by The generative AI in drug discovery market size is poised to grow by USD 1,417.83 million by 2032 from USD 126.07 million in 2022, exhibiting a CAGR of 27.38% during the forecast period 2023-2032.
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.
Precedence Research has conducted a comprehensive market study that provides valuable insights into the performance of the market during the forecast period. The study identifies significant trends that are shaping the growth of the Generative AI in drug discovery market. In this recently published report, essential dynamics such as drivers, restraints, and opportunities are highlighted for both established market players and emerging participants involved in production and supply.
To begin with, the Generative AI in drug discovery Market report features an executive summary that offers a concise overview of the marketplace. It outlines the key players and industry categories expected to have an impact on the market in the coming years. The executive summary provides an unbiased summary of the market.
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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 |
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The empirical study on the global Generative AI in drug discovery market primarily focuses on the drivers in subsequent sections. It demonstrates how changing demographics are projected to influence the supply and demand dynamics in the Generative AI in drug discovery Market. Our market report for the Generative AI in drug discovery market also delves into the significant rules and regulations that are likely to impact the future growth of this sector. Moreover, in order to comprehend the underlying demand factors, industry experts have provided insights into its fundamental origins.
Regional Snapshot:
North America is projected to maintain its dominance in the market throughout the forecast period. The region’s growth can be attributed to the high prevalence of cancer cases. According to the American Cancer Society Journals, the United States reported 1,918,030 new cancer cases and 609,360 cancer-related deaths in 2022. Additionally, North America boasts a well-established and flourishing pharmaceutical industry, with numerous pharmaceutical companies, research institutions, and academic centers actively investing in AI technologies for drug discovery. These entities recognize the potential of generative AI to improve efficiency, reduce costs, and expedite the drug discovery process. For instance, in May 2023, XtalPi partnered with the US-based Eli Lilly to leverage artificial intelligence (AI) for drug development. Utilizing XtalPi’s integrated robotics platform and AI capabilities, the two companies aim to create and deliver medication candidates for an undisclosed target.
This collaboration will employ an AI drug discovery tool to develop a new chemical that Lilly will pursue through clinical and commercial development. Furthermore, regulatory agencies in North America, such as the U.S. Food and Drug Administration (FDA) and Health Canada, have demonstrated a willingness to embrace and support innovative technologies in drug discovery. They recognize the potential of generative AI to enhance the efficiency and success rate of drug development, creating a favorable regulatory environment for the adoption of generative AI in the region, thereby contributing to the market’s growth.
On the other hand, Asia Pacific is anticipated to experience the highest compound annual growth rate (CAGR) during the forecast period. The growth in this region is attributed to the expanding pharmaceutical industry and the rising prevalence of cancer. The region’s pharmaceutical sector is rapidly expanding due to increased healthcare expenditures, a large patient population, and a growing demand for innovative therapies. The adoption of generative AI in drug discovery presents an opportunity to accelerate the development of new drugs and address unmet medical needs in the Asia Pacific region.
Top Key Players:
- Insilico Medicine
- Atomwise Inc.
- BenevolentAI
- XtalPi Inc
- Numerate Inc
- Cyclica Inc
- BioSymetrics
- Variational AI Inc.
- Merck KGaA
- NVIDIA
Data Sources and Methodology
To gather comprehensive insights on the Global Generative AI in drug discovery Market, we relied on a range of data sources and followed a well-defined methodology. Our approach involved interactions with industry experts and key stakeholders across the market’s value chain, including management organizations, processing organizations, and analytics service providers.
We followed a rigorous data analysis process to ensure the quality and credibility of our research. The gathered information was carefully evaluated, and relevant quantitative data was subjected to statistical analysis. By employing robust analytical techniques, we were able to derive meaningful insights and present a comprehensive overview of the Global Generative AI in drug discovery Market.
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- The research report has been meticulously crafted to provide comprehensive knowledge on essential marketing strategies and a holistic understanding of crucial marketing plans spanning the forecasted period from 2023 to 2032.
Key Features of the Report:
- Comprehensive Coverage: The report extensively encompasses a detailed explanation of highly effective analytical marketing methods applicable to companies across all industry sectors.
- Decision-Making Enhancement: It outlines a concise overview of the decision-making process while highlighting key techniques to enhance it, ensuring favorable business outcomes in the future.
- Articulated R&D Approach: The report presents a well-defined approach to conducting research and development (R&D) activities, enabling accurate data acquisition on current and future marketing conditions.
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
By Geography
- North America
- Europe
- Asia-Pacific
- Latin America
- Middle East and Africa
Reasons to Consider Purchasing the Report:
- Enhance your market research capabilities by accessing this comprehensive and precise report on the global Generative AI in drug discovery market.
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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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