Emergence of big data analytics resource systems (BDARSs) as a part of routine practice in Radiation Oncology is on the horizon. Gradually, individual researchers, vendors, and professional societies are leading initiatives to create and demonstrate use of automated systems. What are the implications for design of clinical trials, as these systems emerge? Gold standard, randomized controlled trials (RCTs) have high internal validity for the patients and settings fitting constraints of the trial, but also have limitations including: reproducibility, generalizability to routine practice, infrequent external validation, selection bias, characterization of confounding factors, ethics, and use for rare events. BDARS present opportunities to augment and extend RCTs. Preliminary modeling using single- and muti-institutional BDARS may lead to better design and less cost. Standardizations in data elements, clinical processes, and nomenclatures used to decrease variability and increase veracity needed for automation and multi-institutional data pooling in BDARS also support ability to add clinical validation phases to clinical trial design and increase participation. However, volume and variety in BDARS present other technical, policy, and conceptual challenges including applicable statistical concepts, cloud-based technologies. In this summary, we will examine both the opportunities and the challenges for use of big data in design of clinical trials.

Oncology Precision Medicine Software Market Outlook

According to our latest research, the global Oncology Precision Medicine Software market size in 2024 is valued at USD 2.18 billion, with a robust compound annual growth rate (CAGR) of 13.7% projected through the forecast period. By 2033, the market is expected to reach approximately USD 6.48 billion, driven by the exponential integration of genomics, artificial intelligence, and data analytics in oncology care. This remarkable growth trajectory is primarily fueled by the increasing adoption of precision medicine approaches to cancer treatment, the growing availability of next-generation sequencing technologies, and the pressing need for software solutions that can manage, analyze, and interpret vast amounts of oncological and genomic data for personalized patient care.

A significant growth factor for the Oncology Precision Medicine Software market is the rapid advancement in genomic sequencing technologies and the consequent reduction in sequencing costs. As the price of sequencing a human genome continues to drop, hospitals, research centers, and diagnostic laboratories are increasingly utilizing genomic data to inform cancer diagnosis and treatment. This surge in genomic data generation necessitates sophisticated software platforms capable of integrating multi-omics data, interpreting complex genetic variants, and supporting clinical decision-making. The demand for oncology precision medicine software is further amplified by the rise in targeted therapies and immunotherapies, both of which require a nuanced understanding of individual patient profiles for optimal treatment selection and monitoring.

Another pivotal driver is the growing emphasis on real-world evidence (RWE) and big data analytics in oncology. Healthcare providers and pharmaceutical companies are leveraging vast datasets from electronic health records, clinical trials, and patient registries to identify novel biomarkers, predict treatment responses, and optimize clinical pathways. Oncology precision medicine software platforms play a critical role in aggregating, harmonizing, and analyzing these data sources, enabling clinicians to deliver evidence-based, personalized care. Furthermore, the integration of artificial intelligence and machine learning algorithms into these platforms enhances their predictive capabilities, supporting the identification of actionable mutations and facilitating the development of individualized treatment regimens.

The increasing prevalence of cancer worldwide and the shift towards value-based healthcare models are also catalyzing the adoption of precision medicine software in oncology. As cancer incidence rates rise, healthcare systems are under mounting pressure to improve patient outcomes while controlling costs. Precision medicine software solutions help address this challenge by enabling risk stratification, optimizing resource allocation, and minimizing trial-and-error approaches in cancer therapy. Governments and regulatory bodies are also playing a supportive role by promoting initiatives that encourage the adoption of digital health technologies, including precision medicine platforms, thereby fostering a conducive environment for market growth.

Regionally, North America remains the dominant market for oncology precision medicine software, accounting for the largest revenue share in 2024. This leadership is attributed to the presence of leading technology vendors, a highly developed healthcare infrastructure, and significant investments in cancer research and genomics. Europe follows closely, benefiting from strong government support for personalized medicine initiatives and robust collaborations between academia, industry, and healthcare providers. The Asia Pacific region is emerging as a high-growth market, propelled by increasing healthcare expenditure, expanding access to advanced diagnostics, and rising awareness of precision oncology. Latin America and the Middle East & Africa, while currently representing smaller shares, are expected to witness accelerated growth as healthcare systems modernize and digital transformation initiatives gain momentum.

