AI in Oncology Market

The report "AI in Oncology Market by Player Type (Integrated Suite), Application (Drug Discovery, De Novo Drug Design, Diagnosis, Precision Medicine, Genomic), Technology (CNN, NLP), Cancer Type (Lung), End User (Hospitals, Pharma), & Region - Global Forecast to 2030", is expected to reach USD 11.52 billion by 2030, up from USD 2.45 billion in 2024, at a CAGR of 29.4 % from 2024 to 2030.

Browse 250 market data Tables and 50 Figures spread through 300 Pages and in-depth TOC on "AI in Oncology Market by Player Type (Integrated Suite), Application (Drug Discovery, De Novo Drug Design, Diagnosis, Precision Medicine, Genomic), Technology (CNN, NLP), Cancer Type (Lung), End User (Hospitals, Pharma), & Region - Global Forecast to 2030"
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The demand for AI oncology is driven by the rising demand for cost-effective solutions in cancer research and treatment development, specifically as healthcare expenses are rising and cancer biology is further becoming increasingly complex. Also, technological advancement in artificial intelligence is important to cater to the challenges faced in personalized medicine development based on individual patient data to improve outcomes and enhance the efficiency and speed of oncology-related applications, including tumor detection, drug discovery, and treatment planning.

Furthermore, by offering numerous benefits, artificial intelligence is significantly contributing to the simplification of clinical trial procedures. It facilitates effective patient recruitment, aids in trial design optimization, adverse event monitoring, regulatory compliance, and clinical documentation management, all of which contribute to the quicker and more effective development of cancer treatments and position the biotech industries for long-term growth and advancements in oncology care.

Healthcare providers segment accounted for the largest share of the AI in oncology market in 2023.

In the oncology AI market, healthcare providers account for the largest market share owing to their vital role in executing AI-driven solutions in a variety of clinical settings, such as hospitals, clinics, and diagnostic centers, among others. For instance, in February 2024, AIIMS New Delhi, collaborated with CDAC Pune to launch iOncology.ai, an AI-based platform to improve early cancer discovery initially focused on ovarian and breast cancer. The system employs advanced deep learning models to analyze complex medical data, including radiological and histopathological images, with high accuracy.

Moreover, in the areas of pathology, imaging, and precision oncology-aligned customized therapy planning, healthcare providers handle a substantial number of cancer cases which rely on AI to effectively handle complex tasks. They spend comparatively higher on cutting-edge technology to maintain their competitiveness and offer better patient care.

The development and adoption of AI in cancer is majorly driven by healthcare professionals, owing to collaboration with AI developers. For instance, October 2024, four US leading cancer diagnostic centers, Dana-Farber, Fred Hutch Cancer Center, Johns Hopkins, and Memorial Sloan Kettering merged with AI developers AWS, Microsoft, Deloitte, and NVIDIA to establish the Cancer AI Alliance (CAIA). Supported by USD 40 million in funding, CAIA leverage AI and advanced computing to analyze massive cancer datasets, enabling breakthroughs in treatment and research while maintaining strict data privacy.

The cloud segment accounted for the largest share in deployment mode of AI in oncology market.

Cloud segment accounts for the largest share in the deployment mode of the AI in oncology market owing to its due to its cost-effectiveness, unparalleled scalability, and ease of access. The  cloud platform provides high level security for managing sensitive healthcare data in compliance with regulatory standards. Furthermore, without requiring substantial investment on on-premise infrastructure, cloud-based AI solutions assist healthcare providers to use medical imaging devices, advanced analytics, and predictive models. Cloud deployment also enables collaboration between hospitals research centers and diagnostic facilities through seamless integration across various multiple locations.

For instance, in October 2024, Imagene AI, a leader in precision oncology, implemented Oracle Cloud Infrastructure (OCI) to enhance its AI-driven cancer research and treatment solutions. Its AI platform, including tools like LungOI for rapid cancer diagnosis and CanvOI, a cutting-edge Oncology Intelligence model, enables faster, more accurate diagnostics and supports pharmaceutical research and clinical trials.

Hence, such advancement in data management, and healthcare expertise are scaling precision medicine efforts globally, and positioning cloud deployment mode as dominant segment.

North America accounted for the largest share of the AI in oncology market in 2023.

North America holds the most significant share in AI in oncology market due to several factors including the region hosts several major pharmaceutical and biotechnology companies, which are extremely aggressive in their R&D activities to drive innovation in oncology. Further, North America has presence of top companies, academic institutions, and regulatory bodies that help to establish supportive ecosystem for the implementation and incorporation of AI in oncology technologies. For instance, in October 2024, researchers from Brigham and Women’s Hospital illustrated that an AI program precisely recognized and calculated 85% of aggressive prostate cancers in 732 patients’ s MRI scans. These AI-driven insights exceeded conventional approaches in predicting cancer spread and results, supporsting precision medicine and personalized treatment planning. Also, in October 2024, four US leading cancer centers, Dana-Farber, Fred Hutch Cancer Center, Johns Hopkins, and Memorial Sloan Kettering merged with AI leaders AWS, Microsoft, Deloitte, and NVIDIA to establish the Cancer AI Alliance (CAIA). Supported by USD 40 million in funding, CAIA will leverage AI and advanced computing to analyze massive cancer datasets, enabling breakthroughs in treatment and research while maintaining strict data privacy.

North America has massive financial resources and access to advanced technologies and the region highly focuses on precision medicine and customized therapies. Further, the need for smooth drug development processes amid pressure to adopt data-driven decision-making processes is a perfect catalyst for the market growth in North America. Thus, the aforementioned factors together work towards wholesome growth in AI in oncology applications, and this is the reason North America remains the strong leader in the market.

Prominent players in the AI in Oncology market include are Siemens Healthineers (Germany), GE Healthcare (US), ConcertAI (US), Medtronic (Ireland), F. Hoffmann-La Roche Ltd (Switzerland), Oracle(US), NVIDIA Corporation(US), Koninklijke Philips N.V. (Netherlands), PathAI, Inc. (US), CureMetrix, Inc. (US), Mindpeak GmbH (Germany), Paige AI, Inc. (US), Predictive Oncology (US), Exscientia (UK), Insilico Medicine (US), Iktos (Paris), Tempus (US), Azra AI (US), CureMatch, Inc. (US), OncoLens (US), Triomics (US), Clinakos. (US), Perthera, Inc (US), Cellworks Group, Inc. (US), and biomy, Inc. (Japan).

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