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Global AI In Genomics Market to reach USD 7040.69 million by the end of 2029.

Global AI In Genomics Market Size study & Forecast, by Component (Hardware, Software, Services), By Technology (Machine Learning, 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), and Regional Analysis, 2022-2029

Product Code: HLSB-21321366
Publish Date: 5-05-2023
Page: 200

Global AI In Genomics Market is valued at approximately USD 341.03 million in 2021 and is anticipated to grow with a healthy growth rate of more than 46.0% over the forecast period 2022-2029. Artificial intelligence (AI) is used in genomics to create computer systems that can carry out tasks such as mapping genomes. The structure, evolution, and function of genetic material are also explored with AI more quickly than with human participation. Although the primary goal of AI algorithms is to replicate human intelligence, clinical genomics is geared at performing genomic analysis, which phenotype-to-genotype correspondence, comprises variant calling, genome annotation, and genome annotation. Moreover, AI techniques can assist in immediately predicting DNA or protein structure that does not feature handcrafting. The increasing government investments, the surge in the adoption of AI in precision medicine, the reduction in cost and time for genome sequencing, and rising genomic datasets are the key factors that are fostering market growth across the globe.

Moreover, the rising investment in research of personalized medicine is also fueling the market demand at a substantial rate. As per Statista, in 2019, the global market for personalized medicine market was estimated to be worth around USD 1,980 billion, which is projected to reach USD 2,770 billion by the year 2022. Consequentially, the growing focus on the research of personalized medicine is associated with the growth of the AI In Genomics Market. In addition, the rising emphasis on developing human-aware AI systems, as well as the increasing advancement in the field of gene therapy are presenting various lucrative opportunities over the forecasting years. However, the dearth of skilled AI professionals and stringent regulatory framework are hindering market growth over the forecast period of 2022-2029.

The key regions considered for the Global AI In Genomics Market study include Asia Pacific, North America, Europe, Latin America, and the Rest of the World. North America dominated the market in terms of revenue, owing to the growing investment in R&D, rising advancements in AI-powered solutions for genomics, and the introduction of new software and tools for genomic data analysis. Whereas, Asia Pacific is expected to grow at the highest growth rate over the forecasting period. Factors such as the growing population, rising healthcare spending, increasing focus on precision medicine, and rapid advances in genomics technology are burgeoning the market growth in the forecasting years.

Major market players included in this report are:
IBM Corporation
Microsoft Corporation
NVIDIA Corporation
DEEP GENOMICS
Data4Cure, Inc.
Freenome Holdings, Inc.
Thermo Fisher Scientific, Inc.
Illumina, Inc.
SOPHiA GENETICS
BenevolentAI
Recent Developments in the Market:
Ø In May 2021, the Adventist Church-run non-profit healthcare system AdventHealth and health intelligence company Sema4 entered into a partnership agreement. In this agreement, AdventHealth’s genomic and clinical data are supposed to be combined using Sema4’s software and tools. With investments in genomics research, genetic testing, counselling, and sequencing, AdventHealth was projected to increase its emphasis on genomics and personalised health as a result of this collaboration.
Ø In October 2020, NVIDIA announced a partnership with an AI-powered lab for the development of new drugs and vaccines. The GSK centre accessed more precise genetic and clinical data by combining AI technology, biological data, and contemporary computing platforms. Through NVIDIA Clara discovery, a collection of optimised computational drug discovery tools and frameworks, NVIDIA provided its experience in GPU optimisation and high-speed computational pipeline development.

Global AI In Genomics Market Report Scope:
Historical Data 2019-2020-2021
Base Year for Estimation 2021
Forecast period 2022-2029
Report Coverage Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered Component, Technology, Functionality, Application, End-use, Region
Regional Scope North America; Europe; Asia Pacific; Latin America; Rest of the World
Customization Scope Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Component:
Hardware
Software
Services
By Technology:
Machine Learning
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
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
RoLA
Rest of the World