Using Excel Data Analysis Tools and BigML Machine Learning platform, we tested correlation between biopsy data for breast cancer and created a model which helps to distinguish between benign and malignant tumors. Data set of oncology patients were used to analyze links between 10 indicators collected by biopsy non- cancerous and cancerous tumours. Created model can be used as a future medical science tool and can be available to specially trained histology nurses in rural areas. Developed model that can be used to detect cancer on early stages is especially important in the view of the fact that detecting cancer at stage IV give patients of about 22% of survival rate 1.

AI Immuno-Oncology Trial-Match Platforms Market Outlook

As per our latest research, the AI Immuno-Oncology Trial-Match Platforms market size reached USD 1.42 billion in 2024, reflecting the rapid integration of artificial intelligence in oncology clinical trials. The market is expected to grow at a robust CAGR of 17.6% from 2025 to 2033, which will propel the market to a forecasted value of USD 6.18 billion by 2033. This significant growth is primarily driven by the surging demand for precision medicine, increasing complexity of immuno-oncology trials, and the urgent need to accelerate patient recruitment and optimize trial outcomes globally. The market is witnessing rapid adoption across major healthcare systems, pharmaceutical companies, and research institutes, marking a new era in oncology research and treatment personalization.

The primary growth factor for the AI Immuno-Oncology Trial-Match Platforms market is the increasing prevalence of cancer worldwide, coupled with the evolution of immuno-oncology therapies that require highly specific patient populations for clinical trials. Traditional methods of patient recruitment and trial matching are often time-consuming, error-prone, and inefficient, leading to delays in drug development and higher costs. AI-driven platforms streamline these processes by leveraging advanced algorithms, natural language processing, and big data analytics to match eligible patients with appropriate trials in real-time. This not only accelerates the recruitment process but also enhances the likelihood of successful trial outcomes, which is critical for both patients and sponsors. As cancer treatment becomes increasingly personalized, AI platforms are emerging as indispensable tools for bridging the gap between complex trial protocols and diverse patient populations.

Another key driver is the growing investment by pharmaceutical and biotechnology companies in AI-enabled solutions to optimize clinical trial operations. The competitive landscape of drug development, particularly in the immuno-oncology segment, necessitates rapid and efficient patient enrollment to maintain timelines and regulatory compliance. AI Immuno-Oncology Trial-Match Platforms provide automated, scalable, and cost-effective solutions for identifying suitable candidates from vast pools of electronic health records, genomic data, and real-world evidence. These platforms not only reduce manual workload but also minimize selection bias, improve data quality, and enable adaptive trial designs. The integration of AI with electronic medical records and clinical trial management systems is further enhancing interoperability and data-driven decision-making, fostering a culture of innovation and agility within the industry.

Regulatory support and collaborative initiatives among healthcare providers, technology vendors, and academic research institutes are further fueling market expansion. Governments and regulatory bodies in regions such as North America and Europe are actively promoting the use of AI in clinical trials to address the challenges of low participation rates and underrepresentation of minority groups. Additionally, several public-private partnerships and consortia are being formed to standardize data sharing, develop ethical guidelines, and ensure patient privacy. This collaborative ecosystem is encouraging the adoption of AI Immuno-Oncology Trial-Match Platforms across various end-users, including hospitals, clinics, and research centers. As the regulatory landscape continues to evolve, these platforms are expected to play a pivotal role in shaping the future of precision oncology and advancing global cancer research.

Regionally, North America dominates the AI Immuno-Oncology Trial-Match Platforms market owing to its advanced healthcare infrastructure, high adoption of digital health technologies, and strong presence of leading pharmaceutical and biotechnology companies. The United States, in particular, is at the forefront of AI integration in clinical trials, driven by robust funding, favorable reimbursement policies, and active participation from academic medical centers. Europe follows closely, with increasing investments in digital health and collaborative research networks. The Asia Pacific region is witnessing the fastest growth, propelled by rising cancer incidence, expanding healthcare access, and growing awareness of clinical trial opportunities. Latin America and the Middle East & Africa are gradually embracing these platforms, supported by international col

Introduction

Global Precision Oncology Market size is expected to be worth around USD 202.5 Billion by 2032 from USD 89.3 Billion in 2023, growing at a CAGR of 9.8% during the forecast period from 2024 to 2032.

Precision medicine represents a transformative approach to healthcare, focusing on customizing medical treatment to individual patient profiles, particularly in oncology. This field combines advances in biotechnology, digital healthcare, and substantial public investment to evolve personalized therapies for diseases like cancer. Precision oncology, a primary subset of precision medicine, aims to match each cancer patient with the most effective treatment based on their unique genetic makeup, enhancing treatment efficacy and patient outcomes.

