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The digital pathology market is estimated to be worth $0.7 billion in 2022 and is expected to grow at a CAGR of 8.3% during the forecast period. Pathology is a subfield of medical science that primarily focuses on the nature, genesis and cause of a disease. Further, pathology forms an essential component of diagnostic pathways established for multiple disease indications, especially cancer detection. In fact, 70-80% of the total healthcare decisions involved in either diagnosis or treatment of ailments require a pathological assessment. Further, according to the International Agency for Research on Cancer (IARC), by 2040, 27 million new cancer cases are expected to be reported annually. This rise in cancer cases, coupled to the rapidly ageing global population, is expected to lead to a substantial increase in the pathology workload. However, as the demand for professional pathologists continues to increase, the number of active pathologists in the field is diminishing over time. As per a recent study, a 30% decline in the number of active pathologists is expected to be observed by 2030, as compared to the number of such professionals in 2010. Moreover, 63.2% of the currently active pathologists are anticipated to retire in the next 10 years. Furthermore, it is projected that a substantial disparity (close to 30%) between the expected demand for pathology services and supply of pathologists is likely to be witnessed by the year 2030.
Amidst the ever-growing demand for pathology services, the simultaneous use of technological advances to automate and digitize healthcare procedures is growing. These developments have accelerated research and clinical diagnosis, as well as enhanced patient outcomes, in the recent years. Specifically, AI-powered digital imaging is one such technology, which has revolutionized the pathology industry by enabling high-throughput scanning of patient samples. To provide more context, AI-based digital pathology / AI pathology involves collection, management, analyzing and sharing of data (via digital slides) in a digital setting. Through this process, digital slides are created by scanning conventional glass slides with a scanning device, which may be seen on a computer screen or a mobile device and offer a high-resolution digital image. Further, AI pathology technique presents a viable solution to managing the growing pathology workload, while also ensuring more rapid and consistent diagnostic services and research activities. Moreover, AI-powered digital pathology solutions (digital pathology scanners and digital pathology software) allow pathologists to examine more cases and offer a precise diagnosis. It is worth highlighting that digitized workflows can speed up processing times, lower administrative errors, enable remote collaboration and boost productivity, thereby, allowing significant cost savings. Experts believe that there has been a significant rise in the revenue generation potential within digital pathology market. This is further supported by the significant investments being made in this industry. Since 2016, funding received by digital pathology firms have surpassed USD 1.6 billion, with majority of amount being raised in the year 2021. Additionally, it is worth highlighting that in September 2023, 3DHISTECH and Epredia have collaborated to launch a pathology innovation incubator aimed at speeding up progress in cancer diagnostics. Considering the rising popularity and demand for such solutions in the healthcare and research industry, and the ongoing efforts of AI-based digital pathology companies to further improve / expand their respective portfolios, we believe that the AI-based digital pathology market is likely to witness a steady market growth, during the forecast period.
Examples of key AI-based digital pathology companies engaged in digital pathology market (which have also been profiled in this market report; the complete list of AI-based digital pathology companies is available in the full report) include Aiforia Technologies, Akoya Biosciences, Ibex Medical Analytics, Indica Labs, Paige, PathAI, PROSCIA, Roche Tissue Diagnostics and Visiopharm. This market report includes an easily searchable excel database of all the AI-based digital pathology companies, worldwide.
Several recent developments have taken place in the field of digital pathology market. We have outlined some of these recent initiatives below. These developments, even if they took place post the release of our market report, substantiate the overall market trends that have been outlined in our analysis.
The “AI-based Digital Pathology Market by Type of Neural Network (Artificial Neural Network, Convolutional Neural Network, Fully Convolutional Network, Recurrent Neural Network and Other Neural Networks), Type of Assay (ER Assay, HER2 Assay, Ki67 Assay, PD-L1 Assay, PR Assay and Other Type of Assays), Type of End-user (Academic Institutions, Hospitals / Healthcare Institutions, Laboratories / Diagnostic Institutions, Research Institutes and Other End-users), Area of Application (Diagnostics, Research and Other Areas of Application), Target Disease Indication (Breast Cancer, Colorectal Cancer, Cervical Cancer, Gastrointestinal Cancer, Lung Cancer, Prostate Cancer and Other Indications) and Key Geographies (North America, Europe, Asia, Latin America, Middle East and North Africa and Rest of the World): Industry Trends and Global Forecasts, 2022-2035” market report features an extensive study of the current market landscape, market size, market forecast and future opportunities for the AI-based digital pathology market. The market research report features an in-depth analysis, highlighting the capabilities of various stakeholders engaged in providing AI-based digital pathology.
Amongst other elements, the market research report features:
The key objective of this market report is to provide a detailed market forecast analysis in order to estimate the existing market size and future opportunity for AI-based digital pathology market in the short to mid-term and long term, over the forecast period 2022-2035. Further, the year-wise projections of the current and future opportunity have been segmented based on several relevant parameters, such as type of neural network (artificial neural network, convolutional neural network, fully convolutional network, recurrent neural network and other neural networks), type of assay (ER assay, HER2 assay, Ki67 assay, PD-L1 assay, PR assay and other type of assays), type of end-user (academic institutions, hospitals / healthcare institutions, laboratories / diagnostic institutions, research institutes and other end-users), area of application (diagnostics, research and other areas of application), target disease indication (breast cancer, colorectal cancer, cervical cancer, gastrointestinal cancer, lung cancer, prostate cancer and other indications) and key geographies (North America, Europe, Asia, Latin America, Middle East and North Africa and Rest of the World). In order to account for future uncertainties and to add robustness to our model, we have provided three market forecast scenarios, namely conservative, base and optimistic scenarios, which represent different tracks of the industry’s growth.
All actual figures have been sourced and analyzed from publicly available information forums. Financial figures mentioned in this market report are in USD, unless otherwise specified.