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Unlocking the Glycoproteome: Utilizing a Robust AI/ML Based Platform for Biomarker Discovery

Available on-demand
60 Minutes

Liquid biopsies have shown tremendous progress for the early detection of cancer and for treatment monitoring, but still have limitations in sensitivity and specificity. The inclusion of protein glycosylation can help address these challenges.

Glycoproteomic analysis is now emerging as a promising tool. These biomarkers have the potential to play a crucial role in early intervention and personalized therapy decisions. In the past, the complexity of data generated using mass spectrometry - which is the most reliable method for identifying glycoproteins - made it difficult to analyze the glycoproteome at scale.

Join us for this insightful discussion about the latest solutions for combining robust assays with artificial intelligence and machine learning to accelerate data processing, overcome current barriers, and provide crucial information that is missing from the existing -omics landscape. We’ll explore real-world examples with a look at:

  • Prediction of response to immunotherapy

  • Impact of glycosylation on antibody binding

  • How using a multi-omic knowledge graph can lead to new insights into disease biology


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Daan Hommes, M.D., PH.D.

Daan is a trained internist / gastroenterologist with over 25 years of clinical practice. He served various roles including Department Chair and Professor of Gastroenterology and Hepatology at Leiden University Medical Center; Professor of Medicine at University of California Los Angeles (UCLA); President of the European Crohn’s and Colitis Organization (ECCO); Professor of Health Innovation and Applied Artificial Intelligence at the University of Leiden; and Founder and CEO of DEARhealth, a UCLA spin-off company offering AI-powered Care Pathways. Daan completed his Ph.D. in biomarkers and experimental treatments in Inflammatory Bowel Diseases (IBD) and having lectured around the world and authored over 280 peer-reviewed papers, he offers InterVenn deep scientific and clinical expertise in host immune responses, malignant transformation processes and biomarker development.

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Dan Serie, M.S.

Dan is the Chief Data Officer at InterVenn, with over 15 years of experience mining the genome and proteome for biological and clinical insights. After joining in late 2017, his team was responsible for training, deploying, and publishing the world's first neural network for mass spectrometry peak selection and integration. Prior to starting at InterVenn, Dan led analytical efforts for dozens of scientific publications in cancer, neurodegenerative disease, and cardiovascular health at the Mayo Clinic. He holds a Bachelor of Science degree in Mathematics from the University of Minnesota and a Master's in Applied Statistics from Penn State. His team continues development on advanced machine learning techniques for detecting, quantifying, and utilizing glycoproteins, in service of the ultimate goal: moving these novel biomarkers into clinical practice and improving patient outcomes.

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Kai He, M.D., PH.D.

Dr. He is a distinguished board-certified medical oncologist, serving as an Associate Professor of Medicine with Tenure within The Ohio State University's Thoracic Oncology Program and Cancer Cell therapy Program. Having completed both clinical and research fellowships in Medical Oncology at Johns Hopkins Hospital, Dr. He received accolades including a T32 training grant for his investigation into epigenetics and cancer immunity in lung cancer. He further enriched his expertise through PhD training in Cell Biology at the University of Alabama at Birmingham. Within the Translational Therapeutics Program at OSUCCC – James, Dr. He’s research delves into cancer epigenetics, genomics, and immunology, with a particular focus on developing innovative biomarkers and therapies for lung cancer. His laboratory scrutinizes factors influencing response and resistance to immunotherapy in lung cancer. Dr. He’s contributions extend beyond the laboratory, with over 50 publications in esteemed peer-reviewed journals such as Cancer Discovery, Journal of Thoracic Oncology, Journal Of Clinical Oncology, Lung Cancer, Journal of Hematology & Oncology and others. Recently, he co-authored an authoritative review on the use of glycoproteomics in clinical oncology with Nobel Prize laureate Carolyn Bertozzi (J Hematologist Oncol 2024;17(1):12).

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60 Minutes