This report will prove invaluable to leading firms striving for new revenue pockets if they wish to better understand the industry and its underlying dynamics. It will be useful for companies that would like to expand into different industries or to expand their existing operations in a new region.
Accelerated Drug Discovery and Targeted Therapies Driving Market Growth
AI technologies are transforming the drug research and development process in cancer by harnessing massive volumes of data and smart algorithms. These developments seek to speed up the identification of prospective medication candidates, improve their efficacy, and make the development of targeted medicines easier. AI in drug development has the potential to dramatically reduce the time and expense associated with traditional techniques.
Collaborations between pharmaceutical corporations, technology businesses, and academic institutions have increased as a result of the development of AI-driven platforms and tools for drug discovery and development. These collaborations attempt to use AI to accelerate the development of new cancer medicines. For instance, in May 2023, the University of Sydney and the Australian business Pharos Therapeutics agreed to use AI to advance medication discovery for the treatment of cancer and uncommon disorders.
Lack of Standardization causes significant barriers
Standardized data collection and annotation practices are crucial in AI-driven oncology research and care. Variations in data collection methods, formats, and annotation protocols can impact the performance and generalizability of AI algorithms. By standardizing these processes, the quality and consistency of data can be improved, leading to more robust AI models. Standardization also facilitates data sharing, collaboration, and reproducibility, enabling meaningful comparisons and advancements in the field.
For instance, collaborative efforts between healthcare institutions and technology companies, such as the Cancer Imaging Archive (TCIA) and industry-led consortia like the Digital Imaging and Communications in Medicine (DICOM) are striving towards standardizing data sharing, storage, and annotation practices in oncology imaging. These initiatives promote the use of standardized guidelines and protocols for data collection, algorithm development, and evaluation.
By addressing the lack of standardization in AI oncology, stakeholders can overcome barriers to market growth. Collaborative initiatives, industry partnerships, and regulatory guidance are essential to establish comprehensive frameworks and guidelines for data collection, algorithm development, and evaluation. These efforts ensure that data collection methods, formats, and annotation protocols are consistent and harmonized across different healthcare institutions and research organizations.
What Questions Should You Ask before Buying a Market Research Report?
You need to discover how this will impact the AI in oncology market today, and over the next 10 years:
This report tells you TODAY how the AI in oncology market will develop in the next 10 years, and in line with the variations in COVID-19 economic recession and bounce. This market is more critical now than at any point over the last 10 years.
Forecasts to 2033 and other analyses reveal commercial prospects
This report includes data analysis and invaluable insight into how COVID-19 will affect the industry and your company. Four COVID-19 recovery patterns and their impact, namely, “V”, “L”, “W” and “U” are discussed in this report.
Segments Covered in the Report
Product Type
Usage Type
Disease Type
Accelerated Drug Discovery and Targeted Therapies Driving Market Growth
AI technologies are transforming the drug research and development process in cancer by harnessing massive volumes of data and smart algorithms. These developments seek to speed up the identification of prospective medication candidates, improve their efficacy, and make the development of targeted medicines easier. AI in drug development has the potential to dramatically reduce the time and expense associated with traditional techniques.
Collaborations between pharmaceutical corporations, technology businesses, and academic institutions have increased as a result of the development of AI-driven platforms and tools for drug discovery and development. These collaborations attempt to use AI to accelerate the development of new cancer medicines. For instance, in May 2023, the University of Sydney and the Australian business Pharos Therapeutics agreed to use AI to advance medication discovery for the treatment of cancer and uncommon disorders.
Lack of Standardization causes significant barriers
Standardized data collection and annotation practices are crucial in AI-driven oncology research and care. Variations in data collection methods, formats, and annotation protocols can impact the performance and generalizability of AI algorithms. By standardizing these processes, the quality and consistency of data can be improved, leading to more robust AI models. Standardization also facilitates data sharing, collaboration, and reproducibility, enabling meaningful comparisons and advancements in the field.
For instance, collaborative efforts between healthcare institutions and technology companies, such as the Cancer Imaging Archive (TCIA) and industry-led consortia like the Digital Imaging and Communications in Medicine (DICOM) are striving towards standardizing data sharing, storage, and annotation practices in oncology imaging. These initiatives promote the use of standardized guidelines and protocols for data collection, algorithm development, and evaluation.
By addressing the lack of standardization in AI oncology, stakeholders can overcome barriers to market growth. Collaborative initiatives, industry partnerships, and regulatory guidance are essential to establish comprehensive frameworks and guidelines for data collection, algorithm development, and evaluation. These efforts ensure that data collection methods, formats, and annotation protocols are consistent and harmonized across different healthcare institutions and research organizations.
What Questions Should You Ask before Buying a Market Research Report?
- How is the AI in oncology market evolving?
- What is driving and restraining the AI in oncology market?
- How will each AI in oncology submarket segment grow over the forecast period and how much revenue will these submarkets account for in 2033?
- How will the market shares for each AI in oncology submarket develop from 2023 to 2033?
- What will be the main driver for the overall market from 2023 to 2033?
- Will leading AI in oncology markets broadly follow the macroeconomic dynamics, or will individual national markets outperform others?
- How will the market shares of the national markets change by 2033 and which geographical region will lead the market in 2033?
- Who are the leading players and what are their prospects over the forecast period?
- What are the AI in oncology projects for these leading companies?
- How will the industry evolve during the period between 2023 and 2033? What are the implications of AI in oncology projects taking place now and over the next 10 years?
- Is there a greater need for product commercialisation to further scale the AI in oncology market?
- Where is the AI in oncology market heading and how can you ensure you are at the forefront of the market?
- What are the best investment options for new product and service lines?
- What are the key prospects for moving companies into a new growth path and C-suite?
You need to discover how this will impact the AI in oncology market today, and over the next 10 years:
- Our 289-page report provides 123 tables and 163 charts/graphs exclusively to you.
- The report highlights key lucrative areas in the industry so you can target them – NOW.
- It contains in-depth analysis of global, regional and national sales and growth.
- It highlights for you the key successful trends, changes and revenue projections made by your competitors.
This report tells you TODAY how the AI in oncology market will develop in the next 10 years, and in line with the variations in COVID-19 economic recession and bounce. This market is more critical now than at any point over the last 10 years.
Forecasts to 2033 and other analyses reveal commercial prospects
- In addition to revenue forecasting to 2033, our new study provides you with recent results, growth rates, and market shares.
- You will find original analyses, with business outlooks and developments.
- Discover qualitative analyses (including market dynamics, drivers, opportunities, restraints and challenges), cost structure, impact of rising AI in oncology prices and recent developments.
This report includes data analysis and invaluable insight into how COVID-19 will affect the industry and your company. Four COVID-19 recovery patterns and their impact, namely, “V”, “L”, “W” and “U” are discussed in this report.
Segments Covered in the Report
Product Type
- Software
- Hardware
- Services
Usage Type
- Cancer Research
- Pre-screening and Diagnosis
- Treatment
Disease Type
- Lung Cancer
- Breast Cancer
- Prostate Cancer
- Colon Cancer
- Others
- Pharmaceutical and Biopharmaceutical Companies
- Research Institutes
- Hospitals and Diagnostic Centres
- Others