PUBLISHER: Grand View Research | PRODUCT CODE: 1726194
PUBLISHER: Grand View Research | PRODUCT CODE: 1726194
The global computational pathology market size is expected to reach USD 1.04 billion by 2030, registering a CAGR of 8.24% from 2025 to 2030, according to a new report by Grand View Research, Inc. This growth can be attributed to the rising prevalence of chronic diseases, the increasing demand for advanced solutions for faster diagnosis, the rising integration of Machine Learning (ML) and artificial intelligence (AI) technologies and increasing investment in healthcare supported by market players focused on developing advanced solutions.
Integrating artificial intelligence (AI) and machine learning (ML) algorithms into digital pathology workflows is revolutionizing the field, enabling faster and more accurate analysis of pathology images. AI-powered tools can assist pathologists in detecting patterns, predicting disease progression, and giving clinically relevant insights crucial for disease detection. For instance, In September 2024, Paige introduced Paige Alba, a clinical-grade multimodal co-pilot aimed at transforming personalized medicine and precision oncology. Alba provides real-time, AI-driven insights from patient data, enhancing clinical decision-making at unprecedented speed and scale. This innovation represents a major leap toward Artificial General Intelligence (AGI) in healthcare, bringing the industry closer to a future where AI not only supports but collaborates with clinicians in diagnosing and treating complex diseases such as cancer.
Several companies operating in the market also focusing on developing innovative solutions to enhance the application and performance of computational pathology. For instance, in August 2023, Microsoft and Paige researchers developed Virchow2 and Virchow2G, second-generation foundation models for computational pathology. These large language models are trained on vast amounts of pathology data to understand the complex relationships between clinical information, pathology findings, and disease outcomes.
Virchow2 and Virchow2G can generate human-readable text, answer questions, and assist in tasks like report generation and case summarization. The models are designed to be fine-tuned for specific tasks, enabling their use in various computational pathology applications. This advancement represents a significant step forward in leveraging AI to enhance pathologists' decision-making and improve patient care in computational pathology. Similarly, transitioning from traditional microscopy to digital pathology further contributes to the market growth. This shift enhances accessibility and facilitates remote consultations and collaborative efforts among pathologists worldwide.
The COVID-19 pandemic has accelerated this trend as healthcare systems search for alternatives to execute operations while ensuring compliance with safety protocols. Furthermore, regulatory bodies significantly contribute to digital pathology's growth, leading to approvals for various digital imaging systems and software applications. As organizations invest in infrastructure to support digital workflows, the market is expected to witness significant growth driven by enhanced operational efficiencies and improved diagnostic capabilities.