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Report Scope & Overview:

The Artificial Intelligence in Genomics Market Size was valued at USD 464.50 million in 2022, and is expected to reach USD 13096 million by 2030, and grow at a CAGR of 51.8% over the forecast period 2023-2030.

Genomics is a branch of science that studies genes and their functions, as well as the structure, evolution, and mapping of genomes in living things. Genetic testing is used to learn about disease inclinations, treatment response, and general human biology. Genomics research includes structural and functional studies, DNA sequencing, bioinformatics sequencing, and combined DNA. The use of artificial intelligence (AI) in genomics focuses on the development of computer systems that can perform tasks such as genome mapping.

Artificial Intelligence In Genomics Market Revenue Analysis

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Furthermore, AI aids in the faster study of genetic material's structure, evolution, and function than is achievable with human interaction. Although AI algorithms are designed to simulate human intelligence, they are also utilised in clinical genomics to undertake genomic analysis such as genome annotation, variant calling, phenotype-to-genotype correspondence, and genome annotation. In addition, AI approaches can aid in the accurate prediction of protein structure or DNA data with minimal feature handcrafting. Genomic medicine has a crucial role to play in customized medicine. In this field, AI can help in the production of drugs.

MARKET DYNAMICS

DRIVERS

  • Controlling the time and expense of medication development and discovery is essential.

  • Increasing the amount of money spent on AI in genomics

  • AI is being more widely used in precision medicine.

  • Increasing the size of genomic datasets

RESTRAINTS

  • Medical software regulations are vague, and there is a shortage of competent AI workers.

OPPORTUNITIES

  • Prioritize the development of AI systems that are human-aware.

CHALLENGES

  • There is a scarcity of curated genetic information.

  • Concerns about data security

IMPACT OF COVID-19

The global outbreak of COVID-19 resulted in a long-term decline in the healthcare industry. COVID-19 caused havoc on major world economies and communities, particularly in the healthcare sector. In reaction to the rapidly changing environment, key stakeholders are continuing to alter their strategies. The healthcare business is projected to be affected by COVID-19 in the long run. Until the crisis passes, countries and large actors will have to make considerable changes to their healthcare systems. Technological breakthroughs, cost control, and increased access are all projected to occur in the near future in the healthcare industry. In the present pandemic, digital health and telemedicine have taken center stage.

Remote diagnosis, care, and consultation were all highlighted again during COVID-19. Telehealth's growth has stalled in recent years due to governmental and behavioural constraints. The segment is expected to grow over the next two years, as many healthcare providers are focusing on video conferencing and telephone calls. Patients with moderate symptoms were also required to consult online under the social distancing measures. Furthermore, it alleviated the strain on hospitals that were already overburdened with COVID-19 patient counts. At-home medical IoT devices are already being utilised to optimize outpatient therapy and reduce recurrent visits, and these devices can also be employed in a crisis. The pandemic caused serious resource shortages. This is projected to lead to the creation of competitive pricing and value-based pricing structures, bolstering the AI in genomics market's growth.

Based on Offerings, the market is divided into Software and Services. AI can take the form of software or instruments that can resemble human intelligence in some situations and even outperform it in others. As the complexity of genetic data grows, researchers are turning to AI and machine learning to uncover important correlations. Machine learning and computer perspective are the two main components of the market. Pharmaceutical companies, contract research organizations, and biotechnology companies all used machine learning in the use of genomics drugs, which dominated the market. This is because machine learning can extract data from large data sets, speeding up genetic research.

Genome Sequencing, Gene Editing, and Gene Mapping are the three segments of the market. Traditional operations and medications are anticipated to be replaced as gene therapy advances. Healthcare practitioners will be able to treat an illness by putting a gene into their patients' cells. The discovery of gene editing is both delicate and strong. For a long time, it's been a source of debate, discussion, and, despite flaws, excitement and invention.

Pharmaceutical biotechnology businesses, healthcare providers, research institutes, educational institutions, and government agencies, as well as other end users, are building AI in the genomics market. The pharmaceutical and biotechnology industries are holding the highest market share for end users. The growing demand for solutions to reduce time and cost of drug development is driving market growth.

