Artificial intelligence is transforming how researchers work with pathology, biospecimens, and preclinical models. In this webinar, three experts share practical applications of AI from quantitative image analysis to leveraging curated data and optimizing tumor model selection.
Beyond Human Eyes: How AI Turned Routine H&Es from Qualitative to Quantitative Insights
Meredith Osborn
Associate Director Product Management, Discovery Life Sciences
Pathology H&E slides have a long history as a rich source of qualitative data used in both the clinical and research settings to better understand patients’ pathology. However, our ability to generate quantitative data from these slides has been limited. Advances in targeted AI algorithms have created the potential to shift from small-cohort qualitative observations to large-scale quantitative data, empowering increased scalability and deeper insights. Examples of targeted AI use will include precise tumor percent evaluations, tumor-infiltrating lymphocyte cell counts, and identification of novel predicative biomarkers.
Unlocking Precision Medicine with Visionaire™: 30+ Years of Curated Biospecimen Data
Daryl Waggott
Director – Biologics, Data Products, BioIVT
This presentation explores how BioIVT’s decades of experience in biospecimen collection and curation are being used to support advancements in drug discovery and development. The presentation will delve into the unparalleled value of combining clinical, sociodemographic, and biospecimen data to support workflows integrating artificial intelligence. Learn how Visionaire™ packages this data into actionable insights that empower researchers to accelerate breakthroughs in oncology, neurodegenerative diseases, and beyond.
CertisOI Assistant™ – Optimizing Preclinical Cancer Model Selection with Agentic AI
Luke Jervis
Senior Software Engineer, Certis Oncology
Preclinical oncology researchers often struggle with identifying the most suitable tumor models due to limitations in traditional search platforms. This talk introduces CertisOI Assistant™, an AI-powered platform that supports researchers with natural language queries, dynamic model selection, and predictive analytics. By integrating proprietary PDX models with the Cancer Cell Line Encyclopedia (CCLE) and the CertisAI™ predictive intelligence platform, the tool allows researchers to search, refine, and visualize preclinical model selections in real time. The assistant supports exploratory research by generating targeted queries, running Python-based analyses, and producing interactive outputs—all while preserving security and privacy. This presentation will demonstrate how CertisOI Assistant enhances translational efficiency and early decision-making in oncology research.
Key Topics Include:
- Define high-level themes shared by AI implementations that add value.
- Learn how quantitative data generated from H&E images leads to actionable insights including tumor percent, TIL counts, and novel predictive biomarker identification.
- Understand how BioIVT’s clinically curated and data rich biospecimens support AI-driven research workflows and enhance drug discovery and development pipelines.
- Learn about the unique value propositions of Visionaire™, including data quality, reproducibility, and scalability, and how they empower precision medicine across therapeutic areas.
- Understand how agentic AI and LLMs are transforming tumor model selection in preclinical oncology.
- Learn how CertisOI Assistant integrates with predictive tools and interactive analytics to support dynamic research workflows.
Presenters
Associate Director Product Management
Discovery Life Sciences
Director - Biologics, Data Products
BioIVT
Senior Software Engineer
Certis Oncology
Production Partner
Discovery Life Sciences
BioIVT
Certis Oncology Solutions, Inc.
