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Introduction
Immunohistochemistry (IHC) is the “gold-standard” for pathology examination, but while manually handling the protocols, have you ever thought of all the positive what-ifs?
IHC a widely used technique in pathology that relies on antibodies to detect specific antigens in cells. IHC helps diagnosing a wide range of diseases, such as cancer and source of infection1. In oncology, IHC results help pathologists classify tumours, determine the site of origin, and guide treatment decisions with biomarkers.
Since its first reported application in the 1940s2, IHC has been serving it diagnostic purpose for pathologists. In breast cancer, for example, oestrogen and progesterone receptors are commonly stained to assess tumour characteristics. IHC is also widely used in drug development and translational research.
Conventional IHC involves staining thin tissue sections mounted on glass slides, and the process typically includes multiple steps as shown in fig.1a. While automation platforms (e.g., Roche Ventana, Dako/Agilent, Leica Biosystems) have improved standardisation and throughput in many hospital labs, the overall workflow remains labour-intensive. Full turnaround from sample to diagnostic report can take several days, especially in high-volume settings.
This is particularly challenging in the context of global pathology workforce shortages and rising demand for IHC testing driven by population ageing and precision medicine. Despite advances in digital pathology, such as the adoption of slide scanners and LIS integrations, the bottleneck of staining remains largely unsolved.
Virtual staining, first demonstrated by Rivenson et al.3 in 2019, presents an emerging alternative. Using deep generative neural networks trained and validated on thousands of whole slide images (WSI), this approach can computationally generate IHC-equivalent images from unstained or H&E- and HES-stained slides. The process (fig.1b) significantly reduces hands-on time, reagent usage, and costs. By replacing a time- and resource-intensive step of the IHC workflow, virtual staining represents a promising path to more efficient, scalable, reproducible, and sustainable pathology diagnostic results.
Turnaround time
IHC turnaround times can vary depending on the laboratory, the type and number of biomarkers tested, and whether additional analyses (e.g. FISH) are required, however in this context, we only consider IHC tests. In France, public hospitals, particularly high-throughput centres, typically report staining time of 24 to 72 hours depending on the sample type. Overall, IHC test reports are usually available within 1 to 3 working days, though advanced or multi-marker requests can extend to nearly a week, and the turnaround time varies by antibody types and lab organisations4,5,6.
In comparison, virtual staining can generate an IHC-equivalent image in a matter of seconds using H&E slides, or within one minute from unstained tissue using label-free AI models7, dramatically reducing diagnostic lead times.
Cost per sample
The cost of an IHC test includes both fixed components (e.g. lab equipment, maintenance, technician salary) and variable costs, mainly driven by antibody type and provider. In France, IHC pricing is standardised under national health tariffs. Reimbursement is based on the number of markers, and in practice, running a single IHC test will cost the healthcare provider from € 5 – 30, at €10.10 on average (fig.2)8,9. There is minimal cost difference between public hospitals and private labs conventionnés.
In the UK, NHS hospitals report internal costs for IHC testing isn’t directlyavailable to the public. However, based on expenditure data published by the Manchester University NHS Foundation Trust (one of the largest NHS trusts) in 202510, 11,12. By dividing the total IHC-related spending by the number of cases handled in the same period, we estimate the average cost to the NHS per IHC slide is approximately £5.82, equivalent to €6.64 using October 2025 exchange rates (fig. 2). Depending on the types of antibodies tested, this number can go up to £32.4 (€ 36.94).
For virtual staining, the cost per slide is reduced even further than with automated IHC staining, primarily due to the elimination of costly antibody reagents. Based on our internal dataset, virtually staining a Ki-67 biomarker slide from an H&E WSI costs approximately €0.1 per slide (staining cost alone), and this figure remains consistent at a per slide basis with additional biomarkers included. When factoring in other cost components (overhead, technician salary, consumables, depreciation, and maintenance fee) the total adjusted cost rises modestly to around €0.8 per slide. While actual costs may vary depending on local factors (e.g. local labour rates), this represents a substantial reduction, bringing the per-slide expense down to less than one-tenth of the cost of conventional IHC in France and the UK.
