The global artificial intelligence in genomics market size is expected to reach around US$ 5,972 million by 2030 and is expected to grow at an impressive double-digit rate of 40.31% from 2022 to 2030. The growing adoption of the AI in the precision medicine is significantly driving the growth of the AI in genomics market.
The study includes drivers and restraints of this market. The study provides an analysis of the global artificial intelligence in genomics market for the period 2017-2030, wherein 2022 to 2030 is the forecast period and 2021 is considered as the base year.
Report Scope of the Artificial Intelligence in Genomics Market
| Report Coverage | Details |
| Market Size by 2030 | USD 5,972 Million |
| CAGR from 2022 to 2030 | CAGR of 40.31% |
| Largest Market | North America |
| Fastest Growing Market | Asia Pacific |
| Base Year | 2021 |
| Forecast Period | 2022 to 2030 |
| Segments Covered | Offering, Application, End User, Technology, Functionality, Geography |
Our Free Sample Reports Includes:
- In-depth Industry Analysis, Introduction, Overview, and COVID-19 Pandemic Outbreak.
- Impact Analysis 150+ Pages Research Report (Including latest research).
- Provide chapter-wise guidance on request 2022 Updated Regional Analysis with Graphical Representation of Trends, Size, & Share, Includes Updated List of figures and tables.
- Updated Report Includes Major Market Players with their Sales Volume, Business Strategy and Revenue Analysis by using Precedence Research methodology.
Download Free Sample Copy Here (Including TOC, List of Tables & Figures, and Chart) @ https://www.precedenceresearch.com/sample/1721
Research Methodology
A unique research methodology has been utilized to conduct comprehensive research on the growth of the global artificial intelligence in genomics market and arrive at conclusions on the future growth prospects of the market. This research methodology is a combination of primary and secondary research, which helps analysts warrant the accuracy and reliability of the draw conclusions. Secondary sources referred to by analysts during the production of the global market report include statistics from company annual reports, SEC filings, company websites, World Bank database, investor presentations, regulatory databases, government publications, and industry white papers. Analysts have also interviewed senior managers, product portfolio managers, CEOs, VPs, and market intelligence managers, who contributed to the production of our study on the market as a primary source.
These primary and secondary sources provided exclusive information during interviews, which serves as a validation from mattress topper industry leaders. Access to an extensive internal repository and external proprietary databases allows this report to address specific details and questions about the global artificial intelligence in genomics market with accuracy. The study also uses the top-down approach to assess the numbers for each segment and the bottom-up approach to counter-validate them. This has helped to estimates the future prospects of the global market more reliable and accurate.
Why should you invest in this report?
If you are aiming to enter the global artificial intelligence in genomics market, this report is a comprehensive guide that provides crystal clear insights into this niche market. All the major application areas for artificial intelligence in genomics are covered in this report and information is given on the important regions of the world where this market is likely to boom during the forecast period of 2022-2030, so that you can plan your strategies to enter this market accordingly.
Besides, through this report, you can have a complete grasp of the level of competition you will be facing in this hugely competitive market and if you are an established player in this market already, this report will help you gauge the strategies that your competitors have adopted to stay as market leaders in this market. For new entrants to this market, the voluminous data provided in this report is invaluable.
Some of the prominent players in the global artificial intelligence in genomics market include:
- IBM
- NVIDIA Corporation
- Benevolent AI
- Verge Genomics
- MolecularMatch, Inc.
- SOPHiA GENETICS
- PrecisionLife Ltd.
- Lifebit
- FDNA, Inc.
- Empiric Logic
- Microsoft
- Deep Genomics
- Fabric Genomics Inc.
- Freenome Holdings, Inc.
- Cambridge Cancer Genomics
- Data4Cure Inc.
- Engine Biosciences Pte. Ltd.
- Genoox Ltd.
- Diploid
- DNAnexus Inc.
Market Segmentation:
By Offering
- Software
- Services
By Application
- Drug Discovery & Development
- Precision Medicine
- Diagnostics
- Animal Research and Agriculture
- Others
By End User
- Pharmaceutical & Biotech Companies
- Government Organizations
- Research Organizations
- Others
By Technology
- Machine Learning
- Deep Learning
- Supervised Learning
- Reinforcement Learning
- Unsupervised Learning
- Other
- Other Technologies
By Functionality
- Genome Sequencing
- Gene Editing
- Clinical Workflows
- Predictive Genetic Testing & Preventive Medicine
Regional Analysis:
The geographical analysis of the global artificial intelligence in genomics market has been done for North America, Europe, Asia-Pacific, and the Rest of the World.
