Artificial Intelligence In Oncology Market Forecasts to 2030 – Global Analysis By Component (Hardware, Services and Software Solutions), Cancer Type (Lung Cancer , Colorectal Cancer, Breast Cancer, Brain Tumor, Prostate Cancer and Other Cancer Types), Tre

Artificial Intelligence In Oncology Market Forecasts to 2030 – Global Analysis By Component (Hardware, Services and Software Solutions), Cancer Type (Lung Cancer , Colorectal Cancer, Breast Cancer, Brain Tumor, Prostate Cancer and Other Cancer Types), Treatment Type, Application, End User and By Geography

According to Stratistics MRC, the Global Artificial Intelligence in Oncology Market is accounted for $1124.7 million in 2023 and is expected to reach $5727.9 million by 2030 growing at a CAGR of 26.2% during the forecast period. Oncology uses artificial intelligence (AI) to diagnose cancer more quickly and accurately, which improves patient outcomes. AI uses computer programs that examine enormous volumes of data to predict cancer. AI applications in oncology may enhance cancer detection, diagnosis, and therapy planning. AI is reshaping the current scenario of oncology by combining the massive amounts of data generated by multi-omics analyses with recent advances in deep learning and high-performance computing strategies.

According to WHO statistics, approximately 2.3 million people worldwide will be screened for breast cancer in 2020.

Market Dynamics

Driver

Potential of precision medicine

The adoption of AI in the oncology market has been significantly fuelled by the development of precision medicine as a promising oncology strategy. Based on each patient's specific features, including genetic make-up, lifestyle choices, and impacts from the environment, precision medicine tries to customise medical treatments for them. Additionally, this method acknowledges that every patient's cancer is unique and that various treatment approaches may have varied effects on it. It enhances the precision of cancer classification and diagnosis. AI systems can discover certain genetic variations or mutations that are indicative of particular cancer kinds or subtypes by analysing genomic data which enhances the market growth.

Restraint

Data quality

Adoption of AI in the cancer market is severely constrained by the quality of the data. Large volumes of high-quality data are needed in oncology to properly train AI algorithms and create precise predictive models. However, acquiring such information can be difficult for a number of reasons. Oncology data is frequently dispersed across numerous hospitals, clinics, research facilities, and healthcare systems. Potential differences in data formats, codes, and data gathering techniques, integrating data from many sources can be a challenging undertaking. The capacity to build extensive databases that include a variety of patient groups, cancer types, and treatment treatments is hampered by this fragmentation.

Opportunity

Rising cancer burden

The global increase in cancer incidence has a significant impact on the adoption of AI in oncology market. By aiding with early detection, diagnosis, treatment planning, and monitoring, AI has the potential to improve cancer patient outcomes and survival rates. Cancer continues to be an issue for global health due to its rising incidence and mortality rates. Additionally, with the complexity of cancer diagnosis and therapy and the increasing number of patient data, oncologists increasingly need sophisticated tools to assist them in making more accurate and personalised treatment decisions.

Threat

Cost and infrastructure

Significant investments are required in a number of areas before AI technologies may be implemented in healthcare settings, including oncology. It costs money to build the infrastructure of hardware and software necessary to support AI applications. High-performance servers, GPUs (Graphics Processing Units), and storage systems are frequently needed for AI algorithms. Particularly for smaller healthcare facilities with limited resources, these infrastructure components can be expensive to purchase and maintain. Furthermore, it can be difficult to integrate AI technology into the infrastructure and operations used in healthcare settings nowadays. The smooth incorporation of AI tools into oncology practices can be hampered by legacy systems, interoperability issues, and a lack of standardisation hampers the market growth.

Covid-19 Impact

The coronavirus helped AI detect cancer. Applications of AI and machine learning helped to lighten the workload of healthcare and medical facilities. With the growth of the sector, numerous global IT behemoths have stepped up to develop AI tools and software that identify the coronavirus, which will eventually support the growth of cancer diagnosis facilities. The paucity of medical professionals caused by the rising coronavirus cases drives the adoption of AI tools for better patient assistance and better outcomes.

