Angela Hirbe, MD, PhD, is Associate Professor of Medicine and Pediatrics in the Division of Oncology at the Washington University School of Medicine. She is also the Director of the Sarcoma Program and Director of the Adult Neurofibromatosis Clinical Program at the Washington University School of Medicine. Clinical Interests: Her interests include oncology, neurofibromatosis-related tumors, sarcoma management, pediatric oncology, and management of cancer predisposition syndromes. Memberships: She is the vice chair of the NCCN Bone Panel and a member of the Children’s Tumor Foundation and SARC Career Development Committee. She is co-chair of the Neurofibromatosis Clinical Trials Consortium MPNST committee, as well as a member of the Children’s Oncology Group, and an elected member of the American Society of Clinical Investigation. Research and Trials: Dr. Hirbe has participated in various clinical trials related to peripheral nerve sheath tumors, MPNST, and NF1. She also runs a basic/translational lab interested in early cancer detection in NF1 and preclinical modeling.
The goal of the panel is to move beyond the usual high-level conversations and instead focus on the practical ingredients needed to build truly actionable biomarkers. In particular, we want to highlight three dimensions that must come together:
Affordable data – Dave Zhang from BioState AI will discuss how new sequencing platforms combined with AI/ML analysis are dramatically reducing the cost of generating high-quality molecular data.
Accessible data – Maxine Chan from Washington University will be the voice who can speak to the real barriers around accessing clinical data from systems such as EPIC/Oracle and the complexities surrounding data interoperability.
Available multimodal data – Ali Bashashati, in digital pathology and large-scale image analysis and Angela Hirbe on liquid biopsies to predict malignant transformation, beautifully illustrate how new tools are enabling researchers to interrogate enormous datasets and extract meaningful biological signals.
The central message of the panel is simple: breakthrough biomarkers will not come from a single data modality. They will emerge when genomics, clinical data, and imaging are integrated thoughtfully.