KEY MARKET SEGMENTATION

By Offering Type

  • Software

  • Services

By Technology

  • Machine Learning

  • Deep Learning

  • Supervised Learning

  • Reinforcement Learning

  • Unsupervised Learning

By Functionality

  • Genome Sequencing

  • Gene Editing

  • Clinical Workflows

  • Predictive Genetic Testing & Preventive Medicine

By end user

  • Pharmaceutical & Biotech Companies

  • Healthcare Providers

  • Research Centers, Academic Institutes, &

  • Government Organizations

Artificial Intelligence In Genomics Market Segmentation Analysis

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REGIONAL ANALYSIS

North America dominated the AI in genomics market, followed by Europe. North America's substantial proportion can be ascribed to increased research funding and government activities in the United States to promote precision medicine.

KEY PLAYERS:

Some of the major key players are as follows: IBM, Cambridge Cancer Genomics, NVIDIA Corporation, Verge Genomics, Molecular Match Inc., Deep Genomics, Microsoft, Free nome Holdings, Inc., Benevolent AI, Fabric Genomics Inc. and Other Players

REGIONAL COVERAGE:

  • North America

    • USA

    • Canada

    • Mexico

  • Europe

    • Germany

    • UK

    • France

    • Italy

    • Spain

    • The Netherlands

    • Rest of Europe

  • Asia-Pacific

    • Japan

    • south Korea

    • China

    • India

    • Australia

    • Rest of Asia-Pacific

  • The Middle East & Africa

    • Israel

    • UAE

    • South Africa

    • Rest of Middle East & Africa

  • Latin America

    • Brazil

    • Argentina

    • Rest of Latin America

Artificial Intelligence in Genomics Market Report Scope:
Report Attributes Details
Market Size in 2022 US$ 464.50 Million
Market Size by 2030 US$ 13096 Million
CAGR CAGR of 51.8% From 2023 to 2030
Base Year 2022
Forecast Period 2023-2030
Historical Data 2020-2021
Report Scope & Coverage Market Size, Segments Analysis, Competitive  Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook
Key Segments • By Offering Type (Software, Services)
• By Technology (Machine Learning, Deep Learning, Supervised Learning, Reinforcement Learning, Unsupervised Learning)
• By Functionality (Genome Sequencing, Gene Editing, Clinical Workflows, Predictive Genetic Testing & Preventive Medicine)
• By end user (Pharmaceutical & Biotech Companies, Healthcare Providers, Research Centers, Academic Institutes, Government Organizations)
Regional Analysis/Coverage North America (USA, Canada, Mexico), Europe
(Germany, UK, France, Italy, Spain, Netherlands,
Rest of Europe), Asia-Pacific (Japan, South Korea,
China, India, Australia, Rest of Asia-Pacific), The
Middle East & Africa (Israel, UAE, South Africa,
Rest of Middle East & Africa), Latin America (Brazil, Argentina, Rest of Latin America)
Company Profiles IBM, Cambridge Cancer Genomics, NVIDIA Corporation, Verge Genomics, Molecular Match Inc., Deep Genomics, Microsoft, Free nome Holdings, Inc., Benevolent AI, Fabric Genomics Inc.
DRIVERS • Controlling the time and expense of medication development and discovery is essential.
• Increasing the amount of money spent on AI in genomics
• AI is being more widely used in precision medicine.
RESTRAINTS • Medical software regulations are vague, and there is a shortage of competent AI workers.

Frequently Asked Questions

Ans: The Artificial Intelligence in Genomics market size was valued at US$ 464.50 Mn in 2022.

Genome Sequencing, Gene Editing, Clinical Workflows, and Predictive Genetic Testing & Preventive Medicine are the sub segments of Artificial Intelligence in Genomics market.

Key drivers of the Artificial Intelligence in Genomics Market is Increasing the amount of money spent on AI in genomics, and AI is being more widely used in precision medicine

The use of artificial intelligence (AI) in genomics focuses on the development of computer systems that can perform tasks such as genome mapping. Furthermore, AI aids in the faster study of genetic material's structure, evolution, and function than is achievable with human interaction.

Ans: The Artificial Intelligence in Genomics Market is to grow at a CAGR of 51.8% during the forecast period 2023-2030.

