by The global generative AI in drug discovery market size accounted for US$ 126.07 Mn in 2022 and is projected to reach around USD 1,417.83 Mn by 2032, growing at a CAGR of 27.38% from 2023 to 2032.
Key Takeaways:
- North America contributed more than 50% of revenue share in 2022.
- By technology, the deep learning segment is expected to capture a significant market share over the forecast period.
- By end user, the pharmaceutical & biotechnology company segment generated more than 43% of revenue share in 2022.
Report Summary
The global generative AI in drug discovery market report provides a Point-by-Point and In-Depth analysis of global market size, regional and country-level market size, market share, segmentation market growth, competitive landscape, sales analysis, opportunities analysis, strategic market growth analysis, the impact of domestic and global market key players, value chain optimization, trade regulations, recent developments, product launches, area marketplace expanding, and technological innovations.
The study offers a comprehensive analysis on diverse features, including production capacities, demand, product developments, revenue generation, and sales in the generative AI in drug discovery market across the globe.
A comprehensive estimate on the generative AI in drug discovery market has been provided through an optimistic scenario as well as a conservative scenario, taking into account the sales of generative AI in drug discovery during the forecast period. Price point comparison by region with global average price is also considered in the study.
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Generative AI in Drug Discovery Market Report Scope
| Report Coverage | Details |
| Market Size in 2023 | USD 160.59 Million |
| Market Size by 2032 | USD 1,417.83 Million |
| Growth Rate from 2023 to 2032 | CAGR of 27.38% |
| Largest Market | North America |
| Base Year | 2022 |
| Forecast Period | 2023 to 2032 |
| Segments Covered | By Technology and By End User |
| Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
Key Highlights:
Reports Coverage: It incorporates key market sections, key makers secured, the extent of items offered in the years considered, worldwide containerized generative AI in drug discovery market and study goals. Moreover, it contacts the division study gave in the report based on the sort of item and applications.
Market Outline: This area stresses the key investigations, market development rate, serious scene, market drivers, patterns, and issues notwithstanding the naturally visible pointers.
Market Production by Region: The report conveys information identified with import and fare, income, creation, and key players of every single local market contemplated are canvassed right now.
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Market Segments:
Technology:
In the realm of technology, the market can be categorized into various segments, including machine learning, reinforcement learning, deep learning, molecular docking, and quantum computing. Among these segments, the deep learning category stands out as the dominant force in the generative AI for the ecommerce market, holding an impressive market share of xx%.
Deep learning is a specialized branch of machine learning that places emphasis on artificial neural networks comprising multiple layers. This architecture enables the model to learn and extract intricate patterns and features from complex datasets. Its inspiration lies in the structure and function of the human brain, mimicking the interconnected neural networks present in our biological system.
One of the primary reasons behind the popularity and widespread adoption of deep learning is its exceptional capability to handle vast amounts of data, even in high-dimensional spaces. Moreover, it possesses the remarkable ability to automatically learn hierarchical representations of data. This is achieved through the utilization of multiple interconnected layers of neurons, allowing deep learning models to capture and understand intricate patterns and relationships within the data. As a result, deep learning has garnered significant attention and recognition in various industries.
According to the end-user categorization, the market can be divided into various segments, including pharmaceutical and biotechnology companies, academic and research institutions, contract research organizations, and other end-users. Among these, the pharmaceutical and biotechnology sector stands out as the dominant player, holding a substantial revenue share of 42% during the projected period. This strong position can be attributed to pharmaceutical and biotechnology companies being the primary users of generative AI in the field of drug discovery.
These companies leverage generative AI technologies to expedite the drug discovery process, enabling them to identify new potential drug candidates, optimize lead compounds, and enhance target selection. By investing in generative AI platforms and tools, pharmaceutical and biotechnology firms aim to bolster their research and development capabilities, thereby expediting the introduction of innovative drugs to the market with greater efficiency.
End user:
According to the end-user categorization, the market can be divided into various segments, including pharmaceutical and biotechnology companies, academic and research institutions, contract research organizations, and other end-users. Among these, the pharmaceutical and biotechnology sector stands out as the dominant player, holding a substantial revenue share of 42% during the projected period. This strong position can be attributed to pharmaceutical and biotechnology companies being the primary users of generative AI in the field of drug discovery.
These companies leverage generative AI technologies to expedite the drug discovery process, enabling them to identify new potential drug candidates, optimize lead compounds, and enhance target selection. By investing in generative AI platforms and tools, pharmaceutical and biotechnology firms aim to bolster their research and development capabilities, thereby expediting the introduction of innovative drugs to the market with greater efficiency.
