세계의 유전체학 AI 시장 평가 : 제공별, 기술별, 기능별, 용도별, 최종사용자별, 지역별, 기회, 예측(2017-2031년)

Global AI in genomics market is projected to witness a CAGR of 39.17% during the forecast period 2024-2031, growing from USD 633.60 million in 2023 to USD 8914.51 million in 2031. The market's growth is supported by the advancements in artificial intelligence (AI), rising generation of genomic data, growing requirement for acceleration of drug development processes, increasing cases of chronic diseases, and expansion of geriatric population. The integration of AI with genomics allows the analyses of large amounts of data in an accurate and time efficient manner and AI algorithms aiding in predicting risk of diseases, developing targeted therapies, and identifying genetic mutations, allowing the healthcare professionals to provide enhanced patient care and making informed decisions.

The rising requirement for personalized medicines is another major factor boosting the global AI in genomics market growth as genomic information aids researchers and scientists in studying the individual responses to the drugs while the integration with AI allows for analyses of larger volumes of data in a time efficient manner. The AI algorithms aid in developing targeted therapies, identifying genetic mutations, and predicting the risk of disease.

Additionally, the increasing cases of cancer is another major factor augmenting the global AI in genomics market size. As per the estimates of the National Cancer Institute, approximately 2,001,140 new cases of cancer are expected to be diagnosed in 2024 in the United States. The increase is propelling the efforts towards the research activities, including research in genomic changes in cancer patients to support the development of cancer related drugs that aid in inhibiting enzyme responses responsible for abnormal growth, halting molecular signaling pathways, and blocking characteristics of cancer cells that are responsible for gene expression.

Rising Requirement for Accelerated Drug Development Process Boosts Market Growth

Due to the growth of aging population and rising cases of genetic, chronic, and infectious diseases, the acceleration of drug development process is becoming essential. According to the estimates of the World Health Organization (WHO), the population of individuals of age sixty and above is expected to increase to 2.1 billion, by 2050. Various drug candidates that are selected during the discovery phase of the drug development processes fail to cross late stages due to unfavorable pharmacokinetic properties and toxicity. AI and machine learning technologies aid in target validation and identification, discovery of biomarkers, repurposing of drugs, and optimization of clinical trials by analyzing the effects of drugs on various genetic populations and shortening the development timeline. The AI models can predict the effectiveness of targeting specific pathways and genes, stimulating the effects of different drugs and indicating how a certain group of patients respond to specific treatments. It in turn aids researchers in speeding the drug development process, allowing them to meet the rising requirements.

Increasing Investments Towards Genomic Projects Boosts Market Demand

The rising investments by different governments towards genomics projects is one of the major factors boosting the global AI in genomics market demand as AI aids in enhancing and accelerating the analysis of the generated data. In February 2024, the Department of Biotechnology announced that they had completed the Genome India Project and conducted sequencing of 10,000 genomes. Twenty institutions across the country collected gene samples from ninety-nine ethnic groups, creating a reference of genetic database for utilization in future research activities. Such investments and initiatives are bolstering the generation of genomic data and augmenting the growth of the market as various AI algorithms allow for effective management of data and analysis of complex data sets.

Pharmaceutical and Biotech Companies Hold Significant Market Share

The rapid expansion of pharmaceutical and biotech companies due to the increasing cases of genetic diseases is supporting the market's growth. As per the estimates of the American Lung Association, approximately 30,000 people in the United States have cystic fibrosis, and around 1 in 30 Americans is a carrier. Machine learning and artificial intelligence aid pharmaceutical and biotech companies to automate prediction and prevention of disease, along with efficient management of clinical data that predict toxicity of potential compounds, preventing them from use in drugs that have a higher probability of failing. It in turn will allow the companies to invest in effective therapeutic solutions, thus enhancing the patient outcomes.

Meanwhile, hospitals are expected to witness significant growth in the forecast years, it can be attributed to the rising investments in personalized medicines and rising adoption of AI for management of large data sets.

North America Expected to Hold Significant Market Share

The market growth in North America is supported by the strong presence of research institutions and biotech and genomic companies in the region, coupled with rising investments towards the development of AI powered solutions for applications in genomics. The rising investments in genomics can be attributed to the wide range of applications of the sector in healthcare and possible breakthroughs that could provide a cure for diseases and disorders that were earlier deemed without course or fatal. The rising prevalence of cancer in the region is another major factor, due to which investments in genomics are increasing, which in turn, is providing lucrative growth opportunities for the market. As per the estimates of the National Cancer Institute, 2,001,140 new cases of cancer are expected to be diagnosed in the United States in 2024.

Meanwhile, market is expected to witness significant growth in Asia-Pacific in the forecast years, owing to the increasing government initiatives in the region as genome sequencing in combination with phenotype, microbiome, and clinical information will allow for an enhanced analysis of healthy and disease affected individuals on the basis of inferred local ancestries.

