Artificial Intelligence in Genomics Market to Reach USD 19,018.4 Million by 2032 Driven by Rise of Technological Advancement and Increased Demand for Precision Medicine | Research by SNS Insider

The Artificial Intelligence in Genomics Market has been experiencing a healthy growth curve, fostered by ever-accelerating investments in research genomic activities, coupled with increasing adoption of AI-based solutions across healthcare sectors.

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Austin, Oct. 29, 2024 (GLOBE NEWSWIRE) -- According to SNS Insider, The Artificial Intelligence in Genomics Market valued at USD 699.7 million in 2023 is estimated to reach USD 19,018.4 million by 2032, growing at a CAGR of 44.3% over the forecast period from 2024 to 2032.

Market Overview

At the forefront of a revolutionary trend in healthcare technology, Artificial Intelligence in Genomics uses machine learning, data analytics, and advanced computational techniques to improve the facets of genomic research and clinical applications. This has, in turn, fuelled the need for advanced AI solutions that could process such enormous amounts of genomic data and trace them back to the respective genetic variants causally associated with diseases, enabling personalization of treatment plans and drug discovery acceleration. The market is driven by a significantly increasing public and private investment aimed at developing AI tools for the development and performance of genomics, in addition to an increasing concern for precision medicine tailored to the genetic profile of every individual. Further, the state-of-the-art infrastructure in the healthcare sector, with the ongoing commercialization of AI in applications of genomic investigation such as clinical trials, diagnosis, and patient management, is driving the growth of the market. These factors assert a strong direction toward data-driven healthcare, thus providing it a lucrative arena for the growth of AI in genomics.


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Major Players Analysis Listed in this Report are:

  • IBM
  • Microsoft Corporation
  • NVIDIA Corporation
  • DEEP GENOMICS
  • Data4Cure Inc.
  • Freenome Holdings Inc.
  • Thermo Fisher Scientific
  • Illumina Inc.
  • SOPHiA GENETICS
  • BenevolentAI
  • Fabric Genomics
  • Other Players

Artificial Intelligence in Genomics Market Report Scope:

Report Attributes Details
Market Size in 2023 US$ 699.7 million 
Market Size by 2032 US$ 19018.4 million 
CAGR CAGR of 44.3% From 2024 to 2032
Base Year 2023
Forecast Period 2024-2032
Historical Data 2020-2022
Regional Analysis/Coverage North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe] Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]), Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia, Rest of Latin America)
Key Drivers • Pioneering Advances in Data Management and Drug Development

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Segment Analysis

By Component:

In 2023, the software segment accounted for more than 40% of the total share. It will grow at the highest CAGR of 46.6% during the forecast period. This is due to the growing adoption of AI-based software solutions in healthcare institutions and R&D centers. AI technologies are integrated into various healthcare applications, including cybersecurity, telemedicine, and clinical trials, which themselves are driving the fast growth of this segment. Public and private sector initiatives, such as the release of open-source AI software by Illumina, Inc. in July 2018, are fueling this growth.

By Technology

The market can also be segregated into the sub-segments of machine learning and computer vision. The machine learning segment held approximately 63% of the market share in the year 2023 and is expected to witness maximum CAGR during the forecast period. Machine learning algorithms are highly advantageous for the automation of labor-intensive tasks such as annotating genomic data and discovering drug targets, thereby enhancing the productivity of genomic research.

Artificial Intelligence in Genomics Market Key Segmentation:

By Component

  • Hardware
  • Software
  • Services

By Technology

  • Machine Learning
    • Deep Learning
    • Supervised Learning
    • Unsupervised Learning
    • Others
  • Computer Vision

By Functionality

  • Genome Sequencing
  • Gene Editing
  • Others

By Application

  • Drug Discovery & Development
  • Precision Medicine
  • Diagnostics
  • Others

By End-use

  • Pharmaceutical and Biotech Companies
  • Healthcare Providers
  • Research Centers
  • Others

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Regional Analysis

North America:

In 2023, North America dominated the artificial intelligence in the genomics market at about 29%. This supremacy is accounted for due to prominent market players, significant investments in genomic studies, and modern health infrastructure. Leading companies such as IBM and Thermo Fisher Scientific are propelling AI in genomics solutions with improved diagnosis and therapeutic activity. Well-funded research institutions in this region significantly augment the development and application of AI technologies in genomics, increasing the supremacy position.

The Artificial Intelligence in Genomics market in the Asia Pacific is expected to be the biggest-growing region during the forecast period, at a CAGR of 47.1% by the end. Rising healthcare spending and emphasis on precision medicine have been driving this growth. Besides, investments in this region have been promoted by national genomics projects. For example, national genomics initiatives are established in countries such as Thailand. An example of this is an approved government project, valued at USD 150 million in 2019, which would describe the genomes of 50,000 citizens. These are samples of development in the region regarding enhancing genomic research capabilities and health outcomes.

Recent Trends

  • October 2023: A new AI tool called EXPRESSO was invented to predict genetic risk for autoimmune disease using genomic data, epigenetics, and related information.
  • February 2023: Accenture Ventures invested in Ocean Genomics, a biopharma diagnostics and therapeutics firm focused on developing AI-driven platforms.
  • August 2023: Illumina introduced an AI software suite that helps interpret genomic data and optimize clinical workflows.
  • September 2023: BenevolentAI made its advanced algorithm for machine learning available for drug discovery. This will save a great deal of time in identifying potential therapeutic targets from genomic data.
  • January 2024: NVIDIA launched a new GPU-accelerated platform for genomic data processing and analysis, helping healthcare providers to deliver better services.
  • March 2024: Fabric Genomics has launched a plant form of AI-enhanced personalized medicine focused entirely on incorporating genomic data into the creation of treatments tailored to specific patient needs.

In short, the Artificial Intelligence in Genomics market will grow with the pace of technological advancement, increased adoption of precision medicine, and huge investments in genomic R&D. The integration of AI into genomics improves research capabilities, transforms patient care, and leads to improved health outcomes for populations around the world.


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Table of Contents – Major Key Points

1. Introduction

2. Executive Summary

3. Research Methodology

4. Market Dynamics Impact Analysis

5. Statistical Insights and Trends Reporting

6. Competitive Landscape

7. Artificial Intelligence in Genomics Market Segmentation, by Component

8. Artificial Intelligence in Genomics Market Segmentation, by Technology

9. Artificial Intelligence in Genomics Market Segmentation, by Functionality

10. Artificial Intelligence in Genomics Market Segmentation, by Application

11. Artificial Intelligence in Genomics Market Segmentation, by End-use

12. Artificial Intelligence in Genomics Market Segmentation, by Regional Analysis

13. Company Profiles

14. Use Cases and Best Practices

15. Conclusion

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