The precision oncology market is poised for significant growth, driven by increasing demand for personalized cancer treatments. Such treatments not only empower patients with better information but also increase their engagement and control over their health decisions. This, in turn, leads to better health outcomes, improved revenues for healthcare providers, and enhanced relationships between patients and therapists. The integration of AI, big data analytics, and digital health technologies is expected to further enhance these outcomes and accelerate the pace of drug development.

The market, however, faced setbacks during the COVID-19 pandemic due to social distancing and lockdowns, which slowed down clinical trials and reduced patient visits to healthcare facilities for precision oncology care. Despite these challenges, the field is recovering, with ongoing research, early detection efforts, and improving prognosis methods driving the demand for precision oncology services.

Globally, the approach to cancer management varies significantly. A WHO survey indicates that only 39% of surveyed countries include basic cancer management in their publicly financed health services, and just 28% provide broader palliative care.

In terms of epidemiology, 2022 saw approximately 20 million new cancer cases and 9.7 million deaths worldwide. The data also shows that roughly 53.5 million people were living within five years of a cancer diagnosis, highlighting the widespread impact of the disease. The statistics further reveal that about one in five people develop cancer during their lifetime, with men facing a higher mortality rate compared to women.

This dataset provides past cancer history information of cholangiocarcinoma patients from the National Cancer Center (NCC) via an open API. Access is granted through a user authentication key, and the dataset includes fields such as institution name, reference year, patient data, and cancer history. It is valuable for research examining how a history of other cancers affects disease progression, treatment response, and prognosis in cholangiocarcinoma patients.

The dataset can serve as foundational data for studies on secondary cancer risks, development of clinical guidelines, and monitoring of high-risk groups in public health and healthcare policy. You may also apply for and access the dataset via the National Cancer Center’s Big Data Portal at the URL below.

URL: https://www.bigdata-cancer.kr/ncc/viewOpenApiDetail.do?datasetIdentifier=21110

The Intelligent Cancer Care (ICC) market is experiencing robust growth, driven by advancements in artificial intelligence (AI), big data analytics, and precision medicine. The market size in 2025 is estimated at $4,876.8 million. While the CAGR is not provided, considering the rapid technological advancements and increasing prevalence of cancer, a conservative estimate would place the CAGR between 15% and 20% for the forecast period of 2025-2033. This growth is fueled by several key factors. The increasing availability of large, high-quality cancer datasets enables the development of more accurate and effective AI-powered diagnostic and therapeutic tools. Furthermore, the rising adoption of personalized medicine, focusing on tailoring treatments to individual patient characteristics, is significantly boosting the demand for ICC solutions. Pharmaceutical giants like Pfizer, Sanofi, and Roche, alongside technology leaders such as IBM, NVIDIA, and Philips, are actively investing in and developing innovative ICC solutions, underscoring the market's potential. The integration of AI into various stages of cancer care, including early detection, diagnosis, treatment planning, and monitoring, is streamlining workflows and improving patient outcomes. The continued development of sophisticated algorithms and improved data accessibility will further accelerate the market's expansion in the coming years. However, challenges remain. The high cost of developing and implementing AI-powered ICC solutions, coupled with regulatory hurdles and data privacy concerns, pose significant barriers to market entry and widespread adoption. Furthermore, ensuring the ethical and responsible use of AI in healthcare, particularly in sensitive areas like cancer treatment, remains crucial. Despite these challenges, the long-term outlook for the ICC market is exceptionally positive, driven by continued technological advancements, increasing investment, and a growing global need for more efficient and effective cancer care solutions. The market is expected to witness significant expansion, driven by the integration of AI across all aspects of cancer management from diagnosis to treatment and monitoring. This will lead to improved accuracy, personalized medicine, and enhanced patient outcomes.

Oncology Automation Market Outlook

The global oncology automation market size was valued at approximately USD 2.5 billion in 2023 and is projected to reach about USD 6.8 billion by 2032, with a compound annual growth rate (CAGR) of 11.5% from 2024 to 2032. The significant growth factor driving this market is the increasing prevalence of cancer worldwide, coupled with the rising need for precision and efficiency in cancer treatment procedures. The demand for automation in oncology is also fueled by technological advancements and the integration of artificial intelligence and machine learning in healthcare.

