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ImpriMed is exhibiting at the VCS–VSSO Collaborative Conference to showcase our AI-driven Personalized Prediction Profile (PPP) for canine lymphoma. In addition, our Director of Bioscience, Dr. Ilona Holcomb, will deliver an oral abstract presentation titled, “A Multi-Omic Approach to Biomarker Discovery for the Differential Diagnosis of Feline IBD and EATL Using Minimally Invasive Specimens” on March 19. We look forward to connecting with veterinary oncologists and surgeons to discuss advances in precision diagnostics and treatment planning.
ImpriMed is exhibiting at AACR to highlight our multi-modal precision oncology platform. Stop by our booth #1960 to explore how combining functional drug sensitivity testing delivers clinically meaningful insights.
ImpriMed will be exhibiting at TRI-CON to present our integrated precision medicine approach for oncology research and drug development. Meet our team to learn how our ex vivo testing platform and AI models enable smarter enrollement strategies, and support trial enrichment and precision-driven design.
ImpriMed will be attending ASCO to engage with oncology leaders and explore advancements in precision medicine. We look forward to connecting with collaborators interested in ex vivo drug sensitivity testing and AI-driven approaches to personalized cancer treatment.
ImpriMed is proud to sponsor and present at the Veterinary Cancer Society 2026 Annual Conference in Minneapolis. Join us for insightful discussions on advancements in veterinary oncology and connect with our team!
ImpriMed is exhibiting at ID Week to showcase our data-driven modeling platform. Visit our booth #1142 to discuss how our technology can support infectious disease research, translational studies, and personalized therapeutic strategies.
ImpriMed will be exhibiting at ASH to showcase our AI-driven precision medicine platform for hematologic malignancies. Visit our booth #226 to learn how our ex vivo drug sensitivity testing and predictive analytics generate patient-specific insights to help guide treatment decisions.
