptimus (搜索). "STELA is the fuel to power M-Optimus, allowing us to map the intricate interactions between cells and tissues, across indications, at unprecedented scales, unlocking a new era of precision medicine."
Strategic Technology Partnerships
The collaboration with 10x Genomics (搜索) centers on leveraging the Xenium spatial transcriptomics platform as the foundational technology for the launch. This partnership aims to establish new benchmarks for reproducible, AI-ready data generation across leading research institutions worldwide.
"Many of the most important questions in medicine come down to understanding how cells interact within complex human tissues," said Serge Saxonov, Chief Executive Officer and Co-founder of 10x Genomics (搜索). "By enabling spatial profiling at unprecedented scale, STELA will generate foundational datasets that allow researchers to connect the underlying biology with disease outcomes, unlocking new insights that can accelerate and improve therapeutic discovery and development."
Industrial-Scale Data Generation
Bioptimus (搜索) has established a multi-year agreement with Broad Clinical Laboratories (搜索) to support STELA through large-scale spatial biology data generation. This partnership leverages Broad's high-throughput spatial biology capabilities to process biological samples at scale, creating a massive repository of high-resolution spatial transcriptomics data.
The collaboration extends beyond data production, with both organizations co-developing next-generation, AI-driven quality control metrics and predictive tools designed to optimize assay performance and automate biological insights.
"To unlock the true clinical potential of spatial biology, we must pair massive-scale data generation with uncompromising data quality," said Niall Lennon, Chief Scientific Officer of Broad Clinical Labs (搜索). "By combining our high-throughput laboratory workflows with Bioptimus (搜索)'s advanced AI, we are co-developing next-generation quality control metrics that ensure the highest data integrity."
Powering the World Model of Biology
STELA will serve as the data backbone for M-Optimus, described as the first multimodal and multiscale world model of biology. This AI system aims to map how molecular and cellular interactions drive disease in fields like oncology (搜索) and inflammation (搜索), ultimately enabling researchers to anticipate patient responses to novel therapies, accelerate drug development, and design more effective immunotherapies.
The initiative addresses a critical gap in biological AI development. While foundation models for language have thrived on vast digital datasets, biology has long lacked the standardized, high-quality data scale required for similar breakthroughs, particularly for clinical data.
Global Collaboration Framework
Participating hospitals and research institutions will contribute samples under standardized protocols and receive access to rich spatial characterization and foundation model capabilities in return. This collaborative approach empowers clinicians to transform raw data into actionable insights through more precise diagnostic and therapeutic strategies.
By aligning data generation protocols, data processing and storage, and AI model development within a unified framework at a global scale, STELA establishes foundational infrastructure for the next era of biological AI. The initiative is designed to integrate additional spatial and molecular profiling technologies over time, expanding its capabilities beyond the initial Xenium platform implementation.
Bioptimus (搜索)'s existing AI models are already in use by 16 of the top 20 pharmaceutical companies, with their H-Optimus foundation model for human histology achieving over 1 million downloads and widespread adoption across research, drug discovery, and clinical pipelines.