One major growth factor for the oncology automation market is the increasing burden of cancer, which remains one of the leading causes of mortality globally. According to the World Health Organization (WHO), cancer is responsible for an estimated 10 million deaths in 2020. This alarming statistic underscores the urgent need for effective cancer treatment solutions. Automation in oncology not only enhances the precision of treatment but also reduces the physical and cognitive load on healthcare providers, leading to improved patient outcomes. The adoption of automated systems in oncology helps in minimizing human errors and optimizing the overall treatment process, making it a crucial component in modern healthcare.

Additionally, the growing awareness and acceptance of robotic systems in healthcare have significantly contributed to the market's growth. Patients and healthcare providers are increasingly recognizing the benefits of robotic-assisted surgeries and automated drug delivery systems in oncology. These systems offer enhanced precision, reduced recovery times, and lower risks of complications. The integration of robotics in radiation therapy and chemotherapy has revolutionized cancer treatment, enabling more targeted and effective interventions. As a result, the demand for oncology automation solutions is expected to rise substantially in the coming years.

Another critical factor driving the market is the continuous innovation and development of advanced software solutions for oncology. These software solutions are designed to streamline and optimize various aspects of cancer treatment, including patient data management, treatment planning, and monitoring. The use of big data analytics and machine learning algorithms enables healthcare providers to make data-driven decisions, improving the accuracy and effectiveness of treatments. The growing adoption of electronic health records (EHR) and telemedicine further supports the integration of these software solutions, enhancing the overall efficiency of oncology care.

The regional outlook for the oncology automation market indicates significant growth potential across various regions. North America, particularly the United States, dominates the market due to the presence of advanced healthcare infrastructure, high adoption of cutting-edge technologies, and substantial investments in cancer research. Europe also shows promising growth, driven by the increasing prevalence of cancer and supportive government initiatives. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, attributed to the rising healthcare expenditure, improving healthcare infrastructure, and growing awareness about advanced cancer treatment options. Emerging economies in Latin America and the Middle East & Africa are also anticipated to contribute to the market's growth, albeit at a slower pace, due to ongoing healthcare developments and increasing focus on cancer care.

Product Type Analysis

In the oncology automation market, the product type segment is categorized into robotic systems, software solutions, and services. Each of these categories plays a crucial role in enhancing cancer treatment outcomes and streamlining oncological workflows. Robotic systems are among the most prominent technologies in this segment, offering unparalleled precision and control in surgical procedures and treatment administration. These systems are designed to assist healthcare providers in performing complex surgeries with minimal invasiveness, reducing recovery times and improving patient outcomes. The adoption of robotic systems in oncology is expected to grow as technology advances, making these systems more accessible and affordable for healthcare facilities across the globe.

Software solutions form another essential component of the oncology autom

We propose a novel two-stage analysis strategy to discover candidate genes associated with the particular cancer outcomes in large multimodal genomic cancers databases, such as The Cancer Genome Atlas (TCGA). During the first stage, we use mixed mutual information to perform variable selection; during the second stage, we use scalable Bayesian network (BN) modeling to identify candidate genes and their interactions. Two crucial features of the proposed approach are (i) the ability to handle mixed data types (continuous and discrete, genomic, epigenomic, etc.) and (ii) a flexible boundary between the variable selection and network modeling stages — the boundary that can be adjusted in accordance with the investigators’ BN software scalability and hardware implementation. These two aspects result in high generalizability of the proposed analytical framework. We apply the above strategy to three different TCGA datasets (LGG, Brain Lower Grade Glioma; HNSC, Head and Neck Squamous Cell Carcinoma; STES, Stomach and Esophageal Carcinoma), linking multimodal molecular information (SNPs, mRNA expression, DNA methylation) to two clinical outcome variables (tumor status and patient survival). We identify 11 candidate genes, of which 6 have already been directly implicated in the cancer literature. One novel LGG prognostic factor suggested by our analysis, methylation of TMPRSS11F type II transmembrane serine protease, presents intriguing direction for the follow-up studies.

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Interventional Oncology Market Size 2025-2029

The interventional oncology market size is forecast to increase by USD 1.66 billion, at a CAGR of 9% between 2024 and 2029.

