Mr. Rashid Bux reports

BIOMARK DIAGNOSTICS ANNOUNCES BREAKTHROUGH PUBLICATION REINFORCING LEADERSHIP IN AI-POWERED METABOLOMICS FOR ONCOLOGY

Biomark Diagnostics Inc. has published a significant study exploring an artificial intelligence (AI) approach using novel graph neural networks (GNNs) that enhances the potential for early lung cancer diagnosis by modelling the complex web of metabolic pathways in cancer. The research paper, titled "M-GNN: A Graph Neural Network Framework for Lung Cancer Detection Using Metabolomics and Heterogeneous Graph Modeling," was accepted for publication in the Special Issue of International Journal of Molecular Sciences on Machine Learning in Bioinformatics and Biomedicine demonstrates how Biomark's investments in AI and machine learning are supporting current studies, boosting its cancer diagnostic platform and opening new frontiers in metabolomics.

The research, a collaboration between Biomark's scientific team, Harrisburg University of Science and Technology, and St. Boniface Hospital Research Centre & Asper Clinical Research Centre, introduces the M-GNN framework. This innovative model leverages graph neural networks to interpret complex biological interactions by analyzing metabolomics data alongside patient demographics and established metabolic pathway information.

"Recent advancements in GNNs have been proven effective in modelling relational data, making them ideal for capturing complex interactions within biological systems, such as those between patients' clinical data, blood metabolites, metabolic function and disease pathways. GNNs have been applied to multiomics data for cancer prognosis and subtype classification, including lung cancer. However, their application in metabolomics-driven early detection remains largely unexplored, even with the enriched relational context provided by databases like the human metabolome database (HMDB)," says Jean-Francois Haince, PhD, Biomark's chief scientific officer.

This research signifies a pivotal advancement in the field of metabolomics and underscores Biomark's commitment to investing in AI-driven diagnostics. The M-GNN framework offers a scalable and interpretable tool for precision oncology, which can be used to further refine Biomark's existing assays for lung, breast and neuroendocrine cancers, and pave the way for new diagnostic and prognostic tools.

"Lung cancer remains a devastating disease where early detection is paramount for improving patient survival," said Rashid Bux, chief executive officer of Biomark Diagnostics. "This publication showcases the power of integrating sophisticated AI, like graph neural networks, with our deep expertise in metabolomics. The M-GNN framework's ability to model intricate biological relationships represents a major step forward in our mission to deliver highly accurate and accessible early cancer detection solutions. We are immensely proud of our team of collaborators at Harrisburg University and St. Boniface Hospital Research Centre & Asper Clinical Research for this achievement."

While the M-GNN framework shows immense promise, further validation on larger, diverse real-world data sets will be important for clinical translation. The company is actively exploring pathways to integrate these advanced AI methodologies into its product development pipeline.

"By incorporating advanced AI like GNNs, Biomark is not just improving diagnostic accuracy; we are building a foundation for a new generation of precision oncology tools," added Mr. Bux. "This technology has the potential to expand beyond initial detection to areas like treatment response monitoring and the discovery of new therapeutic targets, solidifying our position at the forefront of AI-driven metabolomics."

The full publication can be accessed on the International Journal of Molecular Sciences website.

About Biomark Diagnostics Inc.

Biomark Diagnostics is a leading developer of liquid biopsy tests for the early detection of cancer that leverages the power of metabolomics and machine learning algorithms. The company's proprietary technology utilizes a simple blood draw to detect the presence of cancer-associated biomarkers, enabling earlier diagnosis and improved patient outcomes. The technology can also be used for measuring response to treatment and potentially for serial monitoring of cancer survivors. Biomark Diagnostics is committed to developing innovative and accessible diagnostic solutions to address unmet medical needs in oncology.

We seek Safe Harbor.