Introduction
In today’s evolving healthcare environment, digital pathology is now essential for improving laboratory efficiency, productivity, and operational excellence. Beyond these critical gains, laboratories that embrace cloud-native imaging and AI-driven analytics are also unlocking entirely new service lines — transforming slide archives and analytical insights into high-value offerings for pharmaceutical sponsors, research and clinical development partners supporting novel enrollment and biomarker assessment, and co-development collaborators.
According to Goldman Sachs Equity Research¹, the total addressable market (TAM) for digital pathology in the U.S. is projected to reach approximately $1 billion by 2030 and grow to $3 billion by 2035. This projected expansion reflects increased utilization of AI in research and pre-clinical settings, broader adoption of remote pathology workflows such as international consultations and tumor board reviews, and the digitization of whole-slide images (WSIs) to support drug development and biomarker discovery efforts.
Imagine being able to run AI-powered pre-screening on routine H&E or IHC scans to accelerate patient selection for clinical trials, or standardize biomarker quantitation with precision as part of an in vitro diagnostic (IVD) service. Envision packaging de-identified whole-slide image datasets enriched through spatial and single-cell analytics into real-world data products, linked with multimodal clinical and molecular data, that support biopharma teams as they evaluate novel biomarker hypotheses. And consider the possibilities of partnering with AI developers to co-design novel diagnostic and prognostic assays, leveraging both clinical expertise and advanced modeling, and then commercializing those algorithms to other labs that have digitized their workflows.
By layering these capabilities onto a best in class digital pathology platform, laboratories shift from traditional cost centers into strategic revenue generators with services that drive sustainable, high-margin growth.
In this blog, we’ll explore three key pathways to revenue generation in digital pathology: AI-driven trial pre-screening and IVD services, real-world data licensing and enrichment, and AI-enabled product co-development.
Trial Pre-Screening and IVD Services
Pharmaceutical sponsors require speed and precision when identifying biomarker‐positive patients for clinical trial enrollment, yet traditional workflows rely on manual slide review and reflex testing that can take days, incur significant per-test costs, and are tissue destructive. Deployed as Research Use Only (RUO) algorithms, AI-powered pre-screening analyzes routine H&E and/or IHC slides nearly in real time, identifying potential clinical trial participants for confirmatory testing and reducing the volume of downstream assays. Through these trial collaborations, laboratories can partner with pharma to pre-screen patients with potential biomarker eligibility to inform whether a patient could be a fit for a clinical trial. Compensation to the laboratory for these services can help cover any labor or technical investments required for such programs, while allowing laboratories to offer access to the latest experimental trials and treatment options.
Once these AI algorithms achieve diagnostic regulatory approval, the same streamlined workflow can evolve into medical devices including complementary diagnostics. Laboratories wishing to offer the latest and most advanced biomarker testing to their customers can offer a unique value proposition of the most advanced testing menu, differentiating themselves in the competitive laboratory testing market.
Real-World Data Licensing and Enrichment
Every digitized slide is a valuable data asset. By converting archived slide libraries into de-identified, research-ready datasets, labs can unlock a powerful new revenue channel. Each whole-slide image—paired with anonymized specimen and clinical metadata—is organized into a common model that partners can query on demand, eliminating lengthy negotiations and generating licensing fees, as the data can support publications, observational studies, or academic collaborations.
Layering AI analytics onto these cohorts further amplifies their value. Spatial biomarker maps and single-cell metrics transform standard slide images into structured histopathology datasets, premium research assets that biopharma teams can utilize to recapitulate findings from early clinical studies, and further explore novel hypotheses in larger observational cohorts. Offered as subscription or per-use access, these AI-enriched datasets create a revenue stream from samples that might be stored or archived and never looked at again.
Product Co-Development
Laboratories play a critical role in advancing patient care — and when they collaborate with AI partners, they can also help drive the development of novel diagnostic and prognostic assays. By combining clinical expertise, specimen archives, AI modeling platforms, and a global network of pathologists, labs and AI partners can co-create new products and revenue-share agreements. Joint development efforts typically begin with collaborative assay design, leveraging foundational AI models and expert annotations, and progress through validation support, regulatory submission, and global commercialization. Multisite validation studies and co-authored publications further strengthen credibility and attract additional sponsorship opportunities. Once commercialized, early-stage AI-powered prognostic tests can command premium per-case fees, creating significant value for both laboratory and AI partners.
Conclusion
Digital pathology is reshaping the future of laboratory services, creating new opportunities to extend impact beyond traditional diagnostics. From AI-driven trial pre-screening and IVD workflows to enriched real-world data licensing and collaborative assay development, the opportunities for high-margin growth are tangible today. Each of these pathways not only accelerates clinical research and drives precision-medicine initiatives but also enhances your lab’s role as a trusted leader and indispensable partner to sponsors, CROs, and academic collaborators.
Yet the real catalyst for success lies in choosing the right digital pathology partner. A best-in-class platform brings turnkey integration, day-one algorithm access and a proven network of pathologists and biopharma relationships—all backed by robust validation and commercialization support. With the right ally, your lab’s archives and expertise seamlessly evolve into new service offerings, unlocking sustainable revenue streams while maintaining the highest standards of quality and compliance.
"Select a vendor that can be an end-to-end provider of the future state digital pathology workflow, including expertise in AI development and LIS integrations."
— Dr. Brian Robinson, Vice Chair of Anatomic Pathology, Weill Cornell Medicine
By combining your clinical strengths with a partner’s AI innovation and global network, you’ll transform your laboratory from a cost center into a strategic revenue engine. The question is no longer whether digital pathology can drive growth—it’s who you choose to deliver on that promise.
Reference
- Goldman Sachs Equity Research. The Modernization of Pathology – The Use of Artificial Intelligence within Digital Pathology. May 29, 2024.Pages 2–5.
