Coherent Market Insights has recently published a report, titled, Artificial Intelligence in Oncology Market, By Component (Software/Platform, Hardware, Services), By Cancer Type (Breast Cancer, Lung Cancer, Prostate Cancer, Colorectal Cancer, Brain Tumor, and Others), By Treatment Type (Chemotherapy, Radiotherapy, Immunotherapy, and Others), By End User: ): Global Opportunity Analysis and Industry Forecast, 2024-2031”. According to the report, the global artificial intelligence in oncology market generated $1.2 billion in 2023, and is anticipated to generate $9.16 billion by 2031, witnessing a CAGR of 33.7% from 2024 to 2031.
Increasing organic growth strategies, such as product launches by key market players, are expected to drive market growth over the forecast period. For instance, on October 27, 2023, Koninklijke Philips N.V., a Netherlands-based multinational health technology company, announced that it had launched a new AI-based imaging and reporting tool for early detection of prostate cancer.
Increasing Prevalence of Cancer Worldwide
The increasing prevalence of various types of cancers such as lung cancer, breast cancer, prostate cancer, skin cancer, leukemia, etc. is one of the major drivers of the artificial intelligence in oncology market. As per estimates by the World Health Organization, cancer burden has risen exponentially and nearly 20 million new cancer cases are reported worldwide every year. Advancements in medical technologies have improved diagnosis and treatment, but this rise in cancer incidence has also increased the workload of oncologists and healthcare professionals. AI tools that can efficiently analyze huge amounts of medical data help improve diagnosis and optimize treatment plans. This reduces workload and healthcare costs.
Growing Adoption of Precision Medicine Approaches
Precision medicine or personalized medicine approaches aim to tailor medical treatment to individual characteristics, risks and responsiveness to therapies. Various machine learning and deep learning algorithms used for cancer screening and analysis can analyze complex genomic and molecular signatures from tumor samples and provide insights on optimal diagnostic and therapeutic approaches for each patient. This promises more effective targeting of cancers and better clinical outcomes. Growing research and development activities in precision oncology are driving increased demand for cutting-edge AI technologies.
Market of Key Takeaways
The global artificial intelligence in oncology market is expected to exhibit a CAGR 33.7% during the forecast period. The merger with emerging economies offers lucrative growth opportunities for players in the global artificial intelligence in oncology market. Moreover, the increasing prevalence of cancer is also expected to drive the market growth. For instance, according to the data published by the European Commission, a part of the executive of the European Union, in May 2023, there were more than 69,697 new cases of breast cancer in Germany in 2022.
Among regions, North America segment is expected to be dominant in the global artificial intelligence in oncology market, owing to the presence of major players such as IBM Corporation, Siemens Healthineers AG, Intel Corporation, GE HealthCare, and other key market players contributing to growth in this region. Major players operating in the global artificial intelligence in oncology market include Azra AI, IBM Corporation, Siemens Healthineers AG, Intel Corporation, GE HealthCare, NVIDIA Corporation, Digital Diagnostics Inc., ConcertAI, Median Technologies, PathAI, Microsoft, Zebra Medical Vision, and Babylon
Market Key Developments
On September 7, 2023, Microsoft Corporation, a U.S.-based multinational technology corporation, announced that it had collaborated with Paige AI, Inc., a company involved in providing generative AI for pathology, to create the world’s largest image-based artificial intelligence (AI) models for digital pathology and oncology.
In October 2022, Model Medicines, a pharmatech company, announced the launch of Galileo, an AI-based drug discovery platform that can be used for both drug discovery for hematological diseases and solid tumors.
The artificial intelligence in oncology market is expected to witness significant growth over the forecast period, owing to the increasing adoption of AI for cancer diagnosis and treatment. AI improves diagnostic accuracy by analyzing large datasets to identify patterns beyond human capabilities. It also helps in optimizing treatment plans by predicting patient outcomes and selecting the most effective therapies for individuals. Additionally, AI assists in drug discovery and precision medicine development by analyzing molecular datasets to identify new targets and biomarkers. These advantages of AI are contributing to the growing demand from hospitals and research institutions.
Currently, artificial intelligence finds greatest use in assisting radiologists in medical imaging analysis for cancer screening and improved diagnosis. However, its applications are gradually expanding beyond diagnosis to other areas of oncology such as cancer research, drug discovery and development, optimizing treatment plans, monitoring treatment response and facilitating precision medicine approaches. Advanced applications leveraging technologies like machine learning, deep learning and cognitive computing are being explored for streamlining clinical trials, expediting discovery of new therapies and developing targeted drug regimens. The multifaceted opportunities available across the oncology workflow present a massive potential for AI vendors.
There is an emerging trend of increased adoption of cloud-based AI solutions in the oncology market. Cloud models allow healthcare organizations easy access to sophisticated AI tools without huge upfront capital investments or need to maintain dedicated IT infrastructure. Cloud solutions particularly benefit small clinics and hospitals with limited budgets. Vendors are also shifting to cloud-based offerings as these provide opportunities for recurring revenues through software licensing or pay-per-use models. This is accelerating the implementation of AI technologies as buyers find cloud deployments more convenient and cost-effective. Several AI-powered medical imaging analytics and precision oncology support platforms are now available through popular cloud models.
While technological advancements have made AI more accessible, developing sophisticated AI algorithms and solutions optimized for medical imaging analysis and precision oncology applications still require huge investments. Significant financial resources are needed for hardware, analytical software tools, neural network development, data storage infrastructure, and hiring talented data scientists and oncologists. Accessing large annotated medical imaging datasets also involves costs. These high capital requirements pose a challenge, especially for early-stage and smaller companies. Several startups may find it difficult to raise funds, which restrains market growth.
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