# Katie Maloney, Partner at DeciBio Consulting, Sees an Inflection Point for Digital and Computational Pathology

Page: https://stenobird.com/podcast/mendelspod-podcast-742570/katie-maloney-partner-at-decibio-consulting-sees-an-inflection-point-for-digital-and-computational-pathology
Text version: https://stenobird.com/podcast/mendelspod-podcast-742570/katie-maloney-partner-at-decibio-consulting-sees-an-inflection-point-for-digital-and-computational-pathology.md
Podcast: [Mendelspod Podcast](https://stenobird.com/podcast/mendelspod-podcast-742570)
Published: 2026-09-15T16:58:29+00:00
Episode link: https://www.mendelspod.com/p/katie-maloney-partner-at-decibio
Audio file: https://api.substack.com/feed/podcast/215533240/6e1c0a5376f80100196cccfee9f062d9.mp3
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Duration seconds: 368

## Resource

This is a free preview of a paid episode. To hear more, visit www.mendelspod.com Digital technology has been promising to transform pathology for years. But the last year looks different. Roche paid roughly $1 billion for PathAI. Tempus acquired Paige. Other deals are adding to a sudden wave of consolidation. And AstraZeneca is developing a computational pathology algorithm for TROP2 that could become a companion diagnostic used to determine which patients receive a drug. DeciBio partner Katie Maloney says these are signs that digital pathology may finally be reaching an inflection point. The important shift is from digital to computational pathology. Until recently, much of the value proposition was about making an existing workflow more efficient. Now algorithms are beginning to extract clinical information that a pathologist could not simply determine by eye. Maloney points to tools that can predict prognosis, stratify patients and potentially predict drug response. Computational pathology is beginning to compete with, and increasingly complement, molecular diagnostics. The transition is still early. Maloney estimates that only 20 to 30 percent of US labs have adopted even a slide scanner. Reimbursement remains a major obstacle, with labs generally not paid for scanning slides, using image management software or deploying computational algorithms. And some of the hardest problems are surprisingly basic. Different labs stain the same tissue differently, creating variability that algorithms must accommodate if they are going to work across thousands of clinical sites. But pharma may change the equation. Maloney is watching to see whether AstraZeneca’s work proves to be an isolated example or the beginning of something much larger. If computational pathology becomes im…

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