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2029 (USD Million)
1.2.1. AI In Genomics Market, by Region, 2019-2029 (USD Million)
1.2.2. AI In Genomics Market, by Component, 2019-2029 (USD Million)
1.2.3. AI In Genomics Market, by Technology, 2019-2029 (USD Million)
1.2.4. AI In Genomics Market, by Functionality, 2019-2029 (USD Million)
1.2.5. AI In Genomics Market, by Application, 2019-2029 (USD Million)
1.2.6. AI In Genomics Market, by End-use, 2019-2029 (USD Million)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global AI In Genomics Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global AI In Genomics Market Dynamics
3.1. AI In Genomics Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Rising investment for research in the field of personalized medicine
3.1.1.2. Increasing government investments
3.1.2. Market Challenges
3.1.2.1. Dearth of skilled AI professionals
3.1.2.2. Stringent regulatory framework
3.1.3. Market Opportunities
3.1.3.1. Rising emphasis on developing human-aware AI systems
3.1.3.2. Increasing advancement in the field of gene therapy
Chapter 4. Global AI In Genomics Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Futuristic Approach to Porter’s 5 Force Model (2019-2029)
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. Industry Experts Prospective
4.7. Analyst Recommendation & Conclusion
Chapter 5. Risk Assessment: COVID-19 Impact
5.1. Assessment of the overall impact of COVID-19 on the industry
5.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global AI In Genomics Market, by Component
6.1. Market Snapshot
6.2. Global AI In Genomics Market by Component, Performance – Potential Analysis
6.3. Global AI In Genomics Market Estimates & Forecasts by Component 2019-2029 (USD Million)
6.4. AI In Genomics Market, Sub Segment Analysis
6.4.1. Hardware
6.4.2. Software
6.4.3. Services
Chapter 7. Global AI In Genomics Market, by Technology
7.1. Market Snapshot
7.2. Global AI In Genomics Market by Technology, Performance – Potential Analysis
7.3. Global AI In Genomics Market Estimates & Forecasts by Technology 2019-2029 (USD Million)
7.4. AI In Genomics Market, Sub Segment Analysis
7.4.1. Machine Learning
7.4.2. Computer Vision
Chapter 8. Global AI In Genomics Market, by Functionality
8.1. Market Snapshot
8.2. Global AI In Genomics Market by Functionality, Performance – Potential Analysis
8.3. Global AI In Genomics Market Estimates & Forecasts by Functionality 2019-2029 (USD Million)
8.4. AI In Genomics Market, Sub Segment Analysis
8.4.1. Genome Sequencing
8.4.2. Gene Editing
8.4.3. Others
Chapter 9. Global AI In Genomics Market, by Application
9.1. Market Snapshot
9.2. Global AI In Genomics Market by Application, Performance – Potential Analysis
9.3. Global AI In Genomics Market Estimates & Forecasts by Application 2019-2029 (USD Million)
9.4. AI In Genomics Market, Sub Segment Analysis
9.4.1. Drug Discovery & Development
9.4.2. Precision Medicine
9.4.3. Diagnostics
9.4.4. Others
Chapter 10. Global AI In Genomics Market, by End-use
10.1. Market Snapshot
10.2. Global AI In Genomics Market by End-use, Performance – Potential Analysis
10.3. Global AI In Genomics Market Estimates & Forecasts by End-use 2019-2029 (USD Million)
10.4. AI In Genomics Market, Sub Segment Analysis
10.4.1. Pharmaceutical and Biotech Companies
10.4.2. Healthcare Providers
10.4.3. Research Centers
10.4.4. Others
Chapter 11. Global AI In Genomics Market, Regional Analysis
11.1. AI In Genomics Market, Regional Market Snapshot
11.2. North America AI In Genomics Market
11.2.1. U.S. AI In Genomics Market
11.2.1.1. Component breakdown estimates & forecasts, 2019-2029
11.2.1.2. Technology breakdown estimates & forecasts, 2019-2029
11.2.1.3. Functionality breakdown estimates & forecasts, 2019-2029
11.2.1.4. Application breakdown estimates & forecasts, 2019-2029
11.2.1.5. End-use breakdown estimates & forecasts, 2019-2029
11.2.2. Canada AI In Genomics Market
11.3. Europe AI In Genomics Market Snapshot
11.3.1. U.K. AI In Genomics Market
11.3.2. Germany AI In Genomics Market
11.3.3. France AI In Genomics Market
11.3.4. Spain AI In Genomics Market
11.3.5. Italy AI In Genomics Market
11.3.6. Rest of Europe AI In Genomics Market
11.4. Asia-Pacific AI In Genomics Market Snapshot
11.4.1. China AI In Genomics Market
11.4.2. India AI In Genomics Market
11.4.3. Japan AI In Genomics Market
11.4.4. Australia AI In Genomics Market
11.4.5. South Korea AI In Genomics Market
11.4.6. Rest of Asia Pacific AI In Genomics Market
11.5. Latin America AI In Genomics Market Snapshot
11.5.1. Brazil AI In Genomics Market
11.5.2. Mexico AI In Genomics Market
11.5.3. Rest of Latin America AI In Genomics Market
11.6. Rest of The World AI In Genomics Market

Chapter 12. Competitive Intelligence
12.1. Top Market Strategies
12.2. Company Profiles
12.2.1. IBM Corporation
12.2.1.1. Key Information
12.2.1.2. Overview
12.2.1.3. Financial (Subject to Data Availability)
12.2.1.4. Product Summary
12.2.1.5. Recent Developments
12.2.2. Microsoft Corporation
12.2.3. NVIDIA Corporation
12.2.4. DEEP GENOMICS
12.2.5. Data4Cure, Inc.
12.2.6. Freenome Holdings, Inc.
12.2.7. Thermo Fisher Scientific Inc.
12.2.8. Illumina, Inc.
12.2.9. SOPHiA GENETICS
12.2.10. BenevolentAI
Chapter 13. Research Process
13.1. Research Process
13.1.1. Data Mining
13.1.2. Analysis
13.1.3. Market Estimation
13.1.4. Validation
13.1.5. Publishing
13.2. Research Attributes
13.3. Research Assumption

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Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
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Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
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To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
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