# From Tissue to Mechanism to Decision: Building AI for Computational Oncology Page: https://stenobird.com/podcast/data-in-biotech-6628050/from-tissue-to-mechanism-to-decision-building-ai-for-computational-oncology Text version: https://stenobird.com/podcast/data-in-biotech-6628050/from-tissue-to-mechanism-to-decision-building-ai-for-computational-oncology.md Podcast: [Data in Biotech](https://stenobird.com/podcast/data-in-biotech-6628050) Published: 2026-06-02T17:00:27+00:00 Episode link: https://www.corrdyn.com/ Audio file: https://downloads.pod.co/5fac40cd-043b-485f-838d-c63fa01ae1b2/fa743fbd-dffe-4551-a7d9-906024888541.mp3 Processing state: not_requested JSON: https://stenobird.com/v1/public/podcasts/data-in-biotech-6628050/episodes/from-tissue-to-mechanism-to-decision-building-ai-for-computational-oncology Duration seconds: 2814 ## Resource In this episode of Data in Biotech, host Ross Katz sits down with Arvind Rao, Professor of Computational Medicine and Bioinformatics at the University of Michigan, for a discussion on the gap between what biomedical AI can do and what it can reliably be trusted to do in clinical practice. Arvind's research sits at the intersection of computational oncology and AI governance and his lab works across H&E histopathology, multiplex immunofluorescence, spatial transcriptomics, and single-cell RNA sequencing, not just to build predictive models, but to understand the full lifecycle from data to model to inference, and to ask where that lifecycle can be trusted and where it can't. The conversation moves through two of his recent papers on SPIFEE, a graph-based framework that replaces scalar interaction scores in the tumor microenvironment with spatially resolved functional representations, and a multimodal framework that traces a path from stained tissue slides to nominated drug targets via morphological pattern discovery and spatial transcriptomic mapping. What you’ll learn in this episode: >> Why the field's central failure is not algorithmic but translational and the gap between a model that performs well on a benchmark and one that can be consistently trusted in a high-stakes clinical setting >> How SPIFEE replaces the conventional scalar edge representation of cell-cell interactions in the tumor microenvironment with spatially resolved functional edges >> How Arvind's multimodal framework moves from H&E pathology slides labeled with clinical outcomes, through morphological pattern discovery via multiple instance learning, to spatial transcriptomic mapping, to the nomination of molecular mechanisms and actionable drug targets >> Why Goodhar… ## Actions - request_transcript: `POST https://stenobird.com/v1/public/podcasts/data-in-biotech-6628050/episodes/from-tissue-to-mechanism-to-decision-building-ai-for-computational-oncology/transcription-requests` — Idempotently request low-priority transcript generation for this episode. - read_markdown: `GET https://stenobird.com/podcast/data-in-biotech-6628050/from-tissue-to-mechanism-to-decision-building-ai-for-computational-oncology.md` — Read the agent-friendly Markdown representation of this episode resource. A page view does not enqueue transcription. Agents should invoke `request_transcript` explicitly when they need this episode processed. ## Transcript Full transcripts are not published on public pages unless there is a clear rights basis.