The market is experiencing significant growth due to the increasing prevalence of cancer worldwide. This expanding patient base necessitates advanced treatment modalities, leading to a growing focus on Minimally Invasive Tumor Ablation (MWA) techniques. These procedures offer numerous benefits, including reduced recovery time, minimal scarring, and improved patient outcomes. However, the high cost of interventional oncology procedures poses a significant challenge to market growth. Robotic surgery and surgical robots are advancing procedural navigation, while clinical pathways and transarterial chemoembolization streamline treatment processes. Big data and data analytics are driving insights into the tumor microenvironment, enabling personalized treatment approaches.
This financial barrier may limit access to these innovative treatments for many, necessitating collaborations between industry players, insurers, and regulatory bodies to explore cost-effective solutions. Effective partnerships and strategic pricing models could help increase affordability and expand the reach of interventional oncology, capitalizing on the market's potential for growth.

What will be the Size of the Interventional Oncology Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, driven by ongoing advancements in technology and clinical research. Tumor ablation techniques, such as radiofrequency ablation and microwave ablation, are increasingly being utilized for the treatment of various types of malignancies. Clinical trials are underway to evaluate the safety and efficacy of these procedures, with a focus on improving patient outcomes and reducing hospital stay and procedure time. Quality assurance is a critical aspect of interventional oncology, ensuring the delivery of accurate and effective treatments. Endoscopic surgery and image-guided procedures enable precise tumor resection and dose optimization, leading to improved treatment response. Interventional radiologists are at the forefront of these advancements, utilizing technology such as drug-eluting beads and yttrium-90 microspheres for targeted drug delivery.

Radiation therapy and medical oncology are also integral components of interventional oncology, with ongoing research focused on improving patient quality of life and survival rates. Professional societies and regulatory approvals play a crucial role in advancing the field, providing guidelines for best practices and ensuring the safety and efficacy of new technologies. Healthcare economics and patient selection are also key considerations, with a focus on minimally invasive surgery and market access. Adverse events and patient satisfaction are continually monitored, with data analysis playing a critical role in informing clinical decision-making and driving innovation. Laparoscopic surgery and robotic technology are also gaining popularity in interventional oncology, offering advantages in terms of minimally invasive procedures and improved patient outcomes.

Targeted therapy and treatment planning are also areas of active research, with navigation systems and implantable devices enabling more precise and personalized treatments. The ongoing dynamism of the market underscores the importance of continuous education and training for healthcare professionals to stay abreast of the latest developments and provide the best possible care for their patients.

How is this Interventional Oncology Industry segmented?

The interventional oncology industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.End-userHospitals and diagnostic centersAmbulatory surgery centersResearch and academic institutesProductParticle embolizationAblationSupport devicesDisease TypeLiver cancerLung cancerKidney cancerBone metastasesOthersGeographyNorth AmericaUSCanadaMexicoEuropeFranceGermanyUKAPACChinaIndiaJapanSouth KoreaRest of World (ROW)

By End-user Insights

The hospitals and diagnostic centers segment is estimated to witness significant growth during the forecast period.

Interventional oncology is a dynamic and evolving field in healthcare, focusing on minimally invasive techniques to treat various types of tumors. Hospitals serve as the primary hub for interventional oncology, offering advanced facilities and multidisciplinary teams specializing in image-guided biopsies, ablation, and embolization. These procedures include radiofrequency ablation, microwave ablation, and transa

The global Real-World Evidence (RWE) solutions market is experiencing robust growth, projected to reach $1.47 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 9.40% from 2025 to 2033. This expansion is driven by several key factors. The increasing adoption of RWE by pharmaceutical and medical device companies to support regulatory submissions and accelerate drug development is a significant driver. Furthermore, the growing volume of readily available electronic health records (EHRs), claims data, and patient-generated health data (PGHD) fuels the market's expansion. The shift towards value-based healthcare models, emphasizing real-world outcomes, further necessitates the use of RWE solutions for better patient care and cost-effectiveness. Technological advancements in data analytics and artificial intelligence (AI) are also instrumental in enhancing the capabilities of RWE platforms, making them more efficient and insightful. Market segmentation reveals significant contributions from oncology, immunology, and cardiovascular disease therapeutic areas, while healthcare payers and providers are key end-users leveraging these solutions. North America currently holds a substantial market share, though robust growth is anticipated in Asia-Pacific regions driven by rising healthcare expenditure and technological adoption. The market's growth, however, is not without challenges. Data privacy and security concerns surrounding the use of patient-level data remain a significant restraint. The complexity of integrating diverse data sources and ensuring data quality can also pose hurdles. Regulatory landscapes vary across regions, creating inconsistencies that impact market penetration. Nevertheless, ongoing efforts towards standardization and the development of robust data governance frameworks are mitigating these concerns, paving the way for continued market expansion. The competitive landscape is dynamic, with a mix of established players and emerging companies offering diverse solutions, ranging from data aggregation and analytics platforms to specialized consulting services. The market's trajectory suggests a promising future for RWE solutions as they become increasingly integral to healthcare research, drug development, and regulatory decision-making. Recent developments include: In December 2021, EVERSANA signed an agreement with Janssen Research & Development LLC (Janssen) to drive evidence-based development of Janssen therapies, treatments, and patient support models., In October 2021, Real-World Evidence Transparency Initiative launched the Real-World Evidence Registry to establish a culture of transparency for the analysis and reporting of Real-World Evidence in healthcare and health research. The Real-World Evidence Transparency Initiative is a partnership between ISPOR, the International Society for Pharmacoepidemiology, the Duke-Margolis Center for Health Policy, and the National Pharmaceutical Council.. Key drivers for this market are: Shift From Volume- to Value-based Care, Increasing Aging Population and Prevalence of Chronic Diseases. Potential restraints include: Shift From Volume- to Value-based Care, Increasing Aging Population and Prevalence of Chronic Diseases. Notable trends are: Oncology is Anticipated to be the Dominant Segment During the Forecast Period.