Future Market Scenario (2024 - 2031F)

AI is expected to accelerate the analysis of massive genome sequencing data. The rising investments in research and development activities are expected to support the expansion of the market. The Hospital Universitari Vall d'Hebron Research Institute is conducting an observational study for improving the SCD prognosis and classification by AI. The study aims to advance disease characterization for improving health outcomes by developing individual models in sickle cell disease and identifying biomarkers. The development of the GENOMED4ALL AI algorithm for the sickle cell disease will allow in-depth characterization and the prediction of various complications associated with the disease. The primary endpoints of interest include the development of a probability score for predicting different patterns recognized by AI, development of predictive risk scores for occurrences of severe and prevalent clinical outcomes, and improved sickle cell disease classification. The study is expected to conclude in December 2024.

Key Players Landscape and Outlook

The growth of AI in genomics market is supported by the rising collaborations and partnerships between the key players of the market and leading biotechnology companies. In June 2024, Helix, Inc. announced partnership with Recursion Pharmaceuticals that will combine the company's clinic-genomic dataset with over 25 petabytes of the latter's chemical and biological data. Such collaborations will aid scientists in gathering more information about the correlation between genes and diseases and the availability of genetic information, allowing them to identify patients that could aid from preventive measures or specific treatments. This will aid healthcare professionals and reduce costs related to duplicate testing, resulting in efficient utilization of resources.

Table of Contents

1. Project Scope and Definitions

2. Research Methodology

3. Executive Summary

4. Global AI in Genomics Market Outlook, 2017-2031F

• 4.1. Market Size Analysis & Forecast
  • 4.1.1. By Value
• 4.2. Market Share Analysis & Forecast
  • 4.2.1. By Offering
    • 4.2.1.1. Software
    • 4.2.1.2. Services
  • 4.2.2. By Technology
    • 4.2.2.1. Machine Learning
      • 4.2.2.1.1. Deep Learning
      • 4.2.2.1.2. Supervised Learning
      • 4.2.2.1.3. Unsupervised Learning
      • 4.2.2.1.4. Reinforcement Learning
      • 4.2.2.1.5. Others
    • 4.2.2.2. Computer Vision
  • 4.2.3. By Functionality
    • 4.2.3.1. Genome Sequencing
    • 4.2.3.2. Clinical Workflow
    • 4.2.3.3. Predictive Genetic Testing and Preventive Medicine
    • 4.2.3.4. Gene Editing
  • 4.2.4. By Application
    • 4.2.4.1. Drug Discovery and Development
    • 4.2.4.2. Precision Medicine
    • 4.2.4.3. Diagnostics
    • 4.2.4.4. Agriculture and Animal Research
    • 4.2.4.5. Others
  • 4.2.5. By End-user
    • 4.2.5.1. Pharmaceutical and Biotech Companies
    • 4.2.5.2. Healthcare Providers
    • 4.2.5.3. Research Centers
    • 4.2.5.4. Others
  • 4.2.6. By Region
    • 4.2.6.1. North America
    • 4.2.6.2. Europe
    • 4.2.6.3. Asia-Pacific
    • 4.2.6.4. South America
    • 4.2.6.5. Middle East and Africa
  • 4.2.7. By Company Market Share Analysis (Top 5 Companies and Others - By Value, 2023)
• 4.3. Market Map Analysis, 2023
  • 4.3.1. By Offering
  • 4.3.2. By Technology
  • 4.3.3. By Functionality
  • 4.3.4. By Application
  • 4.3.5. By End-user
  • 4.3.6. By Region

