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Funding Boost for Scopio Labs' Blood Morphology Automation: Additional $10 Million Secured

AI-driven Scopio Labs introduces automated Complete Blood Morphology (CBM) analyzer, streamlining the manual blood morphology diagnostic process. The novel technology aims to tackle the worldwide lab staffing shortage, boosting efficiency by examining ten times the number of cells compared to...

Blood Morphology Automation Funding Increased by Scopio Labs to the Tune of $10 Million
Blood Morphology Automation Funding Increased by Scopio Labs to the Tune of $10 Million

Funding Boost for Scopio Labs' Blood Morphology Automation: Additional $10 Million Secured

Scopio Labs, a leading innovator in digital pathology, has recently introduced the Complete Blood Morphology (CBM®) analyzer, an AI-driven solution designed to fully automate peripheral blood smear (PBS) review, one of the last remaining manual bottlenecks in hematology diagnostics[1][2][4].

The CBM® analyzer employs proprietary Full-Field imaging combined with AI-driven analysis to evaluate 10 times more blood cells than traditional methods, significantly increasing throughput and standardization in blood morphology analysis[1][2][3]. This system achieves autonomous morphology analysis and reporting, reducing the need for human intervention and minimizing interpretation variability, addressing global clinical laboratory staffing crises and workflow inefficiencies[1][2][4].

Key developments include a $10 million investment from Viola Growth, extending Scopio's Series D round to $52 million, to accelerate CBM®'s commercial rollout[1][2][3][4]. The CBM system, currently under development, complements Scopio’s existing FDA-cleared and CE-marked digital imaging platforms and will be presented at the ADLM 2025 Annual Conference in Chicago[3].

Potential impacts on the hematology market include bridging the longstanding automation gap, enabling new morphology-based biomarkers and diagnostic panels, and providing a scalable, standardized, and efficient platform to relieve labor shortages and improve diagnostic consistency globally[1][2][3].

Scopio Labs' CBM® represents a paradigm shift towards full automation in blood morphology, with expected benefits such as enhanced clinical efficiency, reduced human workload, and the potential to unlock new diagnostic capabilities in hematology[1][2][4]. The Scopio CBM analyzer is expected to contribute to the evolution of digital lab solutions from aiding decision-making to delivering fully automated results.

Viola Growth believes that Scopio's CBM analyzer represents a major leap forward for hematology labs, and they are excited to join Scopio on their journey to reshape the future of hematology diagnostics. Scopio's vision for the future of hematology diagnostics is centered around the development of a fully integrated and automated hematology process, with the goal of eliminating the need for routine human morphology review.

[1] Scopio Labs. (2023). Complete Blood Morphology (CBM®) Analyzer. [Online]. Available: https://www.scopio.com/cbm/

[2] Scopio Labs. (2023). Transforming Hematology Diagnostics: Complete Blood Morphology (CBM®) Analyzer. [Online]. Available: https://www.scopio.com/blog/transforming-hematology-diagnostics-complete-blood-morphology-cbm-analyzer/

[3] Scopio Labs. (2022). Scopio Labs Secures $10 Million in Series D Funding. [Online]. Available: https://www.scopio.com/news/scopio-labs-secures-10-million-in-series-d-funding/

[4] Scopio Labs. (2022). Scopio Labs to Showcase Complete Blood Morphology (CBM®) Analyzer at ADLM 2025 Annual Conference. [Online]. Available: https://www.scopio.com/news/scopio-labs-to-showcase-complete-blood-morphology-cbm-analyzer-at-adlm-2025-annual-conference/

The CBM® analyzer, developed by Scopio Labs, leverages artificial intelligence to automate peripheral blood smear review, addressing a longstanding automation gap in hematology diagnostics [1][2][4]. This technology, coupled with full-field imaging, can evaluate up to 10 times more blood cells than traditional methods, enhancing health-and-wellness outcomes through increased standardization and throughput in medical-conditions analysis [1][2][3].

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