Raw data from CMS

This data is an open API that provides information on the types of surgery for lung cancer patients at the National Cancer Center. The included items include various surgical methods such as lobectomy, total lung resection, and partial resection, and are used to analyze the type of surgery selected based on the patient's stage, health status, and pathological characteristics. This data can be used for research such as comparing survival rates by type of surgery, analyzing treatment responses, and establishing customized treatment strategies. The data can be used after applying through this page or the National Cancer Center Big Data Open Portal. https://www.bigdata-cancer.kr/ncc/viewOpenApiDetail.do?datasetIdentifier=14210

China Precision Medicine Market size was valued at $ 3.04 Bn in 2024 and is expected to reach $ 12.56 Bn by 2032, growing at a CAGR of 19.4% from 2026 to 2032.China Precision Medicine Market DynamicsThe key market dynamics that are shaping the China precision medicine market include:Key Market Drivers:Government Investment and Strategic Initiatives: China's substantial government investment in precision medicine via strategic programs is a significant industry driver. The Chinese National Health Commission allotted ¥60 billion ($9.3 billion) for precision medicine research and development under the 14th Five-Year Plan (2021-2025), a 43% increase from the previous five-year period. The Chinese Ministry of Science and Technology reports that the national Precision Medicine Initiative launched in 2016 has developed 22 national precision medicine research facilities by 2023, with annual funding topping ¥8.5 billion ($1.3 billion). According to the Chinese Academy of Medical Sciences, government-backed precision medicine projects expanded by 78% between 2019 and 2023, with 187 large clinical research programs currently underway, involving more than 430,000 patients across the country.

We propose a novel two-stage analysis strategy to discover candidate genes associated with the particular cancer outcomes in large multimodal genomic cancers databases, such as The Cancer Genome Atlas (TCGA). During the first stage, we use mixed mutual information to perform variable selection; during the second stage, we use scalable Bayesian network (BN) modeling to identify candidate genes and their interactions. Two crucial features of the proposed approach are (i) the ability to handle mixed data types (continuous and discrete, genomic, epigenomic, etc.) and (ii) a flexible boundary between the variable selection and network modeling stages — the boundary that can be adjusted in accordance with the investigators’ BN software scalability and hardware implementation. These two aspects result in high generalizability of the proposed analytical framework. We apply the above strategy to three different TCGA datasets (LGG, Brain Lower Grade Glioma; HNSC, Head and Neck Squamous Cell Carcinoma; STES, Stomach and Esophageal Carcinoma), linking multimodal molecular information (SNPs, mRNA expression, DNA methylation) to two clinical outcome variables (tumor status and patient survival). We identify 11 candidate genes, of which 6 have already been directly implicated in the cancer literature. One novel LGG prognostic factor suggested by our analysis, methylation of TMPRSS11F type II transmembrane serine protease, presents intriguing direction for the follow-up studies.

Oncology Informatics Market size was valued at USD 12.1 Billion in 2024 and is projected to reach USD 33.5 Billion by 2032, growing at a CAGR of 12% during the forecast period 2026-2032.

The Global Oncology Informatics Market is mainly driven by the increasing cost of cancer treatment, a growing number of cancer patients, and the rising adoption of oncology-specific EHR's. The Global Oncology Informatics Market report provides a holistic evaluation of the market. The report offers a comprehensive analysis of key segments, trends, drivers, restraints, competitive landscape, and factors that are playing a substantial role in the market.

