Owkin, a French American biotech company, has shared validation data for MSIntuit CRC, its artificial intelligence-powered digital pre-screening solution designed to optimize the diagnosis and treatment of colorectal cancer. The solution focuses on screening patients for microsatellite instability (MSI), a key genomic biomarker in colorectal cancer. MSI is found in 15% of cases, and recent clinical trials suggest its prognostic and therapeutic significance, particularly in determining responses to immune checkpoint inhibitor therapies.

Figure 1. Owkin’s AI Diagnostic for Colorectal Cancer Takes Center Stage with Promising Validation Results

Figure 1 shows Owkin’s AI Diagnostic for Colorectal Cancer Takes Center Stage with Promising Validation Results Owkin's validation study, published in Nature Communications, indicates that AI-based solutions, such as MSIntuit CRC, can be reliably taught to pre-screen patients in the clinic. The AI model was trained on samples from the Cancer Genome Atlas and blindly validated on a dataset of 600 colorectal cancer cases from nine pathology labs. The results showed that MSIntuit CRC accurately ruled out nearly 50% of microsatellite stable (MSS) patients while correctly classifying over 96% of MSI patients, aligning with the current gold standard. The solution demonstrated consistency across different scanners and slides containing samples from various tumor regions. Importantly, the AI-based approach provides results much faster, within hours rather than days, offering potential improvements in timely and effective treatment decisions for colorectal cancer patients.

Owkin's MSIntuit CRC, an artificial intelligence-powered digital pre-screening solution for colorectal cancer, is anticipated to impact oncologist decision-making, potentially bringing the best treatment to patients sooner, according to proponents. The solution has the potential to optimize costs and organization of microsatellite instability (MSI) testing in pathology labs, particularly in countries implementing universal MSI screening. Dr. Magali Svrcek, a co-author of the publication and professor at Saint Antoine Hospital, Sorbonne Université, emphasized the solution's role in improving patient outcomes and its significance in streamlining diagnostic processes.

Meriem Sefta, PhD, Chief Diagnostic Officer at Owkin, highlighted the solution as a groundbreaking step toward developing an AI diagnostic capable of identifying actionable biomarkers from a single hematoxylin and eosin (H&E) slide used in clinical routine. Owkin has been expanding its activities in the drug discovery space through strategic partnerships with pharmaceutical and other companies. A recent collaboration with Servier, a pharmaceutical group, focuses on leveraging AI to gain insights into disease biology and identifying patient populations likely to benefit from new therapies. This reflects Owkin's commitment to advancing therapies across various disease areas using machine learning capabilities.

In collaboration with Servier, Owkin's initial project aims to identify tumor types, tumor microenvironments, and patient subgroups that would respond optimally to a specific Servier asset. By analyzing data on tumor evolution, the partners aim to pinpoint drug combinations that could act on additional immune checkpoints or tumor cell-intrinsic mechanisms. The second project will explore the implementation of digital pathology to accelerate screening processes and facilitate a more comprehensive analysis of tissue-based biomarkers.

Owkin has also entered into an agreement with Genmab, a biotech company specializing in antibody-based therapeutics for cancer and other diseases. Under this agreement, Owkin utilizes its platform to assess the impact of Genmab's clinical assets on specific cancer types. These collaborations highlight Owkin's commitment to leveraging artificial intelligence and machine learning to advance drug discovery and enhance therapeutic strategies across various disease areas.

Source:genengnews

Cite this article:

Janani R (2023), Owkin’s AI Diagnostic for Colorectal Cancer Takes Center Stage with Promising Validation Results, Anatechmaz, pp.388