Gene Expression on Routinely Processed Tissue - NanoString


Revolutionizing IHC - From one qualitative target to multiple targets quantitatively

Bridging Pathology & Molecular Biology. Use us to leverage morphological AND molecular information.

Global Laboratory System

Epitope Mapping of PD-L1 Primary Antibodies

Digital pathology in immuno-oncology – a roadmap for clinical development


HistoGeneX Global Laboratories announces its publication “Digital Pathology in Immuno-Oncology – A Roadmap for Clinical Development.” This timely manuscript describes validation methodologies that can be used for oncology clinical development, specifically immunotherapies. Digital pathology offers enticing features, not the least of it as an enhanced microscope platform for viewing, collaboration and distribution. In addition, there are a broad milieu of downstream applications for analyzing the resultant high resolution whole slide image. The combination is especially relevant given the renewed emphasis of assessing the tumor microenvironment (TME) when developing immune-oncology therapeutics. The paper discusses the varied pressures - such as cost, workflow, initial set up logistics, and regulatory factors - that constrain the use of a technology that seems so obviously suited for the anatomic pathology laboratory. The second part of the manuscript reviews the available validation guidelines from the FDA and CAP which primarily addresses manufacturers and clinical laboratories respectively but do not provide guidance for clinical developers. Both guidelines take on different approaches, the FDA unpacks the digital pathology system into components while CAP focuses on what emerges from the “black box.” A hybridized model – merging elements of both validation approaches – is presented to the clinical development reader. Finally, the manuscript reviews a series of analysis applications, in particular, the ones that extract valuable data from the TME, and introduces the concept of a laboratory developed digital application (LDDA) that leverages the familiarity of a LDT.