The North American Market is again segmented into the US, Canada, and Mexico. Coming to the European Market, it can be segmented further into the UK, Germany, France, Italy, Spain, and the rest. Coming to the Asia-Pacific, the global artificial intelligence in genomics Market is segmented into China, India, Japan, and Rest of Asia Pacific. Among others, the market is segmented into the Middle East and Africa, (GCC, North Africa, South Africa and Rest of the Middle East & Africa).
Key Questions Answered by the Report:
- What will be the size of the global artificial intelligence in genomics market in 2030?
- What is the expected CAGR for the artificial intelligence in genomics market between 2021 and 2030?
- Which are the top players active in this global market?
- What are the key drivers of this global market?
- How will the market situation change in the coming years?
- Which region held the highest market share in this global market?
- What are the common business tactics adopted by players?
- What is the growth outlook of the global artificial intelligence in genomics market?
TABLE OF CONTENT
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Artificial Intelligence in Genomics Market
5.1. COVID-19 Landscape: Artificial Intelligence in Genomics Industry Impact
5.2. COVID 19 - Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Artificial Intelligence in Genomics Market, By Offering
8.1. Artificial Intelligence in Genomics Market, by Offering, 2022-2030
8.1.1. Software
8.1.1.1. Market Revenue and Forecast (2017-2030)
8.1.2. Services
8.1.2.1. Market Revenue and Forecast (2017-2030)
Chapter 9. Global Artificial Intelligence in Genomics Market, By Application
9.1. Artificial Intelligence in Genomics Market, by Application, 2022-2030
9.1.1. Drug Discovery & Development
9.1.1.1. Market Revenue and Forecast (2017-2030)
9.1.2. Precision Medicine
9.1.2.1. Market Revenue and Forecast (2017-2030)
9.1.3. Diagnostics
9.1.3.1. Market Revenue and Forecast (2017-2030)
9.1.4. Animal Research and Agriculture
9.1.4.1. Market Revenue and Forecast (2017-2030)
9.1.5. Others
9.1.5.1. Market Revenue and Forecast (2017-2030)
Chapter 10. Global Artificial Intelligence in Genomics Market, By End User
10.1. Artificial Intelligence in Genomics Market, by End User, 2022-2030
10.1.1. Pharmaceutical & Biotech Companies
10.1.1.1. Market Revenue and Forecast (2017-2030)
10.1.2. Government Organizations
10.1.2.1. Market Revenue and Forecast (2017-2030)
10.1.3. Research Organizations
10.1.3.1. Market Revenue and Forecast (2017-2030)
10.1.6. Others
10.1.6.1. Market Revenue and Forecast (2017-2030)
Chapter 11. Global Artificial Intelligence in Genomics Market, By Technology
11.1. Artificial Intelligence in Genomics Market, by Technology, 2022-2030
11.1.1. Machine Learning
11.1.1.1. Market Revenue and Forecast (2017-2030)
11.1.2. Other Technologies
11.1.2.1. Market Revenue and Forecast (2017-2030)
Chapter 12. Global Artificial Intelligence in Genomics Market, By Functionality
12.1. Artificial Intelligence in Genomics Market, by Functionality, 2022-2030
12.1.1. Genome Sequencing
12.1.1.1. Market Revenue and Forecast (2017-2030)
12.1.2. Gene Editing
12.1.2.1. Market Revenue and Forecast (2017-2030)
12.1.3. Clinical Workflows
12.1.3.1. Market Revenue and Forecast (2017-2030)
12.1.4. Predictive Genetic Testing & Preventive Medicine
12.1.4.1. Market Revenue and Forecast (2017-2030)
Chapter 13. Global Artificial Intelligence in Genomics Market, Regional Estimates and Trend Forecast