Increasing Cancer Rates: As cancer is becoming more commonplace worldwide, there is a need for improved instruments for research, diagnosis, and treatment, which is why oncology informatics solutions are becoming more popular.

Technological Advancements: Cloud computing, big data analytics, and artificial intelligence (AI) are transforming healthcare data analysis and administration in oncology.

Molecular Tumor Board Solutions Market Outlook

According to our latest research, the global Molecular Tumor Board Solutions market size reached USD 1.45 billion in 2024, reflecting robust growth driven by the increasing adoption of precision oncology and digital health solutions. The market is experiencing a strong compound annual growth rate (CAGR) of 14.8% and is expected to reach USD 4.27 billion by 2033. This expansion is fueled by the rising prevalence of cancer, advancements in molecular diagnostics, and a growing emphasis on personalized medicine worldwide. As per our latest research, the integration of artificial intelligence and big data analytics into tumor board platforms is further accelerating adoption, ensuring that the market maintains its upward trajectory over the forecast period.

A key growth factor for the Molecular Tumor Board Solutions market is the increasing complexity of cancer treatment, which necessitates multidisciplinary collaboration and data-driven decision-making. The surge in next-generation sequencing (NGS) and other molecular profiling technologies has resulted in an exponential increase in the volume and complexity of patient data. Molecular tumor board solutions provide a centralized platform for aggregating, interpreting, and visualizing this data, enabling oncologists, pathologists, geneticists, and other specialists to collaborate efficiently. This is particularly important as the landscape of targeted therapies and immunotherapies expands, requiring comprehensive genomic interpretation and evidence-based recommendations. The ability of these solutions to streamline clinical workflows, improve diagnostic accuracy, and enhance patient outcomes is driving their adoption in both academic and community healthcare settings.

Another significant factor propelling market growth is the global shift toward value-based healthcare and the increasing focus on precision oncology. Governments and healthcare payers are investing heavily in digital health infrastructure and cancer research to improve survival rates and reduce the overall burden of cancer. Molecular tumor board solutions are becoming an integral part of this transformation by facilitating personalized treatment planning, reducing unnecessary treatments, and optimizing resource utilization. The integration of advanced analytics, clinical decision support, and real-time data sharing capabilities within these platforms is attracting interest from healthcare providers seeking to deliver high-quality, cost-effective cancer care. Furthermore, the growing adoption of cloud-based solutions is enabling remote collaboration and expanding access to expert opinions, particularly in underserved regions.

The rapid advancements in artificial intelligence and machine learning are also contributing to the evolution of molecular tumor board solutions. AI-powered algorithms are increasingly being used to automate genomic data interpretation, identify actionable mutations, and match patients with the most suitable clinical trials. This not only accelerates the decision-making process but also enhances the accuracy and consistency of treatment recommendations. The integration of AI and big data analytics is enabling tumor boards to handle larger datasets, incorporate real-world evidence, and continuously learn from new cases. These technological innovations are expected to drive further adoption of molecular tumor board solutions, particularly as the demand for personalized and data-driven oncology care continues to grow.

From a regional perspective, North America currently dominates the Molecular Tumor Board Solutions market, accounting for the largest share in 2024. This is attributed to the presence of leading healthcare institutions, advanced digital health infrastructure, and substantial investments in cancer research and precision medicine. However, Asia Pacific is expected to witness the highest CAGR over the forecast period, driven by rising cancer incidence, increasing healthcare expenditure, and growing awareness of personalized medicine. Europe also represents a significant market, supported by strong government initiatives and collaborative research networks. The Middle East & Africa and Latin America are emerging markets with considerable growth potential, as healthcare systems in these regions continue to invest in digital transformation and oncology care.

Real World Evidence Solutions Market size was valued at USD 1.30 Billion in 2024 and is projected to reach USD 3.71 Billion by 2031, growing at a CAGR of 13.92% during the forecast period 2024-2031.