Discussion et conclusion
Globally, pathology services face an urgent workforce shortage, withover 4,000 additional pathologists projected to be needed in the US alone by 2037 with similar pattern reported in the UK, France and other major economies 12, 14. This gap coincides with a rising demand for IHC tests, driven by an aging population and an increase in structural alteration diseases like cancer. While digitalisation through LIS systems, slide scanners, and automated stainers has improved workflow efficiency and reduced per-slide costs, as reflected in the lower average cost in the UK compared to France, the IHC staining step remains a bottleneck due to its manual, resource-intensive nature.
AI-powered virtual staining offers a promising solution by reducing reagent usage, turnaround time, and labour requirements. It also improves consistency and reproducibility and aligns with healthcare sustainability goals. As proof-of-concept studies and early validations show strong potential, more attention must now turn toward robust clinical trials and standardised validation frameworks. For example, assessment metrics on image quality, pixel-level accuracy and structural similarity may be crucial for performance evaluation. Only then can virtual staining be integrated at scale, ensuring it delivers on its promise: to relieve mounting workloads while supporting precision pathology. With the reimbursement schemes in different regions, the application of virtual staining technology could alleviate the financial burden on the government in the long run.
In conclusion, IHC remains a cornerstone of disease diagnosis, but its rising demand has exposed clear limitations in cost and turnaround time. Typically, 1–3 days in French public hospitals, at costs of €5–30 (France) per slide compared to up to €36.94. Virtual staining can reduce this to under a minute per slide, at less than €1, offering a transformative leap in efficiency and affordability for pathologists and healthcare providers.
At RainPath, we are developing AI-driven virtual staining software to help pathologists save time, reduce costs, and focus on what truly matters, interpreting results for better patient outcomes. We welcome collaborations with academic and clinical partners interested in advancing this innovation.
References
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2. Coons AH, Creech HJ, Jones RN, Berliner E. The demonstration of pneumococcal antigen in tissues by the use of fluorescent antibody. J Immunol. 1942 Nov;45(3):159–170. doi:10.4049/jimmunol.45.3.159.
3. Rivenson Y, Wang H, Wei Z, et al. Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning. Nat Biomed Eng. 2019;3:466–477. doi:10.1038/s41551-019-0362-y.
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10. University Hospitals of North Midlands NHS Trust. FOI request ref 029-2021: Definitions – histopathology (including routine immunohistochemistry) [Internet]. Stafford: UHNM NHS Trust; 2020 May [cited 2025 Oct 29]. Available from: https://www.uhnm.nhs.uk/media/tmzc2mhu/20200518-foi-request-ref-029-2021-final-2-of-2.pdf
11. Đorđević M, Životić M, Radojević Škodrić S, Nešović Ostojić J, Marković Lipkovski J, Filipović J, et al. Effects of Automation on Sustainability of Immunohistochemistry Laboratory. Healthcare. 2021 July 8;9(7):866. doi: 10.3390/healthcare9070866
12. Walsh E, Orsi NM. The current troubled state of the global pathology workforce: a concise review. Diagn Pathol. 2024 Dec 21;19(1):163. doi: 10.1186/s13000-024-01590-2
13. Manchester University NHS Foundation Trust. What we spend [Internet]. Manchester: MFT; [cited 2025 Oct 31]. Available from: https://mft.nhs.uk/the-trust/other-departments/procurement-e-commerce-department/what-we-spend/
14. Medicus Healthcare Solutions. The shrinking pathologist workforce: What’s driving the shortage? [Internet]. Windham (NH): Medicus Healthcare Solutions; 2025 Sep 18 [cited 2025 Oct 29]. Available from: https://medicushcs.com/resources/the-shrinking-pathologist-workforce-whats-driving-the-shortage
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