13.1. North America
13.1.1. Market Revenue and Forecast, by Offering (2017-2030)
13.1.2. Market Revenue and Forecast, by Application (2017-2030)
13.1.3. Market Revenue and Forecast, by End User (2017-2030)
13.1.4. Market Revenue and Forecast, by Technology (2017-2030)
13.1.5. Market Revenue and Forecast, by Functionality (2017-2030)
13.1.6. U.S.
13.1.6.1. Market Revenue and Forecast, by Offering (2017-2030)
13.1.6.2. Market Revenue and Forecast, by Application (2017-2030)
13.1.6.3. Market Revenue and Forecast, by End User (2017-2030)
13.1.6.4. Market Revenue and Forecast, by Technology (2017-2030)
13.1.7. Market Revenue and Forecast, by Functionality (2017-2030)
13.1.8. Rest of North America
13.1.8.1. Market Revenue and Forecast, by Offering (2017-2030)
13.1.8.2. Market Revenue and Forecast, by Application (2017-2030)
13.1.8.3. Market Revenue and Forecast, by End User (2017-2030)
13.1.8.4. Market Revenue and Forecast, by Technology (2017-2030)
13.1.8.5. Market Revenue and Forecast, by Functionality (2017-2030)
13.2. Europe
13.2.1. Market Revenue and Forecast, by Offering (2017-2030)
13.2.2. Market Revenue and Forecast, by Application (2017-2030)
13.2.3. Market Revenue and Forecast, by End User (2017-2030)
13.2.4. Market Revenue and Forecast, by Technology (2017-2030)
13.2.5. Market Revenue and Forecast, by Functionality (2017-2030)
13.2.6. UK
13.2.6.1. Market Revenue and Forecast, by Offering (2017-2030)
13.2.6.2. Market Revenue and Forecast, by Application (2017-2030)
13.2.6.3. Market Revenue and Forecast, by End User (2017-2030)
13.2.7. Market Revenue and Forecast, by Technology (2017-2030)
13.2.8. Market Revenue and Forecast, by Functionality (2017-2030)
13.2.9. Germany
13.2.9.1. Market Revenue and Forecast, by Offering (2017-2030)
13.2.9.2. Market Revenue and Forecast, by Application (2017-2030)
13.2.9.3. Market Revenue and Forecast, by End User (2017-2030)
13.2.10. Market Revenue and Forecast, by Technology (2017-2030)
13.2.11. Market Revenue and Forecast, by Functionality (2017-2030)
13.2.12. France
13.2.12.1. Market Revenue and Forecast, by Offering (2017-2030)
13.2.12.2. Market Revenue and Forecast, by Application (2017-2030)
13.2.12.3. Market Revenue and Forecast, by End User (2017-2030)
13.2.12.4. Market Revenue and Forecast, by Technology (2017-2030)
13.2.13. Market Revenue and Forecast, by Functionality (2017-2030)
13.2.14. Rest of Europe
13.2.14.1. Market Revenue and Forecast, by Offering (2017-2030)
13.2.14.2. Market Revenue and Forecast, by Application (2017-2030)
13.2.14.3. Market Revenue and Forecast, by End User (2017-2030)
13.2.14.4. Market Revenue and Forecast, by Technology (2017-2030)
13.2.15. Market Revenue and Forecast, by Functionality (2017-2030)
13.3. APAC
13.3.1. Market Revenue and Forecast, by Offering (2017-2030)
13.3.2. Market Revenue and Forecast, by Application (2017-2030)
13.3.3. Market Revenue and Forecast, by End User (2017-2030)
13.3.4. Market Revenue and Forecast, by Technology (2017-2030)
13.3.5. Market Revenue and Forecast, by Functionality (2017-2030)
13.3.6. India
13.3.6.1. Market Revenue and Forecast, by Offering (2017-2030)
13.3.6.2. Market Revenue and Forecast, by Application (2017-2030)
13.3.6.3. Market Revenue and Forecast, by End User (2017-2030)
13.3.6.4. Market Revenue and Forecast, by Technology (2017-2030)
13.3.7. Market Revenue and Forecast, by Functionality (2017-2030)
13.3.8. China
13.3.8.1. Market Revenue and Forecast, by Offering (2017-2030)
13.3.8.2. Market Revenue and Forecast, by Application (2017-2030)
13.3.8.3. Market Revenue and Forecast, by End User (2017-2030)
13.3.8.4. Market Revenue and Forecast, by Technology (2017-2030)
13.3.9. Market Revenue and Forecast, by Functionality (2017-2030)
13.3.10. Japan
13.3.10.1. Market Revenue and Forecast, by Offering (2017-2030)
13.3.10.2. Market Revenue and Forecast, by Application (2017-2030)
13.3.10.3. Market Revenue and Forecast, by End User (2017-2030)
13.3.10.4. Market Revenue and Forecast, by Technology (2017-2030)
13.3.10.5. Market Revenue and Forecast, by Functionality (2017-2030)
13.3.11. Rest of APAC
13.3.11.1. Market Revenue and Forecast, by Offering (2017-2030)
13.3.11.2. Market Revenue and Forecast, by Application (2017-2030)
13.3.11.3. Market Revenue and Forecast, by End User (2017-2030)
13.3.11.4. Market Revenue and Forecast, by Technology (2017-2030)
