by The artificial intelligence (AI) in biopharmaceutical market size is poised to grow by USD 14.07 billion by 2032 from USD 0.86 billion in 2022, exhibiting a CAGR of 32.3% during the forecast period 2023-2032.
Key Takeaways
- By region, North America contributed more than 45% of the revenue share in the artificial intelligence in biopharmaceutical market in 2022. On the other hand, Asia-Pacific is estimated to expand the fastest CAGR between 2023 and 2032.
- By application, the drug discovery segment has held the largest market share of 35% in 2022. Whereas the research segment is anticipated to grow at a remarkable CAGR of 32.8% between 2023 and 2032.
- By technology, the natural language processing segment generated over 32% of revenue share in 2022. Meanwhile, the deep learning segment is expected to expand at the fastest CAGR over the projected period.
- By offering, the hardware segment had the largest market share of 44% in 2022. On the other hand, the service segment is expected to expand at the fastest CAGR over the projected period.
- By deployment, the cloud segment had the largest market share of 52% 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 Artificial intelligence (AI) in biopharmaceutical 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 Artificial intelligence (AI) in biopharmaceutical 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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Artificial Intelligence (AI) in Biopharmaceutical Market Scope
| Report Coverage | Details |
| Growth Rate from 2023 to 2032 | CAGR of 32.3% |
| Market Size in 2023 | USD 1.13 Billion |
| Market Size by 2032 | USD 14.07 Billion |
| Largest Market | North America |
| Base Year | 2022 |
| Forecast Period | 2023 to 2032 |
| Segments Covered | By Application, By Technology, By Offering, and By Deployment |
| Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
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The empirical study on the global Artificial intelligence (AI) in biopharmaceutical 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 Artificial intelligence (AI) in biopharmaceutical Market. Our market report for the Artificial intelligence (AI) in biopharmaceutical 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.
Top Key Players:
- IBM Watson Health
- Google Health
- NVIDIA Corporation
- Microsoft Healthcare
- DeepMind
- Atomwise
- Insilico Medicine
- PathAI
- Tempus
- GNS Healthcare
- OWKIN
- Cloud Pharmaceuticals
- Numerate
- Recursion Pharmaceuticals
- Healx
Data Sources and Methodology
To gather comprehensive insights on the Global Artificial intelligence (AI) in biopharmaceutical 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 Artificial intelligence (AI) in biopharmaceutical 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.
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- 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.
Market Segmentation:
By Application
- Drug Discovery
- Precision Medicine
- Medical Imaging & Diagnostics
- Research
By Technology
- Machine Learning
- Natural Language Processing
- Deep Learning
- Others
By Offering
- Hardware
- Software
- Services
By Deployment
- Cloud
- On-Premises
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 Artificial intelligence (AI) in biopharmaceutical market.
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- Receive valuable recommendations and guidance for both new entrants and established players seeking further market expansion.
- Discover not only the cutting-edge technological advancements in the global Artificial intelligence (AI) in biopharmaceutical market but also the strategic plans of industry leaders.
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 Artificial Intelligence (AI) in Biopharmaceutical Market
5.1. COVID-19 Landscape: Artificial Intelligence (AI) in Biopharmaceutical 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 Artificial Intelligence (AI) in Biopharmaceutical Market, By Application
8.1. Artificial Intelligence (AI) in Biopharmaceutical Market, by Application, 2023-2032
8.1.1. Drug Discovery
8.1.1.1. Market Revenue and Forecast (2020-2032)
8.1.2. Precision Medicine
8.1.2.1. Market Revenue and Forecast (2020-2032)
8.1.3. Medical Imaging & Diagnostics
8.1.3.1. Market Revenue and Forecast (2020-2032)
8.1.4. Research
8.1.4.1. Market Revenue and Forecast (2020-2032)
Chapter 9. Global Artificial Intelligence (AI) in Biopharmaceutical Market, By Technology
9.1. Artificial Intelligence (AI) in Biopharmaceutical Market, by Technology, 2023-2032
9.1.1. Machine Learning
9.1.1.1. Market Revenue and Forecast (2020-2032)
9.1.2. Natural Language Processing
9.1.2.1. Market Revenue and Forecast (2020-2032)
9.1.3. Deep Learning
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 Artificial Intelligence (AI) in Biopharmaceutical Market, By Offering
10.1. Artificial Intelligence (AI) in Biopharmaceutical Market, by Offering, 2023-2032
10.1.1. Hardware
10.1.1.1. Market Revenue and Forecast (2020-2032)
10.1.2. Software
10.1.2.1. Market Revenue and Forecast (2020-2032)
10.1.3. Services
10.1.3.1. Market Revenue and Forecast (2020-2032)
Chapter 11. Global Artificial Intelligence (AI) in Biopharmaceutical Market, By Deployment
11.1. Artificial Intelligence (AI) in Biopharmaceutical Market, by Deployment, 2023-2032
11.1.1. Cloud
11.1.1.1. Market Revenue and Forecast (2020-2032)
11.1.2. On-Premises
11.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 12. Global Artificial Intelligence (AI) in Biopharmaceutical Market, Regional Estimates and Trend Forecast
12.1. North America
12.1.1. Market Revenue and Forecast, by Application (2020-2032)
12.1.2. Market Revenue and Forecast, by Technology (2020-2032)
12.1.3. Market Revenue and Forecast, by Offering (2020-2032)
12.1.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.1.5. U.S.
