ViewsML, a Vancouver-based startup focused on AI-driven pathology analysis, has secured $4.9 million CAD in seed funding to advance its virtual biomarker staining platform. The round was led by Wittington Ventures, with strategic participation from Mayo Clinic and Continuum Health Ventures, alongside existing investors RiSC Capital, Debiopharm, WUTIF Capital, Defined, and eFund. The funding will support the company’s efforts to commercialize its technology, which uses artificial intelligence to derive biomarker insights from standard hematoxylin and eosin (H&E) stained pathology slides without requiring traditional laboratory staining processes.
The company describes its platform as building “the computational layer for next-generation diagnostics,” aiming to replace time-consuming and resource-intensive immunohistochemistry (IHC) workflows. By analyzing routine pathology images, ViewsML’s AI models generate per-cell spatial and quantitative biomarker data in minutes, eliminating the demand for chemical staining that can take days or weeks and often consumes limited tissue samples. This approach preserves precious biopsy material while accelerating insights for drug development and diagnostic applications.
ViewsML’s technology centers on creating what it calls the world’s first virtual biomarker library—a database of AI-generated biomarker profiles derived directly from H&E slides. According to the company, this library enables scalable computation for assay development, shifting IHC from a manual lab procedure to a high-resolution computational process. The platform is designed for use across translational research, clinical trials, diagnostics, and emerging fields such as neurodegenerative disease research, where tissue samples are often scarce and valuable.
Strategic partnerships are central to ViewsML’s path to clinical validation. The company highlighted its collaboration with Mayo Clinic as a key factor in advancing real-world testing of its platform. Wittington Ventures, which is backed by the holding company for Loblaw and Shoppers Drug Mart, led the seed round and emphasized the importance of moving biomarker analysis into software-driven workflows. Zeeshan Ali, a partner at Wittington Ventures, stated in a press release that biomarker detection remains constrained by legacy methods despite its foundational role in precision medicine.
The funding will be used to accelerate commercialization, expand engineering and scientific teams, and advance clinical validation efforts. ViewsML plans to publicly showcase its technology at the American Association for Cancer Research (AACR) Annual Meeting in April 2026, where it aims to demonstrate how virtual staining can speed up biomarker analysis while reducing costs and preserving sample integrity. Kenneth To, CEO of ViewsML, said the platform empowers scientists and clinicians to analyze biomarker expression in minutes rather than the traditional days or weeks required by conventional IHC.
ViewsML’s approach addresses a longstanding bottleneck in pathology workflows. Traditional IHC requires multiple steps including tissue sectioning, antibody staining, washing, and visualization—processes that are not only time-consuming but also variable in reproducibility and destructive to samples. By contrast, the company’s AI-driven method analyzes existing digital pathology slides, extracting biomarker information without additional lab procedures. This could significantly improve efficiency in pharmaceutical research, where biomarker profiling is critical for patient stratification in clinical trials and companion diagnostic development.
The company’s technology relies on training deep learning models on large datasets of paired H&E and IHC slides to learn the visual correlates of biomarker expression. Once trained, the models can infer biomarker presence and distribution from H&E images alone. ViewsML emphasizes that its platform provides both spatial context—showing where biomarkers are expressed within tissue architecture—and quantitative measurements, enabling deeper analysis than some existing digital pathology tools that focus only on overall positivity scores.
Investors spot potential for ViewsML’s platform to democratize access to advanced biomarker analysis, particularly in settings where specialized staining expertise or laboratory infrastructure is limited. By reducing reliance on physical reagents and manual labor, the technology could lower barriers to entry for biomarker testing in community hospitals and research labs worldwide. Continuum Health Ventures, one of the novel backers in the seed round, cited the platform’s potential to support faster, more scalable paths to precision medicine as a key rationale for its investment.
As ViewsML moves toward commercialization, it will need to navigate regulatory pathways for AI-based diagnostic tools. While the company positions its platform primarily for research use initially, long-term goals may include seeking clearance for clinical diagnostic applications. The partnership with Mayo Clinic suggests an early focus on validating the technology in real-world clinical settings, which will be essential for building trust among pathologists and oncologists who rely on biomarker data for treatment decisions.
The $4.9 million CAD seed round reflects continued investor interest in AI applications that address inefficiencies in healthcare workflows, particularly in oncology and pathology. ViewsML joins a growing ecosystem of startups using computational methods to enhance or replace traditional laboratory techniques, from digital slide analysis to predictive modeling of treatment response. Its focus on virtualizing IHC—a cornerstone of pathologic diagnosis—places it at the intersection of medical imaging, artificial intelligence, and precision medicine.
With the funding closed, ViewsML’s immediate priorities include scaling its AI models, expanding its virtual biomarker library, and preparing for its debut at the AACR Annual Meeting. The event, scheduled for April 2026, will provide a high-visibility opportunity to demonstrate the platform’s capabilities to researchers, clinicians, and industry stakeholders. Success in clinical validation studies will be critical to determining whether the technology can transition from a research tool to a routine component of diagnostic workflows.
For now, ViewsML’s advancement represents a step toward reimagining how biomarker data is generated—not through wet lab processes, but through software that learns to see what stains reveal. If successful, the approach could reshape aspects of pathology practice by making biomarker analysis faster, less costly, and more sustainable, all while preserving the integrity of precious tissue samples for future use.