13.3.11.5. Market Revenue and Forecast, by Functionality (2017-2030)
13.4. MEA
13.4.1. Market Revenue and Forecast, by Offering (2017-2030)
13.4.2. Market Revenue and Forecast, by Application (2017-2030)
13.4.3. Market Revenue and Forecast, by End User (2017-2030)
13.4.4. Market Revenue and Forecast, by Technology (2017-2030)
13.4.5. Market Revenue and Forecast, by Functionality (2017-2030)
13.4.6. GCC
13.4.6.1. Market Revenue and Forecast, by Offering (2017-2030)
13.4.6.2. Market Revenue and Forecast, by Application (2017-2030)
13.4.6.3. Market Revenue and Forecast, by End User (2017-2030)
13.4.6.4. Market Revenue and Forecast, by Technology (2017-2030)
13.4.7. Market Revenue and Forecast, by Functionality (2017-2030)
13.4.8. North Africa
13.4.8.1. Market Revenue and Forecast, by Offering (2017-2030)
13.4.8.2. Market Revenue and Forecast, by Application (2017-2030)
13.4.8.3. Market Revenue and Forecast, by End User (2017-2030)
13.4.8.4. Market Revenue and Forecast, by Technology (2017-2030)
13.4.9. Market Revenue and Forecast, by Functionality (2017-2030)
13.4.10. South Africa
13.4.10.1. Market Revenue and Forecast, by Offering (2017-2030)
13.4.10.2. Market Revenue and Forecast, by Application (2017-2030)
13.4.10.3. Market Revenue and Forecast, by End User (2017-2030)
13.4.10.4. Market Revenue and Forecast, by Technology (2017-2030)
13.4.10.5. Market Revenue and Forecast, by Functionality (2017-2030)
13.4.11. Rest of MEA
13.4.11.1. Market Revenue and Forecast, by Offering (2017-2030)
13.4.11.2. Market Revenue and Forecast, by Application (2017-2030)
13.4.11.3. Market Revenue and Forecast, by End User (2017-2030)
13.4.11.4. Market Revenue and Forecast, by Technology (2017-2030)
13.4.11.5. Market Revenue and Forecast, by Functionality (2017-2030)
13.5. Latin America
13.5.1. Market Revenue and Forecast, by Offering (2017-2030)
13.5.2. Market Revenue and Forecast, by Application (2017-2030)
13.5.3. Market Revenue and Forecast, by End User (2017-2030)
13.5.4. Market Revenue and Forecast, by Technology (2017-2030)
13.5.5. Market Revenue and Forecast, by Functionality (2017-2030)
13.5.6. Brazil
13.5.6.1. Market Revenue and Forecast, by Offering (2017-2030)
13.5.6.2. Market Revenue and Forecast, by Application (2017-2030)
13.5.6.3. Market Revenue and Forecast, by End User (2017-2030)
13.5.6.4. Market Revenue and Forecast, by Technology (2017-2030)
13.5.7. Market Revenue and Forecast, by Functionality (2017-2030)
13.5.8. Rest of LATAM
13.5.8.1. Market Revenue and Forecast, by Offering (2017-2030)
13.5.8.2. Market Revenue and Forecast, by Application (2017-2030)
13.5.8.3. Market Revenue and Forecast, by End User (2017-2030)
13.5.8.4. Market Revenue and Forecast, by Technology (2017-2030)
13.5.8.5. Market Revenue and Forecast, by Functionality (2017-2030)
Chapter 14. Company Profiles
14.1. IBM
14.1.1. Company Overview
14.1.2. Product Offerings
14.1.3. Financial Performance
14.1.4. Recent Initiatives
14.2. NVIDIA Corporation
14.2.1. Company Overview
14.2.2. Product Offerings
14.2.3. Financial Performance
14.2.4. Recent Initiatives
14.3. Benevolent AI
14.3.1. Company Overview
14.3.2. Product Offerings
14.3.3. Financial Performance
14.3.4. Recent Initiatives
14.4. Verge Genomics
14.4.1. Company Overview
14.4.2. Product Offerings
14.4.3. Financial Performance
14.4.4. Recent Initiatives
14.5. MolecularMatch, Inc.
14.5.1. Company Overview
14.5.2. Product Offerings
14.5.3. Financial Performance
14.5.4. Recent Initiatives
14.6. SOPHiA GENETICS
14.6.1. Company Overview
14.6.2. Product Offerings
14.6.3. Financial Performance
14.6.4. Recent Initiatives
14.7. PrecisionLife Ltd.
14.7.1. Company Overview
14.7.2. Product Offerings
14.7.3. Financial Performance
14.7.4. Recent Initiatives
14.8. Lifebit
14.8.1. Company Overview
14.8.2. Product Offerings
14.8.3. Financial Performance
14.8.4. Recent Initiatives
14.9. FDNA, Inc.
14.9.1. Company Overview
14.9.2. Product Offerings
14.9.3. Financial Performance
14.9.4. Recent Initiatives
14.10. Empiric Logic
14.10.1. Company Overview
14.10.2. Product Offerings
14.10.3. Financial Performance
14.10.4. Recent Initiatives
Chapter 15. Research Methodology
15.1. Primary Research
15.2. Secondary Research
15.3. Assumptions
Chapter 16. Appendix
16.1. About Us
16.2. Glossary of Terms
Contact Us:
Mr. Alex
Sales Manager
Call: +1 9197 992 333
Email: sales@precedenceresearch.com
0 Comments