John: What inspired you to start SpatialX, and how has your vision for the company evolved since its inception?

Noor: Every year, cancer claims 10 million lives. A significant part of this tragedy stems from our inability to detect cancer early and our lack of tools to determine which patients will respond to which treatments. This was the reality we faced—until now. I believe we have the tools and technology to change this narrative. I founded SpatialX to harness the transformative potential of artificial intelligence and give every patient a fighting chance against cancer.



John: SpatialX has developed AI models for analyzing tumor microenvironments. How do you see AI transforming pathology and cancer diagnostics in the next five years?

Noor: Pathology largely relies on centuries-old technology—the microscope—and the human eye. This introduces limitations and subjectivity. Ideally, a tissue sample should yield the same diagnosis, regardless of when or by whom it is examined. Yet, this is far from reality. Furthermore, the sheer complexity of cancer surpasses human capacity; while experts can diagnose and stage cancer, they often cannot predict, for instance, which patients will benefit from specific treatments. AI brings the power and sophistication needed to decode cancer’s intricacies, providing an unparalleled tool to tackle these challenges.

John: Can you tell us more about one of your collaborations or major successes that you found particularly impactful in putting SpatialX AI on the map?

Noor: We collaborate with several leading hospitals to develop AI tools for cancer diagnosis and prognosis. One notable success is our work with UPMC and Emory on bile duct biopsies. Here, AI flagged cases that pathologists would have missed. In another project focused on colon cancer, our AI models predicted overall survival and identified patients likely to develop metastases. Moreover, the AI discovered novel features that significantly enhanced risk prediction.

John: What have been the most significant challenges in integrating AI into traditional pathology workflows, and where does SpatialX offer unique value in this regard?

Noor: The biggest hurdles are digitization and workflow integration. AI must seamlessly integrate into everyday practices, yet many hospitals are still in the early stages of digitization. SpatialX addresses this through Orca, our cloud-based AI platform for whole-slide image analysis. Orca simplifies AI model development, validation, and deployment, empowering pathologists to use AI effortlessly. Its unique integration of label-free foundation models allows the discovery of novel, annotation-free features linked to disease outcomes, opening up new possibilities for biomarker research.

John: In what settings or collaborations do you work most closely with spatial biology scientists, and how do these interactions influence your work at SpatialX?

Noor: We use “spatial” to highlight AI’s ability to analyze not just the types and quantities of cells but also their spatial arrangement. This focus enables the discovery of entirely new biomarkers that were previously immeasurable. Emerging evidence underscores the relevance of spatial features in guiding treatment decisions. Through unsupervised learning, we are uncovering previously unseen morphological and spatial patterns that hold immense potential for advancing patient care.

John: SpatialX offers tools like the Orca™ platform. How do these platforms enhance the accessibility and scalability of AI tools in labs?

Noor: Orca is a cloud-based, AI-native platform designed for global accessibility. It’s device-friendly, enabling users to perform case reviews, annotations, and comment sharing from phones or tablets. We’ve also connected Orca to a robust high-performance computing infrastructure, allowing pathologists to train and deploy AI models on hundreds of images with ease.

John: What measures have you taken to ensure ethical AI use and safeguard patient data in your platforms?

Noor: Orca processes fully anonymized whole-slide images without any patient identifiers, ensuring compliance with privacy and ethical standards.

John: Which specific disease areas or diagnostic challenges are you focusing on, and how do you envision expanding these applications in the future?

Noor: Our technology is disease-agnostic, adaptable to any cancer type. For example, Orca has supported pathologists working on a wide range of cancers such as colon, melanoma, and pancreatic cancers as well as quantifying biomarkers like Ki-67 and PD-L1. By building a foundational platform, we empower pathologists to tailor AI models to their unique datasets and diagnostic needs.

John: As a successful entrepreneur rapidly advancing in your field, what advice would you give to aspiring founders looking to make an impact in healthcare?

Noor: Healthcare uniquely combines the joy of scientific advancement with the profound impact of saving lives. We’re at an unprecedented moment where AI has reached a transformative inflection point. It’s an exciting time to build in AI healthcare, and while the journey is challenging, it’s deeply fulfilling.

John: What is one of the most important lessons you’ve learned as a founder that you would share with someone aspiring to launch a start-up in this field?

Noor: A startup’s strength lies in its people. I’ve been fortunate to work with incredibly talented and dedicated individuals. Surrounding yourself with the right team can make all the difference.


Contact Information for SpatialX:

• email: contact@spatialx.ai

• phone: +44 (0) 7742 2138 81

• address: 5a Clarendon Rd., W11 4JA, London, United Kingdom

• website