Artificial intelligence is quietly transforming how pharmaceutical companies develop cancer drugs by automating the analysis of tissue samples, a shift that could speed up the journey from lab discovery to patient treatment. Imagene AI, a precision oncology company, announced today that it has joined the Proscia Ready partner alliance, integrating its AI-powered image analysis tools with Proscia's Concentriq platform, a digital pathology system used by 16 of the top 20 pharmaceutical companies.

What Are Companion Diagnostics and Why Do They Matter?

Companion diagnostics are tests that identify which patients will benefit most from a specific drug before treatment begins. They're becoming essential in precision oncology, where one-size-fits-all approaches are giving way to targeted therapies tailored to individual patient biology. The problem is that developing these diagnostics traditionally requires multiple organizations, including pharmaceutical sponsors, diagnostic companies, and contract research organizations (CROs), to work in silos with fragmented data and workflows.

This fragmentation slows down the entire process. Imagene AI's integration with Proscia aims to solve that by creating a unified digital environment where teams can collaborate seamlessly from the initial biomarker discovery phase through clinical validation and final deployment in hospitals and labs.

How Does AI Image Analysis Improve Pathology Workflows?

Traditional pathology relies on human experts visually examining tissue slides under a microscope, a process that is subjective and time-consuming. Imagene AI's technology applies advanced artificial intelligence to automate and quantify what pathologists see. The company's capabilities include high-definition cell and sub-cellular segmentation, meaning the AI can identify and measure individual cells and their components with precision that would be difficult or impossible for humans to achieve consistently.

The platform also identifies meaningful feature combinations that differentiate patient populations, offers continuous and advanced spatial scoring, and provides stratification tools for analyzing patient groups. In essence, the AI transforms qualitative observations into quantitative data that can be standardized, validated, and deployed at scale across multiple laboratories and clinical trials.

Steps to Operationalize AI-Powered Companion Diagnostics

• Biomarker Strategy: Imagene AI partners with biopharma organizations to define which biological markers should be measured and why they matter for patient selection and drug response prediction.
• Quantitative Assay Development: The AI tools are used to develop standardized, measurable assays that can be validated and reproduced across different laboratories and patient populations.
• Validation and Regulatory Planning: Organizations work through the regulatory pathway, ensuring the AI-powered assay meets standards set by agencies like the FDA, including planning for clinical validation studies.
• Deployment Readiness: Once validated, the assay is integrated into clinical workflows, allowing diagnostic laboratories to run the test on patient samples and provide results that guide treatment decisions.

Who Benefits From This Integration?

The collaboration creates value across the entire companion diagnostic ecosystem. For pharmaceutical companies, the integration provides a scalable foundation for incorporating advanced quantitative pathology into biomarker strategies and clinical development programs. Diagnostic assay and platform providers can complement their existing tissue-diagnostic capabilities with AI-powered image analysis. Contract research organizations can incorporate Imagene AI's capabilities into the global laboratory workflows they support for multiple clients.

"Companion diagnostic development depends on bringing specialized expertise and technology together," said Stephan Fromme, Head of Business Development at Proscia. "Imagene AI expands the advanced quantitative image analysis and deep precision-oncology capabilities available through Proscia Ready. Together, we can help more pharmaceutical companies and their diagnostic and laboratory partners efficiently operationalize AI-powered IHC workflows, from biomarker strategy to clinical impact."

Stephan Fromme, Head of Business Development at Proscia

A Real-World Example of AI-Powered Pathology Success

Imagene AI's track record demonstrates the potential of this approach. The company developed LungOI, described as the first AI-based non-small cell lung cancer (NSCLC) multi-gene biomarker panel to receive a PLA (Proprietary Laboratory Analysis) code and CMS (Centers for Medicare and Medicaid Services) payment rate. This achievement is significant because it means the test has been validated, approved for clinical use, and is now reimbursed by Medicare, removing a major barrier to adoption in real-world patient care.

The development, validation, and deployment of LungOI across multiple centers and laboratories globally demonstrates that AI-powered pathology tools can move from research prototypes to clinical reality. This success story suggests that the Proscia integration could accelerate similar pathways for other cancer types and biomarkers.

Why Centralized Platforms Matter for Drug Development

Proscia's Concentriq platform is already used by leading pharmaceutical companies and CROs across drug discovery, clinical development, and companion diagnostic development. The platform provides a GxP (Good Practice) environment, meaning it meets regulatory standards for building and validating algorithms. Teams can then deploy these validated algorithms at scale across global trials on the same platform.

Because Concentriq is also used by diagnostic laboratories managing millions of patient cases each year, it creates a direct pathway for validated diagnostics to move from approval into broad clinical adoption. This integration of research, validation, and clinical deployment on a single platform reduces the friction and delays that typically occur when organizations must manually transfer data and algorithms between disconnected systems.

"By joining Proscia Ready, we are making it easier to integrate advanced AI image analysis into established pathology workflows and scale IHC companion diagnostic programs from biomarker strategy through clinical development and deployment," said Michael Hreczuck, Senior Vice President of Business Development at Imagene AI.

Michael Hreczuck, Senior Vice President of Business Development at Imagene AI

What Does This Mean for Patients?

The practical impact of this integration is faster, more accurate drug development and more precise patient selection for cancer therapies. When pharmaceutical companies can more quickly identify which patients will benefit from a drug, clinical trials become more efficient. When diagnostic tests are standardized and validated through AI, patients receive more consistent and reliable results, regardless of which laboratory performs the test. And when the entire ecosystem works on a unified platform, the time from biomarker discovery to clinical deployment shrinks, meaning patients gain access to precision therapies sooner.

The Proscia Ready alliance represents a broader industry trend toward integrated, interoperable solutions in digital pathology. Rather than companies building isolated point solutions, the alliance combines technologies, coordinates customer support, and shares a vision for continued innovation. This collaborative approach helps organizations reduce the complexity of implementing and managing solutions from multiple vendors, ultimately making it easier for healthcare systems to adopt AI-powered diagnostics at scale.