Table of Contents

 

1. Introduction

1.1 Market Definition

1.2 Scope

1.3 Research Assumptions

 

2. Research Methodology

 

3. Market Dynamics

3.1 Drivers

3.2 Restraints

3.3 Opportunities

3.4 Challenges

 

4. Impact Analysis

4.1 COVID-19 Impact Analysis

4.2 Impact of Ukraine- Russia war

4.3 Impact of ongoing Recession

4.3.1 Introduction

4.3.2 Impact on major economies

4.3.2.1 US

4.3.2.2 Canada

4.3.2.3 Germany

4.3.2.4 France

4.3.2.5 United Kingdom

4.3.2.6 China

4.3.2.7 Japan

4.3.2.8 South Korea

4.3.2.9 Rest of the World

 

5. Value Chain Analysis

 

6. Porter’s 5 forces model

 

7.  PEST Analysis

  

8. Artificial Intelligence in Genomics Market Segmentation, By Offering Type

8.1 Software

8.2 Services

 

9. Artificial Intelligence in Genomics Market Segmentation, By Technology

9.1 Machine Learning

9.2 Deep Learning

9.3 Supervised Learning

9.4 Reinforcement Learning

9.5 Unsupervised Learning

 

10. Artificial Intelligence in Genomics Market Segmentation, By Functionality

10.1 Genome Sequencing

10.2 Gene Editing

10.3 Clinical Workflows

10.4 Predictive Genetic Testing & Preventive Medicine

 

11. Artificial Intelligence in Genomics Market Segmentation, By end user

11.1 Pharmaceutical & Biotech Companies

11.2 Healthcare Providers

11.3 Research Centers, Academic Institutes

11.4 Government Organizations

 

12. Regional Analysis

12.1 Introduction

12.2 North America

12.2.1 USA

12.2.2 Canada

12.2.3 Mexico

12.3 Europe

12.3.1 Germany

12.3.2 UK

12.3.3 France

12.3.4 Italy

12.3.5 Spain

12.3.6 The Netherlands

12.3.7 Rest of Europe

12.4 Asia-Pacific

12.4.1 Japan

12.4.2 South Korea

12.4.3 China

12.4.4 India

12.4.5 Australia

12.4.6 Rest of Asia-Pacific

12.5 The Middle East & Africa

12.5.1 Israel

12.5.2 UAE

12.5.3 South Africa

12.5.4 Rest

12.6 Latin America

12.6.1 Brazil

12.6.2 Argentina

12.6.3 Rest of Latin America

 

13. Company Profiles

13.1 IBM

13.1.1 Financial

13.1.2 Products/ Services Offered

13.1.3 SWOT Analysis

13.1.4 The SNS view

13.2 Cambridge Cancer Genomics

13.3 NVIDIA Corporation

13.4 Verge Genomics

13.5 Molecular Match Inc.

13.6 Deep Genomics

13.7 Microsoft

13.8 Free nome Holdings, Inc.

13.9 Benevolent AI

13.10 Fabric Genomics Inc.

 

14. Competitive Landscape

14.1 Competitive Benchmark

14.2 Market Share Analysis

14.3 Recent Developments

 

15. Conclusion

An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.

Each report that we prepare takes a timeframe of 350-400 business hours for production. Starting from the selection of titles through a couple of in-depth brain storming session to the final QC process before uploading our titles on our website we dedicate around 350 working hours. The titles are selected based on their current market cap and the foreseen CAGR and growth.

 

The 5 steps process:

Step 1: Secondary Research:

Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.

Secondary Research

Step 2: Primary Research

When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data.  This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.

We at SNS Insider have divided Primary Research into 2 parts.

Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.

This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.

Primary Research

Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.

Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.

Step 3: Data Bank Validation

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Data Bank Validation

Step 4: QA/QC Process

After all the data collection and validation our team does a final level of quality check and quality assurance to get rid of any unwanted or undesired mistakes. This might include but not limited to getting rid of the any typos, duplication of numbers or missing of any important information. The people involved in this process include technical content writers, research heads and graphics people. Once this process is completed the title gets uploader on our platform for our clients to read it.

Step 5: Final QC/QA Process:

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