Market Players
The report includes the profiles of key generative AI in drug discovery market companies along with their SWOT analysis and market strategies. In addition, the report focuses on leading industry players with information such as company profiles, components and services offered, financial information, key development in past five years.
Major companies operating in this area
- Insilico Medicine
- Atomwise Inc.
- BenevolentAI
- XtalPi Inc
- Numerate Inc
- Cyclica Inc
- BioSymetrics
- Variational AI Inc.
- Merck KGaA
- NVIDIA
Generative AI in Drug Discovery Market Segmentation
By Technology
- Machine Learning
- Reinforcement Learning
- Deep Learning
- Molecular Docking
- Quantum Computing
By End User
- Pharmaceutical & Biotechnology Company
- Academic & Research Institution
- Contract Research Organizations
- Others
Regional Segmentation
- North America (U.S., Canada, Mexico)
- Europe (Germany, France, U.K., Italy, Spain, Rest of Europe)
- Asia-Pacific (China, Japan, India, Southeast Asia and Rest of APAC)
- Latin America (Brazil and Rest of Latin America)
- Middle East and Africa (GCC, North Africa, South Africa, Rest of MEA)
Research Methodology
Secondary Research
It involves company databases such as Hoover’s: This assists us to recognize financial information, the structure of the market participants and industry’s competitive landscape.
The secondary research sources referred in the process are as follows:
- Governmental bodies, and organizations creating economic policies
- National and international social welfare institutions
- Company websites, financial reports and SEC filings, broker and investor reports
- Related patent and regulatory databases
- Statistical databases and market reports
- Corporate Presentations, news, press release, and specification sheet of Manufacturers
Primary Research
Primary research includes face-to-face interviews, online surveys, and telephonic interviews.
- Means of primary research: Email interactions, telephonic discussions and Questionnaire-based research etc.
- In order to validate our research findings and analysis, we conduct primary interviews of key industry participants. Insights from primary respondents help in validating the secondary research findings. It also develops Research Team’s expertise and market understanding.
TABLE OF CONTENT
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology (Premium Insights)
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Generative AI in Drug Discovery Market
5.1. COVID-19 Landscape: Generative AI in Drug Discovery Industry Impact
5.2. COVID 19 – Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Generative AI in Drug Discovery Market, By Technology
8.1. Generative AI in Drug Discovery Market, by Technology, 2023-2032
8.1.1. Machine Learning
8.1.1.1. Market Revenue and Forecast (2020-2032)
8.1.2. Reinforcement Learning
8.1.2.1. Market Revenue and Forecast (2020-2032)
8.1.3. Deep Learning
8.1.3.1. Market Revenue and Forecast (2020-2032)
8.1.4. Molecular Docking
8.1.4.1. Market Revenue and Forecast (2020-2032)
8.1.5. Quantum Computing
8.1.5.1. Market Revenue and Forecast (2020-2032)
Chapter 9. Global Generative AI in Drug Discovery Market, By End User
9.1. Generative AI in Drug Discovery Market, by End User, 2023-2032
9.1.1. Pharmaceutical & Biotechnology Company
9.1.1.1. Market Revenue and Forecast (2020-2032)
9.1.2. Academic & Research Institution
9.1.2.1. Market Revenue and Forecast (2020-2032)
9.1.3. Contract Research Organizations
9.1.3.1. Market Revenue and Forecast (2020-2032)
9.1.4. Others
9.1.4.1. Market Revenue and Forecast (2020-2032)
Chapter 10. Global Generative AI in Drug Discovery Market, Regional Estimates and Trend Forecast
