SpotitEarly Knowledge Center

At the 2026 ASCO Annual Meeting, two of the largest multi-cancer early detection studies, PATHFINDER 2 and NHS-Galleri, reported their results. This article explains what they showed about detecting more cancers earlier and more safely, why one trial missed its primary endpoint, and what the findings mean for the future of cancer screening, including SpotitEarly's breath-based approach.

SpotitEarly plans to scale its technology to meet a growing global user base through the modular design of its LUCID platform. The approach combines automation, standardized VOC analysis, and patient-friendly sample collection. With adaptability for diverse environments and a focus on accessibility, SpotitEarly ensures consistent quality, efficiency, and reach in expanding cancer detection worldwide.

Cancer screening today is effective but limited, with most cancers lacking recommended tests. This article compares traditional methods like mammography and colonoscopy with new liquid biopsy approaches and introduces SpotitEarly’s breath-based test. By detecting volatile organic compounds (VOCs) through a bio-hybrid platform that combines canine olfaction with AI, SpotitEarly is advancing a non-invasive, accurate solution that complements current screening and expands early

SpotitEarly’s canine partners are at the heart of its early cancer detection platform. This article explores how the dogs are selected, trained, and cared for, and the science behind their extraordinary ability to detect cancer through scent. Learn about their daily work alongside handlers, the role they play in the hybrid canine-AI detection process, and how their skills contribute to making cancer screening accurate, non-invasive, and accessible.

Breath analysis is transforming the landscape of early cancer detection. By identifying volatile organic compounds (VOCs) in exhaled air, this non-invasive method can reveal disease indicators long before symptoms appear. This article explains the science behind breath-based biomarkers, how SpotitEarly integrates them with canine scent detection and AI, and why this approach offers accuracy, comfort, and scalability for global screening.

The recent Rainbow clinical study, published in Nature Scientific Reports, showcases SpotitEarly’s extraordinary success. It shows SpotitEarly is able to detect cancer at early stages with sensitivity rates exceeding 90% for multiple cancers, including those with no standard screening options available today. This breakthrough positions SpotitEarly as a world leader in early disease detection technology.

Artificial intelligence is at the core of SpotitEarly’s bio-hybrid AI platform, refining and validating results from canine scent detection to ensure accuracy and scalability. This article explores how AI models process complex data, integrate it with clinical workflows, and evolve it over time. By combining canine’s abilities with cutting-edge machine learning, SpotitEarly aims to make early cancer screening more precise, accessible, and widely adopted.

Dogs possess an extraordinary sense of smell — capable of detecting volatile organic compounds linked to cancer at concentrations humans cannot perceive. This article will explain the biology of canine olfaction, the research behind scent-based cancer detection, and how SpotitEarly plans to train dogs as part of a hybrid platform with AI to make early, non-invasive cancer screening possible on a global scale.

SpotitEarly is developing a revolutionary approach to early cancer detection, combining the natural scent detection abilities of trained dogs with advanced AI analysis. This article introduces the company’s mission, technology, and vision for a future where non-invasive, accurate, and accessible screening is available worldwide. Learn how this hybrid platform aims to make early detection more effective and widely adopted.

At SpotitEarly, we are transforming the way cancer screening works, making it more accessible, accurate and user-friendly. Our innovative breath test is designed to detect cancer early, when survival rates are highest and treatment is most effective. But what will the full testing process look like for patients?