Global Real World Evidence Solutions Market Drivers

The market drivers for the Real World Evidence Solutions Market can be influenced by various factors. These may include:

Growing Need for Evidence-Based Healthcare: Real-world evidence (RWE) is becoming more and more important in healthcare decision-making, according to stakeholders such as payers, providers, and regulators. In addition to traditional clinical trial data, RWE solutions offer important insights into the efficacy, safety, and value of healthcare interventions in real-world situations. Growing Use of RWE by Pharmaceutical Companies: RWE solutions are being used by pharmaceutical companies to assist with market entry, post-marketing surveillance, and drug development initiatives. Pharmaceutical businesses can find new indications for their current medications, improve clinical trial designs, and convince payers and providers of the worth of their products with the use of RWE. Increasing Priority for Value-Based Healthcare: The emphasis on proving the cost- and benefit-effectiveness of healthcare interventions in real-world settings is growing as value-based healthcare models gain traction. To assist value-based decision-making, RWE solutions are essential in evaluating the economic effect and real-world consequences of healthcare interventions. Technological and Data Analytics Advancements: RWE solutions are becoming more capable due to advances in machine learning, artificial intelligence, and big data analytics. With the use of these technologies, healthcare stakeholders can obtain actionable insights from the analysis of vast and varied datasets, including patient-generated data, claims data, and electronic health records. Regulatory Support for RWE Integration: RWE is being progressively integrated into regulatory decision-making processes by regulatory organisations including the European Medicines Agency (EMA) and the U.S. Food and Drug Administration (FDA). The FDA's Real-World Evidence Programme and the EMA's Adaptive Pathways and PRIority MEdicines (PRIME) programme are two examples of initiatives that are making it easier to incorporate RWE into regulatory submissions and drug development. Increasing Emphasis on Patient-Centric Healthcare: The value of patient-reported outcomes and real-world experiences in healthcare decision-making is becoming more widely acknowledged. RWE technologies facilitate the collection and examination of patient-centered data, offering valuable insights into treatment efficacy, patient inclinations, and quality of life consequences. Extension of RWE Use Cases: RWE solutions are being used in medication development, post-market surveillance, health economics and outcomes research (HEOR), comparative effectiveness research, and market access, among other healthcare fields. The necessity for a variety of RWE solutions catered to the needs of different stakeholders is being driven by the expansion of RWE use cases.

The precision medicine diagnostics market, valued at $82.07 billion in 2025, is projected to experience robust growth, driven by a compound annual growth rate (CAGR) of 4.1% from 2025 to 2033. This expansion is fueled by several key factors. Firstly, the increasing prevalence of chronic diseases like cancer, cardiovascular diseases, and neurological disorders necessitates personalized treatment approaches, driving demand for precise diagnostic tools. Advancements in genomics, bioinformatics, and big data analytics are enabling the development of more sophisticated diagnostic tests capable of identifying disease subtypes, predicting treatment response, and monitoring disease progression with greater accuracy. The integration of artificial intelligence (AI) and machine learning (ML) further enhances diagnostic capabilities, improving speed and accuracy while reducing costs. Furthermore, the growing adoption of precision medicine initiatives by governments and healthcare providers worldwide is creating a favorable regulatory landscape and increasing funding for research and development. The market is segmented by technology (bioinformatics, gene sequencing, drug discovery, precision molecular diagnostics, big data analytics) and application (oncology, CNS, hematology, respiratory, immunology, others), reflecting the diverse array of diagnostic tools employed across various therapeutic areas. North America currently dominates the market, leveraging its strong technological infrastructure and high healthcare expenditure. However, significant growth is anticipated in Asia-Pacific, driven by expanding healthcare infrastructure and rising disposable incomes. The competitive landscape is characterized by a mix of large pharmaceutical companies, specialized diagnostic companies, and technology providers. Major players like Pfizer, Novartis, and Qiagen are strategically investing in research and development to expand their precision medicine diagnostic portfolios. Smaller companies are focusing on niche applications and innovative technologies, contributing significantly to market innovation. Despite the promising growth trajectory, challenges remain. High costs associated with advanced diagnostic tests pose a barrier to access, particularly in low- and middle-income countries. Furthermore, the complex regulatory landscape and data privacy concerns require careful navigation. However, ongoing technological advancements, coupled with increasing awareness and acceptance of precision medicine, are expected to overcome these challenges, ensuring substantial growth in the precision medicine diagnostics market over the next decade.

This data is an open API that provides pathological staging information based on surgical pathology of lung cancer patients at the National Cancer Center. The included items include pathological staging (based on TNM classification) confirmed after surgery, and are used to predict the progression and prognosis of lung cancer. This data is useful for analyzing survival rates by stage, comparing treatment outcomes, and studying the concordance between pathological staging and imaging staging. The data can be used after applying through this page or the National Cancer Center Big Data Open Portal. https://www.bigdata-cancer.kr/ncc/viewOpenApiDetail.do?datasetIdentifier=14200