10.1. North America
10.1.1. Market Revenue and Forecast, by Technology (2020-2032)
10.1.2. Market Revenue and Forecast, by End User (2020-2032)
10.1.3. U.S.
10.1.3.1. Market Revenue and Forecast, by Technology (2020-2032)
10.1.3.2. Market Revenue and Forecast, by End User (2020-2032)
10.1.4. Rest of North America
10.1.4.1. Market Revenue and Forecast, by Technology (2020-2032)
10.1.4.2. Market Revenue and Forecast, by End User (2020-2032)
10.2. Europe
10.2.1. Market Revenue and Forecast, by Technology (2020-2032)
10.2.2. Market Revenue and Forecast, by End User (2020-2032)
10.2.3. UK
10.2.3.1. Market Revenue and Forecast, by Technology (2020-2032)
10.2.3.2. Market Revenue and Forecast, by End User (2020-2032)
10.2.4. Germany
10.2.4.1. Market Revenue and Forecast, by Technology (2020-2032)
10.2.4.2. Market Revenue and Forecast, by End User (2020-2032)
10.2.5. France
10.2.5.1. Market Revenue and Forecast, by Technology (2020-2032)
10.2.5.2. Market Revenue and Forecast, by End User (2020-2032)
10.2.6. Rest of Europe
10.2.6.1. Market Revenue and Forecast, by Technology (2020-2032)
10.2.6.2. Market Revenue and Forecast, by End User (2020-2032)
10.3. APAC
10.3.1. Market Revenue and Forecast, by Technology (2020-2032)
10.3.2. Market Revenue and Forecast, by End User (2020-2032)
10.3.3. India
10.3.3.1. Market Revenue and Forecast, by Technology (2020-2032)
10.3.3.2. Market Revenue and Forecast, by End User (2020-2032)
10.3.4. China
10.3.4.1. Market Revenue and Forecast, by Technology (2020-2032)
10.3.4.2. Market Revenue and Forecast, by End User (2020-2032)
10.3.5. Japan
10.3.5.1. Market Revenue and Forecast, by Technology (2020-2032)
10.3.5.2. Market Revenue and Forecast, by End User (2020-2032)
10.3.6. Rest of APAC
10.3.6.1. Market Revenue and Forecast, by Technology (2020-2032)
10.3.6.2. Market Revenue and Forecast, by End User (2020-2032)
10.4. MEA
10.4.1. Market Revenue and Forecast, by Technology (2020-2032)
10.4.2. Market Revenue and Forecast, by End User (2020-2032)
10.4.3. GCC
10.4.3.1. Market Revenue and Forecast, by Technology (2020-2032)
10.4.3.2. Market Revenue and Forecast, by End User (2020-2032)
10.4.4. North Africa
10.4.4.1. Market Revenue and Forecast, by Technology (2020-2032)
10.4.4.2. Market Revenue and Forecast, by End User (2020-2032)
10.4.5. South Africa
10.4.5.1. Market Revenue and Forecast, by Technology (2020-2032)
10.4.5.2. Market Revenue and Forecast, by End User (2020-2032)
10.4.6. Rest of MEA
10.4.6.1. Market Revenue and Forecast, by Technology (2020-2032)
10.4.6.2. Market Revenue and Forecast, by End User (2020-2032)
10.5. Latin America
10.5.1. Market Revenue and Forecast, by Technology (2020-2032)
10.5.2. Market Revenue and Forecast, by End User (2020-2032)
10.5.3. Brazil
10.5.3.1. Market Revenue and Forecast, by Technology (2020-2032)
10.5.3.2. Market Revenue and Forecast, by End User (2020-2032)
10.5.4. Rest of LATAM
10.5.4.1. Market Revenue and Forecast, by Technology (2020-2032)
10.5.4.2. Market Revenue and Forecast, by End User (2020-2032)
Chapter 11. Company Profiles
11.1. Insilico Medicine
11.1.1. Company Overview
11.1.2. Product Offerings
11.1.3. Financial Performance
11.1.4. Recent Initiatives
11.2. Atomwise Inc.
11.2.1. Company Overview
11.2.2. Product Offerings
11.2.3. Financial Performance
11.2.4. Recent Initiatives
11.3. BenevolentAI
11.3.1. Company Overview
11.3.2. Product Offerings
11.3.3. Financial Performance
11.3.4. Recent Initiatives
11.4. XtalPi Inc
11.4.1. Company Overview
11.4.2. Product Offerings
11.4.3. Financial Performance
11.4.4. Recent Initiatives
11.5. Numerate Inc
11.5.1. Company Overview
11.5.2. Product Offerings
11.5.3. Financial Performance
11.5.4. Recent Initiatives
11.6. Cyclica Inc
11.6.1. Company Overview
11.6.2. Product Offerings
11.6.3. Financial Performance
11.6.4. Recent Initiatives
11.7. BioSymetrics
11.7.1. Company Overview
11.7.2. Product Offerings
11.7.3. Financial Performance
11.7.4. Recent Initiatives
11.8. Variational AI Inc.
11.8.1. Company Overview
11.8.2. Product Offerings
11.8.3. Financial Performance
11.8.4. Recent Initiatives
11.9. Variational AI Inc.
11.9.1. Company Overview
11.9.2. Product Offerings
11.9.3. Financial Performance
11.9.4. Recent Initiatives
11.10. NVIDIA
11.10.1. Company Overview
11.10.2. Product Offerings
11.10.3. Financial Performance
11.10.4. Recent Initiatives
Chapter 12. Research Methodology
12.1. Primary Research
12.2. Secondary Research
12.3. Assumptions
Chapter 13. Appendix
13.1. About Us
13.2. Glossary of Terms
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