(EMAILWIRE.COM, December 13, 2024 ) The global AI in Oncology Market is forecasted to grow steadily from US$1.92 billion in 2023 to US$2.45 billion in 2024, ultimately reaching an impressive US$11.52 billion by 2030, driven by a robust CAGR of 29.4%. The AI in oncology market is experiencing significant growth due to rising investments in the pharmaceutical and biotech companies to develop potential and advance cancer drugs to reduce the growing cancer burden worldwide. AI helps to streamline such drug discovery as well as drug development processes by offering predictive modeling, simulation techniques, and advanced data analysis, which make it easier to evaluate a drugs safety and efficacy. This reduces drug discovery time and costs as it helps the user minimize the experimental work and optimize the clinical trial design.
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Global AI in Oncology Market Dynamics
DRIVER: Prevalence of cancer disease
The high global incidence of cancer creates urgency in finding more effective, efficient, and personalized diagnostic and treatment options. The number of cancer patients is galloping against the healthcare industry because most of these patients are aged, creating a proportional increase in demand for treatment. According to the World Health Organization (WHO)’s cancer agency, the International Agency for Research on Cancer (IARC), in 2022, there were an estimated 20 million new cancer cases and 9.7 million cancer-related deaths globally. In the year 2022, lung cancer emerged as the most prevalent cancer, at 12.4% of all diagnoses. Female breast cancer was in second place, with 11.6% of the total. Third place was taken by colorectal cancer, at 9.6% of all diagnoses. Prostate cancer represented 7.3%, whereas stomach cancer accounted for 4.9% of all new cases of cancer. As cancer rates rise, Al’s ability to process data and tailor therapies will be vital in advancing personalized medicine and supporting healthcare systems.
RESTRAINT: High initial costs
High initial costs are one of the major hindrances to the adoption of AI in the oncology market due to development, data acquisition, and regulatory approval charges. According to the FDA, the costs of regulatory processes can be substantial. For instance, the 510(k) pre-market notification process costs about 24,335 USD, while the PMA process for class III devices costs up to 540,783 USD. Regulatory costs for the De Novo Classification Request, which is required for new devices with no analog, are USD 162,235. Such regulatory costs, therefore, are very high for small to medium AI startups, which would already require a lot of money for research data collection and clinical trials. Apart from these costs, developing oncology AI solutions is very cost-intensive. Data acquisition to train the AI models is expensive and time consuming. It might take more than USD 1 million annually for a single dataset.
OPPORTUNITY: Increasing focus on personalized treatment plans
Cancer is a complex disease; AI is transforming oncology by allowing more personalized approaches to treatment. Analyzing individual patient characteristics, which include genetic profiles, tumor mutations, and clinical information, helps clinicians find tailored therapies that optimize treatment outcomes. This approach, particularly for therapies like immunotherapy, aims to reduce unnecessary side effects and improve patient responses. Unlike the traditional one-size-fits-all model, AI tools can predict how patients will respond to specific treatments. Many firms are acting very decisively in AI-related cancer care. In October 2024, Ataraxis AI launched its availability for Ataraxis Breast – a prognostic and predictive tool for breast cancer that is 30 percent more accurate than standards at the moment.
CHALLENGES: Limited Availability of Datasets
The limited availability of datasets remains a significant challenge in the AI-driven oncology market, particularly due to data privacy and protection regulations. HIPAA, for example, focuses on ensuring that peoples health information remains confidential, secure, and accessible only to authorized individuals. Similarly, GDPR provides broader protections for all personal data of EU residents, including health-related information. These regulations necessitate careful management of data privacy, and non-compliance can result in significant penalties of up to USD 21 million (20 million) or 4% of global revenue under GDPR and up to USD 2 million for severe violations of HIPAA.
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North America accounted for the largest share of the AI in Oncology market in 2023.
The AI in oncology market is segmented into North America, Europe, Asia Pacific, Latin America, and the Middle East & Africa. In 2023, North America accounted for the highest share of the AI in oncology market. The large share of the region is led by the strong presence of companies providing AI in oncology solutions in the region, especially in US. Major US-based companies such as GE Healthcare, ConcertAI, Oracle, NVIDIA Corp, Predictive Oncology, PathAI and CureMatrix dominate the AI in oncology market. Further growth in the field is fueled by the ongoing advancements in the field of machine learning and deep learning. Along with rising accessibility of diverse health care data and increasing demand for precision medicine, these factors contributed to this growth. Collaborations in AI-based oncology play the most important role in creating a boost in demand and innovation in the region. For example, in April 2024, Moffitt Cancer Center joined forces with NVIDIA, Oracle, and Deloitte to reimagine cancer care using advanced AI and machine learning. The team is refining a large language model to ingest 100,000 clinical notes coming from Moffitt to crack some of the key operational bottlenecks through better billing and coding processes for cancer treatments and related conditions.
Recent Developments of AI in Oncology Market
-In October 2024, GE HealthCare announced the launch of its new cloud-first application CareIntellect for Oncology. This application combines multi-modal patient data from various systems into a unified view, which leverages generative AI to summarize clinical notes and reports.
-In September 2024, F. Hoffmann-La Roche Ltd announced a collaboration with Qritive enhancing cancer diagnostics and treatment, and the adoption of AI among pathologists. This collaboration will enable Qritives AI-powered solutions to fully integrated with Roches navify Digital Pathology platform which will help pathologists diagnose cancer more accurately and efficiently.
-In September 2024, Oracle announced a partnership with Imagene AI Ltd. to introduce CanvOI, an advanced pan-cancer foundation model aimed at supporting innovative research and development in digital pathology and oncology.
-In June 2024, ConcertAI announced a collaboration with NVIDIA Corporation (US) to enhance translational and clinical development solutions within its CARA AI platform. ConcertAI will leverage NVIDIA’s AI expertise and infrastructure which includes the Meta Llama 3 NIM in order to enhance oncology research and treatment through advanced LLM workloads.
-In June 2024, Predictive Oncology announced the launch of a unique 3D cell culture model to advance cancer drug discovery, offering more accurate in vivo testing and better predictions for clinical outcomes and drug candidate selection.
-In May 2024, ConcertAI launched CARA AI, a platform that integrates multi-modal data management, predictive AI, and generative AI to streamline and enhance healthcare processes. The platform supports life sciences and healthcare professionals in exploring multi-modal real-world data (RWD) while utilizing AI-driven workflows.