12.1.5.1. Market Revenue and Forecast, by Application (2020-2032)
12.1.5.2. Market Revenue and Forecast, by Technology (2020-2032)
12.1.5.3. Market Revenue and Forecast, by Offering (2020-2032)
12.1.5.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.1.6. Rest of North America
12.1.6.1. Market Revenue and Forecast, by Application (2020-2032)
12.1.6.2. Market Revenue and Forecast, by Technology (2020-2032)
12.1.6.3. Market Revenue and Forecast, by Offering (2020-2032)
12.1.6.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.2. Europe
12.2.1. Market Revenue and Forecast, by Application (2020-2032)
12.2.2. Market Revenue and Forecast, by Technology (2020-2032)
12.2.3. Market Revenue and Forecast, by Offering (2020-2032)
12.2.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.2.5. UK
12.2.5.1. Market Revenue and Forecast, by Application (2020-2032)
12.2.5.2. Market Revenue and Forecast, by Technology (2020-2032)
12.2.5.3. Market Revenue and Forecast, by Offering (2020-2032)
12.2.5.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.2.6. Germany
12.2.6.1. Market Revenue and Forecast, by Application (2020-2032)
12.2.6.2. Market Revenue and Forecast, by Technology (2020-2032)
12.2.6.3. Market Revenue and Forecast, by Offering (2020-2032)
12.2.6.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.2.7. France
12.2.7.1. Market Revenue and Forecast, by Application (2020-2032)
12.2.7.2. Market Revenue and Forecast, by Technology (2020-2032)
12.2.7.3. Market Revenue and Forecast, by Offering (2020-2032)
12.2.7.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.2.8. Rest of Europe
12.2.8.1. Market Revenue and Forecast, by Application (2020-2032)
12.2.8.2. Market Revenue and Forecast, by Technology (2020-2032)
12.2.8.3. Market Revenue and Forecast, by Offering (2020-2032)
12.2.8.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.3. APAC
12.3.1. Market Revenue and Forecast, by Application (2020-2032)
12.3.2. Market Revenue and Forecast, by Technology (2020-2032)
12.3.3. Market Revenue and Forecast, by Offering (2020-2032)
12.3.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.3.5. India
12.3.5.1. Market Revenue and Forecast, by Application (2020-2032)
12.3.5.2. Market Revenue and Forecast, by Technology (2020-2032)
12.3.5.3. Market Revenue and Forecast, by Offering (2020-2032)
12.3.5.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.3.6. China
12.3.6.1. Market Revenue and Forecast, by Application (2020-2032)
12.3.6.2. Market Revenue and Forecast, by Technology (2020-2032)
12.3.6.3. Market Revenue and Forecast, by Offering (2020-2032)
12.3.6.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.3.7. Japan
12.3.7.1. Market Revenue and Forecast, by Application (2020-2032)
12.3.7.2. Market Revenue and Forecast, by Technology (2020-2032)
12.3.7.3. Market Revenue and Forecast, by Offering (2020-2032)
12.3.7.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.3.8. Rest of APAC
12.3.8.1. Market Revenue and Forecast, by Application (2020-2032)
12.3.8.2. Market Revenue and Forecast, by Technology (2020-2032)
12.3.8.3. Market Revenue and Forecast, by Offering (2020-2032)
12.3.8.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.4. MEA
12.4.1. Market Revenue and Forecast, by Application (2020-2032)
12.4.2. Market Revenue and Forecast, by Technology (2020-2032)
12.4.3. Market Revenue and Forecast, by Offering (2020-2032)
12.4.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.4.5. GCC