The chemotherapy segment is expected to be the largest during the forecast period

The chemotherapy segment is estimated to hold the largest share. The chemotherapy-based therapy involves the use of chemical molecules that kill quickly proliferating cancer cells. A unique digital profile of each patient can be created with the help of AI when it comes to chemotherapy treatment, allowing doctors to adjust the patient's dose properly. The expansion of research efforts to use AI in chemotherapy has sped up segment growth. A personalised digital profile of each patient can be created with the help of AI when it comes to chemotherapy treatment, enabling doctors to modify the patient's dose accordingly. The expansion of research efforts to use AI in chemotherapy has sped up segment growth.

The software solutions segment is expected to have the highest CAGR during the forecast period

The software solutions segment is anticipated to have lucrative growth during the forecast period. AI-enabled software solutions have the potential to improve a number of elements of cancer care, including the diagnosis, planning, and monitoring of treatments. These software solutions allow advanced data analytics and machine learning to extract analytical information and enhance healthcare professionals' decision-making. Furthermore, these systems can produce prediction models to direct treatment decisions by combining patient-specific data, such as genetic data, treatment histories, and clinical results. AI software solutions can also help in the monitoring of disease development and therapy responses. Overall, AI-powered software solutions have the capacity to transform cancer treatment through improving clinical decision-making, enhancing patient outcomes, and expediting oncology-related research and development initiatives.

Region with largest share

North America commanded the largest market share during the extrapolated period due to the presence of well-developed digital infrastructure, favourable regulatory and reimbursement policies, and rising government initiatives to boost the adoption of AI technology in the healthcare industry. The increasing incidence of various cancers is fueling the demand for improved therapies and diagnostics, which is further encouraging regional market expansion.

Region with highest CAGR

Europe is expected to witness profitable growth over the projection period. European nations with strong health systems and research institutions, such as Germany, France, and Great Britain, have made significant contributions to the development and use of artificial intelligence techniques in cancer therapy research and care. As a result, Europe has also seen major developments in oncology research and treatment. The improvement of care delivery and the improvement of precision cancer therapy outcomes for a specific patient population are the main areas of focus for the implementation of these strategies in clinical settings.

Key players in the market

Some of the key players in the Artificial Intelligence In Oncology Market include Concert AI, CancerCenter.AI, Median Technologies, IBM Watson Health, Berg, GE Healthcare, LK Inspection, Path AI, Owkin, Inc., Roche Diagnostics, Azra AI, Intel, Siemens Healthineers, Digital Diagnostics Inc. and NVIDIA.

Key Developments

In July 2023, Path AI launched AIM-HER2 Breast Cancer, an Artificial Intelligence-Powered HER2 Scoring Algorithm that can be utilized by biopharma research and clinical labs.

In June 2023, GE Healthcare has announced collaboration with RaySearch Laboratories AB (publ), a prominent provider of radiation oncology software, to create a new radiation therapy simulation and treatment planning workflow solution that would simplify how radiation is targeted to decrease a tumour.

In September 2021, Owkin, Inc., in collaboration with Cleveland Clinic researchers, announced the development of a deep-learning model that predicts survival and health outcomes for hepato cellular carcinoma.

Components Covered
• Hardware
• Services
• Software Solutions

Cancer Types Covered
• Lung Cancer
• Colorectal Cancer
• Breast Cancer
• Brain Tumor
• Prostate Cancer
• Other Cancer Types

Treatment Types Covered
• Chemotherapy
• Immunotherapy
• Radiotherapy
• Other Treatment Types

Applications Covered
• Cancer Detection
• Drug Development
• Drug Discovery
• Other Applications

End Users Covered
• Diagnostic Centers
• Hospitals
• Pharmaceutical Companies
• Research Institutes
• Other End Users

Regions Covered
• North America
US
Canada
Mexico
• Europe
Germany
UK
Italy
France
Spain
Rest of Europe
• Asia Pacific
Japan
China
India
Australia
New Zealand
South Korea
Rest of Asia Pacific
• South America
Argentina
Brazil
Chile
Rest of South America
• Middle East & Africa
Saudi Arabia
UAE
Qatar
South Africa
Rest of Middle East & Africa

What our report offers
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2021, 2022, 2023, 2026, and 2030
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements