The Artificial Intelligence in Genomics Market Size was valued at USD 726.9 million in 2023 and is expected to reach USD 15007.1 million by 2031, and grow at a CAGR of 46.0% over the forecast period 2024-2031.
The market is driven by the need to control drug development and discovery costs and time, increase public and private investment in AI genomics, adoption of artificial intelligence solutions for precision medicine, increased partnerships and collaboration between players as well as growing investments in AI Genomics. Also, the market growth is supported by factors like improving computing capacity, decreasing hardware costs, increasing adoption of artificial intelligence in precision medicine and huge volumes of data from bioinformatics and genotyping.
Get more information on Artificial Intelligence In Genomics Market - Request Sample Report
DRIVERS
In precision medicine, AI has become more and more widespread.
To increase the number of genomic data sets
The cost of developing and discovering drugs needs to be reduced by speeding up processes and time lines
The discovery of new drugs is an expensive and protracted process, which means that alternative methods are needed to discover them. It is common to conduct drug discovery and development through in vivo or pharmacologic methods, which are expensive and time consuming. In addition, a new medicine takes an average of 10 years to reach the market and costs USD 2.6 billion.
RESTRAINTS
The lack of skilled AI workers and unclear guidance on the regulation of medical technology
AI is a complex system, and companies need workers with certain skills in order to develop, manage or implement an AI system. For example, people working on AI systems should know about image recognition, deep learning, cognitive computing, ML and machine intelligence. Integrating AI technologies into existing systems is a difficult task, requiring significant data processing, in order to replicate human brain behavior. A small error can lead to system failure or have a negative effect on the desired outcome.
OPPORTUNITIES
Focus on developing human-aware AI systems
The development of artificial intelligence technologies was to enable them to become human aware, or able to think like humans. But for the developers of AI machines, it is still a challenge to create interactive and scaleable machines. In addition, new research problems of interpretation and presentation have arisen as a result of the increasing interference of humans with AI techniques, e.g. in interactions between automated components and smart control of crowdsourcing parts. The challenge of interpreting human input, such as knowledge and specific directives, is part of the problem AI machines face.
CHALLENGES
There's a shortage of curated genomic data
Data is a vital source for training and developing an intelligent system which can be fully exploited. Datasets were previously largely composed and entered by hand. However, large volumes of unstructured data, in the form of text, voice, or image, are emerging as a result of the growing digital footprint and the adoption of technologies such as the Internet of Things in healthcare and life sciences.
The Ukrainian health system faces a number of challenges. Due to security concerns, limited mobility, fragmented supply chains and mass migration, access to healthcare is seriously hampered. Between February 24 and June 15, a total of 295 attacks targeting healthcare, including assaults on health facilities, transportation, personnel, patients, supplies, and warehouses, resulted in 60 injuries and 77 deaths. According to the World Health Organization WHO Surveillance System for Attacks on Health Care, these attacks rob people of urgently needed medical attention, threaten health care providers and jeopardise healthcare systems.
Since February 24, over 161 confirmed assaults on healthcare facilities in Ukraine have been limiting the available services. Access to reproductive, maternal, antenatal, and mental health care in Ukraine has likewise been significantly hindered by security apprehensions, limited mobility, disrupted supply chains, and widespread displacement. All wartime patients fall into several categories. The initial group comprises military personnel experiencing battlefield injuries and adverse environmental effects, while the second group encompasses civilians residing in occupied territories or areas near combat zones. Access to healthcare and medical supplies for these individuals is either restricted or insufficient.
The current economic slowdown in the health sector will be aggravated by recession's consequences. The COVID-19 pandemic exposed weaknesses in health systems worldwide, with numerous systems grappling with infrastructure and technology-related hurdles, while also endeavoring to tackle enduring workforce-related issues that impede system resilience. As the downturn approaches, healthcare systems have to cope with a risk environment shaped by persistent long-term trends such as climate change and ageing populations, which are exacerbated by pandemics like funding gaps and supply chain weaknesses.
Innovation and collaboration in the field of AI driven genomics may also be stimulated by economic slowdown. Researchers and industry professionals can take advantage of joint opportunities for pooling resources and expertise, as the focus is increasingly on cost effectiveness and efficiency. In that to support the development of accessable and low-cost AI tools for genetic analysis, which will benefit a wider scientific community, openness initiatives and partnerships with academia, industry and governments could be encouraged.
By Component
In 2023, software accounted for more than 40.2% of the market share and is projected to grow rapidly at a compound annual growth rate of 46.8% over the forecast period. The segments are anticipated to be driven by the rapid adoption of AI based software solutions for genomics among healthcare institutions, R&D centres and patients as well as new product launches from market participants.
By Technology
Machine Learning
Deep Learning
Supervised Learning
Unsupervised Learning
Others
Computer Vision
In 2023, The machine learning segment had the largest market share of around 63.2% and is expected to grow at a faster compound annual growth rate over the forecast period. Machine learning, which allows scientists to make discoveries and improve their understanding of the genetic basis for health and disease, is becoming an important tool in research on genomics. Automated tasks such as the annotation of genomic data or identifying potential drug targets can be performed by machine learning algorithms without requiring a great deal of manual effort.
By Functionality
Genome Sequencing
Gene Editing
Others
In 2023, the segment of genome sequencing accounted for a revenue share of 44.3% and is expected to maintain its dominance over the forecast period. The sequencing of the genome to find genetic patterns has been accelerated by the use of artificial intelligence in the field of genomics. In order to speed up the process, genome sequencing companies are working with companies based on artificial intelligence. For example, PacBio, a provider of genome sequencing technology, and Google have been working together since January 2022. Under the terms of the collaboration, PacBio was expected to use Google's algorithm development, genomic analysis, and machine learning tools to enhance its existing HiFI sequencing operations and to provide new information from its sequencing data.
By Application
Drug Discovery & Development
Precision Medicine
Diagnostics
Others
In 2023, the drug discovery & development segment dominated the market with a revenue share of over 30.2%. This is due to a growing demand for novel medicines for the treatment of infectious and chronic diseases, as well as an increasing number of partnerships between pharmaceutical and biotechnology companies and market players providing AI solutions in the field of genomics.
By End-Use
Pharmaceutical and Biotech Companies
Healthcare Providers
Research Centers
Others
In 2023, the pharmaceutical and biotech companies accounted for around 35.2% of the market's revenue due to artificial intelligence and machine learning are widely applied for applications such as data management, automatic disease prediction and prevention of illness or identification of biomarkers within the biotechnology and pharmaceutical industry. In order to help pharmaceutical companies avoid investments in drugs that are unlikely to perform well in clinical trials, AI algorithms can be applied to predict drug toxicity.
Need any customization research on Artificial Intelligence In Genomics Market - Enquiry Now
Regional Analysis
In 2023, North America accounted for around 29.4% of the global market for artificial intelligence in genomics in terms of revenue due to the presence of many market players such as Danone; Abbott; Nestlé; Targeted Medical Pharma, Inc.; and Mead Johnson & Company, LLC, North America is home to some of the world's largest and most well-funded research institutions and biotechnology companies, and these organizations are investing heavily in the development of AI powered solutions for genomics. This is driving the development of new software and tools to analyse genomic data in North America, contributing to a growing market for artificial intelligence in genomics.
The fastest compound annual growth rate is expected to be in Asia Pacific during the forecast period. The combination of rapid increases in healthcare costs, increased emphasis on precision medicine, advances in genomics technologies and an aging population is driving the demand for artificial intelligence in Genomics across the region. National initiatives in the field of genomics have been launched by some Asia countries, which are setting up their own population genetic database based on DNA sample from healthy people.
REGIONAL 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 the Middle East
Africa
Nigeria
South Africa
Rest of Africa
Latin America
Brazil
Argentina
Colombia
Rest of Latin America
The Major Players are IBM, Cambridge Cancer Genomics, NVIDIA Corporation, Thermo Fisher Scientific, MolecularMatch Inc., Deep Genomics, Microsoft, Freenome Holdings, Inc., BenevolentAI, Fabric Genomics Inc. and Other Players.
Cambridge Cancer Genomics-Company Financial Analysis
| Report Attributes | Details |
|---|---|
| Market Size in 2023 | US$ 726.9 Million |
| Market Size by 2031 | US$ 15007.1 Million |
| CAGR | CAGR of 46% From 2024 to 2031 |
| Base Year | 2023 |
| Forecast Perio | 2024-2031 |
| Historical Data | 2020-2022 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • 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) |
| 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) |
| Company Profiles | IBM, Cambridge Cancer Genomics, NVIDIA Corporation, Thermo Fisher Scientific, MolecularMatch Inc., Deep Genomics, Microsoft, Freenome Holdings, Inc., BenevolentAI, 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. |
Ans: The Artificial Intelligence in Genomics market size was valued at US$ 726.9 Mn in 2023
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 46% during the forecast period 2024-2031
TABLE OF CONTENTS
1. Introduction
1.1 Market Definition
1.2 Scope
1.3 Research Assumptions
2. Industry Flowchart
3. Research Methodology
4. Market Dynamics
4.1 Drivers
4.2 Restraints
4.3 Opportunities
4.4 Challenges
5. Impact Analysis
5.1 Impact of Russia-Ukraine Crisis
5.2 Impact of Economic Slowdown on Major Countries
5.2.1 Introduction
5.2.2 United States
5.2.3 Canada
5.2.4 Germany
5.2.5 France
5.2.6 UK
5.2.7 China
5.2.8 Japan
5.2.9 South Korea
5.2.10 India
6. Value Chain Analysis
7. Porter’s 5 Forces Model
8. Pest Analysis
9. Artificial Intelligence in Genomics Market, By Component
9.1 Introduction
10. Artificial Intelligence in Genomics Market, by Technology
11. Artificial Intelligence in Genomics Market, by Functionality
12. Artificial Intelligence in Genomics Market, by Application
12.1 Introduction
12.2 Trend Analysis
12.3 Drug Discovery & Development
12.4 Precision Medicine
12.5 Diagnostics
12.6 Others
13. Artificial Intelligence in Genomics Market, by End-use
13.1 Introduction
13.2 Trend Analysis
13.3 Pharmaceutical and Biotech Companies
13.4 Healthcare Providers
13.5 Research Centers
13.6 Others
14. Regional Analysis
14.1 Introduction
14.2 North America
14.2.1 USA
14.2.2 Canada
14.2.3 Mexico
14.3 Europe
14.3.1 Eastern Europe
14.3.1.1 Poland
14.3.1.2 Romania
14.3.1.3 Hungary
14.3.1.4 Turkey
14.3.1.5 Rest of Eastern Europe
14.3.2 Western Europe
14.3.2.1 Germany
14.3.2.2 France
14.3.2.3 UK
14.3.2.4 Italy
14.3.2.5 Spain
14.3.2.6 Netherlands
14.3.2.7 Switzerland
14.3.2.8 Austria
14.3.2.9 Rest of Western Europe
14.4 Asia-Pacific
14.4.1 China
14.4.2 India
14.4.3 Japan
14.4.4 South Korea
14.4.5 Vietnam
14.4.6 Singapore
14.4.7 Australia
14.4.8 Rest of Asia Pacific
14.5 The Middle East & Africa
14.5.1 Middle East
14.5.1.1 UAE
14.5.1.2 Egypt
14.5.1.3 Saudi Arabia
14.5.1.4 Qatar
14.5.1.5 Rest of the Middle East
14.5.2 Africa
14.5.2.1 Nigeria
14.5.2.2 South Africa
14.5.2.3 Rest of Africa
14.6 Latin America
14.6.1 Brazil
14.6.2 Argentina
14.6.3 Colombia
14.6.4 Rest of Latin America
15. Company Profiles
15.1 IBM
15.1.1 Company Overview
15.1.2 Financial
15.1.3 Products/ Services Offered
15.1.4 SWOT Analysis
15.1.5 The SNS View
15.2 Cambridge Cancer Genomics
15.2.1 Company Overview
15.2.2 Financial
15.2.3 Products/ Services Offered
15.2.4 SWOT Analysis
15.2.5 The SNS View
15.3 NVIDIA Corporation
15.3.1 Company Overview
15.3.2 Financial
15.3.3 Products/ Services Offered
15.3.4 SWOT Analysis
15.3.5 The SNS View
15.4 Thermo Fisher Scientific
15.4.1 Company Overview
15.4.2 Financial
15.4.3 Products/ Services Offered
15.4.4 SWOT Analysis
15.4.5 The SNS View
15.5 Molecular Match Inc.
15.5.1 Company Overview
15.5.2 Financial
15.5.3 Products/ Services Offered
15.5.4 SWOT Analysis
15.5.5 The SNS View
15.6 Deep Genomics
15.6.1 Company Overview
15.6.2 Financial
15.6.3 Products/ Services Offered
15.6.4 SWOT Analysis
15.6.5 The SNS View
15.7 Microsoft
15.7.1 Company Overview
15.7.2 Financial
15.7.3 Products/ Services Offered
15.7.4 SWOT Analysis
15.7.5 The SNS View
15.8 Freenome Holdings Inc.
15.8.1 Company Overview
15.8.2 Financial
15.8.3 Products/ Services Offered
15.8.4 SWOT Analysis
15.8.5 The SNS View
15.9 Benevolent AI
15.9.1 Company Overview
15.9.2 Financial
15.9.3 Products/ Services Offered
15.9.4 SWOT Analysis
15.9.5 The SNS View
15.10 Fabric Genomics Inc.
15.10.1 Company Overview
15.10.2 Financial
15.10.3 Products/ Services Offered
15.10.4 SWOT Analysis
15.10.5 The SNS View
16. Competitive Landscape
16.1 Competitive Benchmarking
16.2 Market Share Analysis
16.3 Recent Developments
16.3.1 Industry News
16.3.2 Company News
16.3.3 Mergers & Acquisitions
17. Use Case and Best Practices
18. 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.
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.
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
Once all the information is collected via primary and secondary sources, we run that information for data validation. At our intelligence centre our research heads track a lot of information related to the market which includes the quarterly reports, the daily stock prices, and other relevant information. Our data bank server gets updated every fortnight and that is how the information which we collected using our primary and secondary information is revalidated in real time.
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:
This is the last process and comes when the client has ordered the study. In this process a final QA/QC is done before the study is emailed to the client. Since we believe in giving our clients a good experience of our research studies, therefore, to make sure that we do not lack at our end in any way humanly possible we do a final round of quality check and then dispatch the study to the client.
The ECG Equipment and Management System market is anticipated to arrive at USD 9.77 billion by 2030. From 2023 to 2030, the market is assessed to develop at a CAGR of 6.38%.
The Genomics Services Market size was valued at USD 16.4 billion in 2022 and is estimated to reach USD 46.4 billion in 2030, and grow at a compound annual growth rate approx. CAGR of 12.8% over the forecast period of 2023-2030.
The CBD Skin Care Product Market size was valued at US$ 4.17 billion in 2023 and is projected to reach US$ 24.93 billion by 2031, with a growing CAGR of 25.03% over the forecast period 2024-2031.
The Gene Therapy Market size was USD 7.35 Billion in 2022 and is expected to Reach USD 30.15 Billion by 2030 and grow at a CAGR of 19.3% over the forecast period of 2023-2030.
Report Scope & Overview: The Infusion Pump Software Market Size was valued at USD 924.28 million in 2022 and is expected to reach USD 1660 million by 2030 and grow at a CAGR of 7.6% over the forecast period 2023-2030.
The Pharmaceuticals Logistics Market size was valued at USD 92.74 billion in 2023 and is expected to reach USD 186.47 billion by 2031 and grow at a CAGR of 9.12% over the forecast period of 2024-2031.
Hi! Click one of our member below to chat on Phone
© 2024 All Rights Reserved by SNS Insider Pvt Ltd