12.4.5.1. Market Revenue and Forecast, by Application (2020-2032)
12.4.5.2. Market Revenue and Forecast, by Technology (2020-2032)
12.4.5.3. Market Revenue and Forecast, by Offering (2020-2032)
12.4.5.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.4.6. North Africa
12.4.6.1. Market Revenue and Forecast, by Application (2020-2032)
12.4.6.2. Market Revenue and Forecast, by Technology (2020-2032)
12.4.6.3. Market Revenue and Forecast, by Offering (2020-2032)
12.4.6.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.4.7. South Africa
12.4.7.1. Market Revenue and Forecast, by Application (2020-2032)
12.4.7.2. Market Revenue and Forecast, by Technology (2020-2032)
12.4.7.3. Market Revenue and Forecast, by Offering (2020-2032)
12.4.7.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.4.8. Rest of MEA
12.4.8.1. Market Revenue and Forecast, by Application (2020-2032)
12.4.8.2. Market Revenue and Forecast, by Technology (2020-2032)
12.4.8.3. Market Revenue and Forecast, by Offering (2020-2032)
12.4.8.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.5. Latin America
12.5.1. Market Revenue and Forecast, by Application (2020-2032)
12.5.2. Market Revenue and Forecast, by Technology (2020-2032)
12.5.3. Market Revenue and Forecast, by Offering (2020-2032)
12.5.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.5.5. Brazil
12.5.5.1. Market Revenue and Forecast, by Application (2020-2032)
12.5.5.2. Market Revenue and Forecast, by Technology (2020-2032)
12.5.5.3. Market Revenue and Forecast, by Offering (2020-2032)
12.5.5.4. Market Revenue and Forecast, by Deployment (2020-2032)
12.5.6. Rest of LATAM
12.5.6.1. Market Revenue and Forecast, by Application (2020-2032)
12.5.6.2. Market Revenue and Forecast, by Technology (2020-2032)
12.5.6.3. Market Revenue and Forecast, by Offering (2020-2032)
12.5.6.4. Market Revenue and Forecast, by Deployment (2020-2032)
Chapter 13. Company Profiles
13.1. IBM Watson Health
13.1.1. Company Overview
13.1.2. Product Offerings
13.1.3. Financial Performance
13.1.4. Recent Initiatives
13.2. Google Health
13.2.1. Company Overview
13.2.2. Product Offerings
13.2.3. Financial Performance
13.2.4. Recent Initiatives
13.3. NVIDIA Corporation
13.3.1. Company Overview
13.3.2. Product Offerings
13.3.3. Financial Performance
13.3.4. Recent Initiatives
13.4. Microsoft Healthcare
13.4.1. Company Overview
13.4.2. Product Offerings
13.4.3. Financial Performance
13.4.4. Recent Initiatives
13.5. DeepMind
13.5.1. Company Overview
13.5.2. Product Offerings
13.5.3. Financial Performance
13.5.4. Recent Initiatives
13.6. Atomwise
13.6.1. Company Overview
13.6.2. Product Offerings
13.6.3. Financial Performance
13.6.4. Recent Initiatives
13.7. Insilico Medicine
13.7.1. Company Overview
13.7.2. Product Offerings
13.7.3. Financial Performance
13.7.4. Recent Initiatives
13.8. PathAI
13.8.1. Company Overview
13.8.2. Product Offerings
13.8.3. Financial Performance
13.8.4. Recent Initiatives
13.9. Tempus
13.9.1. Company Overview
13.9.2. Product Offerings
13.9.3. Financial Performance
13.9.4. Recent Initiatives
13.10. GNS Healthcare
13.10.1. Company Overview
13.10.2. Product Offerings
13.10.3. Financial Performance
13.10.4. Recent Initiatives
Chapter 14. Research Methodology
14.1. Primary Research
14.2. Secondary Research
14.3. Assumptions
Chapter 15. Appendix
15.1. About Us
15.2. Glossary of Terms
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