What practicing pathologists and oncologists should know about the new computational pathology‐based companion diagnostic tools
The Journal of Pathology, vol. 269, pp. 143–148
Abstract
The integration of artificial intelligence into pathology is transforming the assessment of histological and immunohistochemical (IHC) slides, offering opportunities to reduce variability and streamline diagnostics. In practical terms, most available tools and research models emulate the diagnostic capabilities of pathologists by detecting, grading, and classifying tumours and other diseases. More recent applications have moved beyond mimicry, aiming to predict established biomarkers, such as microsatellite instability or IHC-based markers, and to tackle even more ambitious tasks, such as directly predicting patient prognosis from H&E whole slide images. Remarkably, novel computational tools are now being designed as companion diagnostic assays, linking the automated evaluation of specific IHC biomarkers to the prediction of response to specific drugs, potentially marking a new chapter in the evolution of digital and computational pathology. The TROPION-PanTumor01 trial recently demonstrated the superiority of a supervised machine learning model (termed the quantitative continuous score [QCS] by the vendor) in assessing TROP2 IHC compared with human scoring, promising better stratification of patients with non-small cell lung cancer for treatment with datopotamab deruxtecan. The same approach has shown promise in refining HER2 (human epidermal growth factor receptor 2) and PD-L1 (programmed death-ligand 1) evaluations, revealing patient subgroups that may benefit from targeted therapies. Moreover, other similar approaches are progressively reaching the market, posing significant opportunities and challenges for clinicians involved in the care of patients with cancer. This Perspective is promoted by the European Society of Digital and Integrative Pathology (ESDIP, founded in 2016, and having long-standing experience in computational pathology, esdipath.org) and the European Interdisciplinary Society of Artificial Intelligence for Cancer Research (ESAC, a recently established initiative, founded in 2024, esac-network.eu), both bringing together clinicians, engineers and other professionals dedicated to the development and clinical translation of computational approaches aimed at improving patient care. It aims to provide an informed overview of novel computational pathology companion diagnostic tools, with a particular focus on the background that practicing pathologists and oncologists need to have with these tools, when transitioning from research to clinical practice, irrespective of their prior familiarity with computational approaches. © 2026 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Authors 12
-
Instituto Português de Oncologia Francisco Gentil · IPO Porto · Centro de Investigação do Instituto Português de Oncologia do Porto Francisco Gentil · IMP Diagnostics (Portugal) · RISE - Health Research Network
Affiliation as printed
Cancer Biology and Epigenetics Group, Research Center of IPO Porto (CI‐IPOP) Portuguese Oncology Institute of Porto, Comprehensive Cancer Center Raquel Seruca (Porto.CCC) & CI‐IPOP@RISE (Health Research Network) Porto Portugal
European Society of Digital and Integrative Pathology (ESDIP) Lisbon Portugal
Research & Development Unit, IMP Diagnostics Porto Portugal
-
The Netherlands Cancer Institute
Affiliation as printed
Computational Pathology Group, The Netherlands Cancer Institute Amsterdam The Netherlands
European Society of Digital and Integrative Pathology (ESDIP) Lisbon Portugal
-
Affiliation as printed
Department of Digital Medicine University of Bern Bern Switzerland
European Society of Digital and Integrative Pathology (ESDIP) Lisbon Portugal
Institute of Tissue Medicine and Pathology (ITMP), University of Bern Bern Switzerland
-
Radboud University Nijmegen · Radboud University Medical Center
Affiliation as printed
Computational Pathology Group, Department of Pathology Radboud University Medical Center Nijmegen The Netherlands
European Society of Digital and Integrative Pathology (ESDIP) Lisbon Portugal
-
Vall d'Hebron Hospital Universitari
Affiliation as printed
European Society of Digital and Integrative Pathology (ESDIP) Lisbon Portugal
Pathology Department, Vall Hebron University Hospital Barcelona Spain
-
Haukeland University Hospital · University of Bergen
Affiliation as printed
Department of Clinical Medicine University of Bergen Bergen Norway
Department of Pathology Haukeland University Hospital Bergen Norway
European Society of Digital and Integrative Pathology (ESDIP) Lisbon Portugal
-
Affiliation as printed
European Society of Digital and Integrative Pathology (ESDIP) Lisbon Portugal
ImginIT Paris France
-
University of Medicine and Pharmacy of Craiova · University of Craiova
Affiliation as printed
Department of Medical Informatics and Biostatistics University of Medicine and Pharmacy of Craiova Craiova Romania
European Society of Digital and Integrative Pathology (ESDIP) Lisbon Portugal
-
Fondazione IRCCS Istituto Nazionale dei Tumori · Politecnico di Milano
Affiliation as printed
Department of Electronics, Information, and Bioengineering Polytechnic University of Milan Milan Italy
European Interdisciplinary Society for AI in Cancer Research (ESAC) Milan Italy
Thoracic Oncology Unit, Department of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori Milan Italy
-
University of Leeds · University Hospital Heidelberg · National Center for Tumor Diseases · Else Kröner Fresenius Center for Digital Health · Technische Universität Dresden
Affiliation as printed
Department of Medicine I, Faculty of Medicine TUD Dresden University of Technology Dresden Germany
Else Kröner Fresenius Center for Digital Health, Faculty of Medicine TUD Dresden University of Technology Dresden Germany
European Interdisciplinary Society for AI in Cancer Research (ESAC) Milan Italy
Medical Oncology, National Center for Tumor Diseases (NCT) University Hospital Heidelberg Heidelberg Germany
Pathology & Data Analytics, Leeds Institute of Medical Research at St James's University of Leeds Leeds UK
-
Humboldt-Universität zu Berlin · Universitätsklinikum Aachen · Charité - Universitätsmedizin Berlin · RWTH Aachen University
Affiliation as printed
Charité ‐ Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin Institute of Medical Informatics Berlin Germany
European Society of Digital and Integrative Pathology (ESDIP) Lisbon Portugal
Institute of Pathology RWTH Aachen University Hospital Aachen Germany
-
Vincenzo L'Imperio corresponding
Affiliation as printed
Department of Pathology Fondazione IRCCS San Gerardo dei Tintori Monza Italy
European Society of Digital and Integrative Pathology (ESDIP) Lisbon Portugal
School of Medicine and Surgery University of Milano‐Bicocca Milan Italy
Cited by 2 stored of 2
2 results
No patents citing this paper on Lens.org (checked 2026-10-06).