5. North America AI in Genomics Market Outlook, 2017-2031F*

• 5.1. Market Size Analysis & Forecast
  • 5.1.1. By Value
• 5.2. Market Share Analysis & Forecast
  • 5.2.1. By Offering
    • 5.2.1.1. Software
    • 5.2.1.2. Services
  • 5.2.2. By Technology
    • 5.2.2.1. Machine Learning
      • 5.2.2.1.1. Deep Learning
      • 5.2.2.1.2. Supervised Learning
      • 5.2.2.1.3. Unsupervised Learning
      • 5.2.2.1.4. Reinforcement Learning
      • 5.2.2.1.5. Others
    • 5.2.2.2. Computer Vision
  • 5.2.3. By Functionality
    • 5.2.3.1. Genome Sequencing
    • 5.2.3.2. Clinical Workflow
    • 5.2.3.3. Predictive Genetic Testing and Preventive Medicine
    • 5.2.3.4. Gene Editing
  • 5.2.4. By Application
    • 5.2.4.1. Drug Discovery and Development
    • 5.2.4.2. Precision Medicine
    • 5.2.4.3. Diagnostics
    • 5.2.4.4. Agriculture and Animal Research
    • 5.2.4.5. Others
  • 5.2.5. By End-user
    • 5.2.5.1. Pharmaceutical and Biotech Companies
    • 5.2.5.2. Healthcare Providers
    • 5.2.5.3. Research Centers
    • 5.2.5.4. Others
  • 5.2.6. By Country Share
    • 5.2.6.1. United States
    • 5.2.6.2. Canada
    • 5.2.6.3. Mexico
• 5.3. Country Market Assessment
  • 5.3.1. United States AI in Genomics Market Outlook, 2017-2031F*
    • 5.3.1.1. Market Size Analysis & Forecast
      • 5.3.1.1.1. By Value
    • 5.3.1.2. Market Share Analysis & Forecast
      • 5.3.1.2.1. By Offering
        • 5.3.1.2.1.1. Software
        • 5.3.1.2.1.2. Services
      • 5.3.1.2.2. By Technology
        • 5.3.1.2.2.1. Machine Learning
        • 5.3.1.2.2.1.1. Deep Learning
        • 5.3.1.2.2.1.2. Supervised Learning
        • 5.3.1.2.2.1.3. Unsupervised Learning
        • 5.3.1.2.2.1.4. Reinforcement Learning
        • 5.3.1.2.2.1.5. Others
        • 5.3.1.2.2.2. Computer Vision
      • 5.3.1.2.3. By Functionality
        • 5.3.1.2.3.1. Genome Sequencing
        • 5.3.1.2.3.2. Clinical Workflow
        • 5.3.1.2.3.3. Predictive Genetic Testing and Preventive Medicine
        • 5.3.1.2.3.4. Gene Editing
      • 5.3.1.2.4. By Application
        • 5.3.1.2.4.1. Drug Discovery and Development
        • 5.3.1.2.4.2. Precision Medicine
        • 5.3.1.2.4.3. Diagnostics
        • 5.3.1.2.4.4. Agriculture and Animal Research
        • 5.3.1.2.4.5. Others
      • 5.3.1.2.5. By End-user
        • 5.3.1.2.5.1. Pharmaceutical and Biotech Companies
        • 5.3.1.2.5.2. Healthcare Providers
        • 5.3.1.2.5.3. Research Centers
        • 5.3.1.2.5.4. Others
  • 5.3.2. Canada
  • 5.3.3. Mexico

All segments will be provided for all regions and countries covered

6. Europe AI in Genomics Market Outlook, 2017-2031F

• 6.1. Germany
• 6.2. France
• 6.3. Italy
• 6.4. United Kingdom
• 6.5. Russia
• 6.6. Netherlands
• 6.7. Spain
• 6.8. Poland

7. Asia-Pacific AI in Genomics Market Outlook, 2017-2031F

• 7.1. India
• 7.2. China
• 7.3. Japan
• 7.4. Australia
• 7.5. Vietnam
• 7.6. South Korea
• 7.7. Indonesia
• 7.8. Philippines

8. South America AI in Genomics Market Outlook, 2017-2031F

• 8.1. Brazil
• 8.2. Argentina

9. Middle East and Africa AI in Genomics Market Outlook, 2017-2031F

• 9.1. Saudi Arabia
• 9.2. UAE
• 9.3. South Africa
• 9.4. Israel

10. Demand Supply Analysis

11. Import and Export Analysis

12. Value Chain Analysis

13. Porter's Five Forces Analysis

14. PESTLE Analysis

15. Pricing Analysis

16. Market Dynamics

• 16.1. Market Drivers
• 16.2. Market Challenges

17. Market Trends and Developments

18. Regulatory Framework and Innovation

• 18.1. Clinical Trials
• 18.2. Regulatory Approvals

19. Patent Landscape

20. Case Studies

21. Competitive Landscape

• 21.1. Competition Matrix of Top 5 Market Leaders
• 21.2. SWOT Analysis for Top 5 Players
• 21.3. Key Players Landscape for Top 10 Market Players
  • 21.3.1. Intel Services
    • 21.3.1.1. Company Details
    • 21.3.1.2. Key Management Personnel
    • 21.3.1.3. Products and Services
    • 21.3.1.4. Financials (As Reported)
    • 21.3.1.5. Key Market Focus and Geographical Presence
    • 21.3.1.6. Recent Developments/Collaborations/Partnerships/Mergers and Acquisition
  • 21.3.2. Illumina, Inc.
  • 21.3.3. Thermo Fisher Scientific Inc.
  • 21.3.4. NVIDIA Corporation
  • 21.3.5. Microsoft Corporation
  • 21.3.6. International Business Machines Corporation
  • 21.3.7. SOPHiA GENETICS
  • 21.3.8. BenevolentAI Group
  • 21.3.9. Helix, Inc.
  • 21.3.10. Deep Genomics Incorporated

Companies mentioned above DO NOT hold any order as per market share and can be changed as per information available during research work.

22. Strategic Recommendations

23. About Us and Disclaimer