March 4, 2024

Artificial Intelligence in Genomics Market Size to Worth Around US$ 5,972 million by 2030

[150+ Pages Report] As per the latest Research and survey report issued by Precedence Research, the global artificial intelligence in genomics market was valued at around USD 283.41 million in 2021 and is expected to register revenues worth USD 5,972 million by the end of 2030, growing at an exceptional CAGR of approximately 40.31% between 2022 and 2030.

Artificial Intelligence in Genomics

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Artificial Intelligence in Genomics Market Report Scope

A recent study by Precedence Research on the artificial intelligence in genomics market offers a forecast for 2022 and 2030. The study analyzes crucial trends that are currently determining the growth of the artificial intelligence in genomics market. This report explicates on vital dynamics such as the drivers, restraints, and opportunities for key market players, along with key stakeholders as well as emerging players associated with the manufacturing of artificial intelligence in genomics. The study also provides the dynamics that are responsible for influencing the future status of the artificial intelligence in genomics market over the forecast period.

A detailed assessment of the artificial intelligence in genomics market value chain analysis, business execution, and supply chain analysis across regional markets has been covered in the report. A list of prominent companies operating in the artificial intelligence in genomics market along with their product portfolio enhances the reliability of this comprehensive research study.

Competition Landscape

The report has engulfed a chapter on the global artificial intelligence in genomics market’s competitive landscape, which provides detailed analysis and insights on companies offering artificial intelligence in genomics. Profiles of key companies, along with a strategic overview of their M&A and expansion plans across geographies, have been delivered in this chapter. This chapter is priceless for report readers, as its enables them in gauging their growth potential in the market and implement key strategies for extending their market reach.

This chapter offers key recommendations for both new and existing market participants, enabling them to emerge sustainably and profitably. Intelligence on the market players has been delivered on the basis of their product overview, SWOT analysis, key developments, key financials and company overview. Occupancy of these market participants has been tracked by the report and portrayed via an intensity map.

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Some of the Prominent Players in the 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.
Artificial Intelligence in Genomics 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 Segmentation

  • Asia-Pacific [China, Southeast Asia, India, Japan, Korea, Western Asia]
  • Europe [Germany, UK, France, Italy, Russia, Spain, Netherlands, Turkey, Switzerland]
  • North America [United States, Canada, Mexico]
  • South America [Brazil, Argentina, Columbia, Chile, Peru]
  • Middle East & Africa [GCC, North Africa, South Africa]

Regional Analysis

The research report includes a detailed study of regions of North America, Europe, China, Japan and Rest of the World. The report has been curated after observing and studying various factors that determine regional growth such as economic, environmental, social, technological, and political status of the particular region. Analysts have studied the data of revenue and manufacturers of each region. This section analyses region-wise revenue and volume for the forecast period of 2022 to 2030. These analyses will help the reader to understand the potential worth of investment in a particular region.

The report provides in-depth segment analysis of the global artificial intelligence in genomics market, thereby providing valuable insights at macro as well as micro levels. Analysis of major countries, which hold growth opportunities or account for significant share has also been included as part of geographic analysis of the artificial intelligence in genomics market.

The report includes country-wise and region-wise market size for the period 2022-2030. It also includes market size and forecast by segments in terms of production capacity, price and revenue for the period 2022-2030.

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.

Table of Contents

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

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Janet Edward

I have completed my education in Bachelors in Computer Application. A focused learner having a keen interest in the field of digital marketing, SEO, SMM, and Google Analytics enthusiastic to learn new things along with building leadership skills.

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