The generative AI in personalized medicine market provides a deep study of market segments including type, end-use, and region. The report tracks the latest market trends and analyses their overall impact on the market. It also evaluates the market dynamics, which cover the key demand and price indicators, and studies the market on the basis of the SWOT and Porter's Five Forces models.
Key Takeaways:
- North America is expected to dominate in the generative AI in personalized medicine market during the forecast period.
- By personalized medicine therapeutics, the pharmaceutical segment is expected to hold a leading position in the generative AI in personalized medicine market.
- By deployment model, the cloud-based segment is expected to carry a significant share of the generative AI in personalized medicine market during the forecast period.
- By end-user, the hospitals and clinics segment shares the maximum CAGR during the projection period.
The generative AI in personalized medicine report offers a comprehensive study of the current state expected at the major drivers, market strategies, and key vendors’ growth. The report presents energetic visions to conclude and study the market size, market hopes, and competitive surroundings. The research also focuses on the important achievements of the market, research & development, and regional growth of the leading competitors operating in the market. The current trends of the global generative AI in personalized medicine in conjunction with the geographical landscape of this vertical have also been included in this report.
The report offers intricate dynamics about different aspects of the global generative AI in personalized medicine market, which aids companies operating in the market in making strategic development decisions. The study also elaborates on significant changes that are highly anticipated to configure growth of the global generative AI in personalized medicine during the forecast period. It also includes a key indicator assessment that highlights growth prospects of this market and estimates statistics related to growth of the market in terms of value (US$ Mn) and volume (tons).
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This study covers a detailed segmentation of the global generative AI in personalized medicine market, along with key information and a competition outlook. The report mentions company profiles of players that are currently dominating the global generative AI in personalized medicine market, wherein various developments, expansions, and winning strategies practiced and implemented by leading players have been presented in detail.
Key Players
- Butterfly Network
- Deep Genomics
- Google LLC
- IBM Watson Health
- Microsoft Corporation
- Aidoc
- Insilico Medicine
- PathAI
- Tencent Holdings Ltd.
- Neuralink Corporation
- Johnson & Johnson
Market Segmentation
By Personalized Medicine Therapeutics
- Pharmaceutical
- Genomic Medicine
- Devices
By Deployment Model
- On-premise
- Cloud Based
By End-User
- Hospitals and Clinics
- Clinical Research
- Healthcare Organizations
- Diagnostic Centers
By Geography
- North America
- Europe
- Asia-Pacific
- Latin America
- Middle East and Africa
Research Methodology
The research methodology adopted by analysts for compiling the global generative AI in personalized medicine report is based on detailed primary as well as secondary research. With the help of in-depth insights of the market-affiliated information that is obtained and legitimated by market-admissible resources, analysts have offered riveting observations and authentic forecasts for the global market.
During the primary research phase, analysts interviewed market stakeholders, investors, brand managers, vice presidents, and sales and marketing managers. Based on data obtained through interviews of genuine resources, analysts have emphasized the changing scenario of the global market.
For secondary research, analysts scrutinized numerous annual report publications, white papers, market association publications, and company websites to obtain the necessary understanding of the global generative AI in personalized medicine market.
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 Personalized Medicine Market
5.1. COVID-19 Landscape: Generative AI in Personalized Medicine 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 Personalized Medicine Market, By Personalized Medicine Therapeutics
8.1. Generative AI in Personalized Medicine Market, by Personalized Medicine Therapeutics, 2023-2032
8.1.1 Pharmaceutical
8.1.1.1. Market Revenue and Forecast (2020-2032)
8.1.2. Genomic Medicine
8.1.2.1. Market Revenue and Forecast (2020-2032)
8.1.3. Devices
8.1.3.1. Market Revenue and Forecast (2020-2032)
Chapter 9. Global Generative AI in Personalized Medicine Market, By Deployment Model
9.1. Generative AI in Personalized Medicine Market, by Deployment Model, 2023-2032
9.1.1. On-premise
9.1.1.1. Market Revenue and Forecast (2020-2032)
9.1.2. Cloud Based
9.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 10. Global Generative AI in Personalized Medicine Market, By End-User
10.1. Generative AI in Personalized Medicine Market, by End-User, 2023-2032
10.1.1. Hospitals and Clinics
10.1.1.1. Market Revenue and Forecast (2020-2032)
10.1.2. Clinical Research
10.1.2.1. Market Revenue and Forecast (2020-2032)
10.1.3. Healthcare Organizations
10.1.3.1. Market Revenue and Forecast (2020-2032)
10.1.4. Diagnostic Centers
10.1.4.1. Market Revenue and Forecast (2020-2032)
Chapter 11. Global Generative AI in Personalized Medicine Market, Regional Estimates and Trend Forecast
11.1. North America
11.1.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.1.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.1.3. Market Revenue and Forecast, by End-User (2020-2032)
11.1.4. U.S.
11.1.4.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.1.4.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.1.4.3. Market Revenue and Forecast, by End-User (2020-2032)
11.1.5. Rest of North America
11.1.5.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.1.5.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.1.5.3. Market Revenue and Forecast, by End-User (2020-2032)
11.2. Europe
11.2.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.2.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.2.3. Market Revenue and Forecast, by End-User (2020-2032)
11.2.4. UK
11.2.4.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.2.4.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.2.4.3. Market Revenue and Forecast, by End-User (2020-2032)
11.2.5. Germany
11.2.5.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.2.5.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.2.5.3. Market Revenue and Forecast, by End-User (2020-2032)
11.2.6. France
11.2.6.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.2.6.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.2.6.3. Market Revenue and Forecast, by End-User (2020-2032)
11.2.7. Rest of Europe
11.2.7.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.2.7.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.2.7.3. Market Revenue and Forecast, by End-User (2020-2032)
11.3. APAC
11.3.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.3.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.3.3. Market Revenue and Forecast, by End-User (2020-2032)
11.3.4. India
11.3.4.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.3.4.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.3.4.3. Market Revenue and Forecast, by End-User (2020-2032)
11.3.5. China
11.3.5.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.3.5.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.3.5.3. Market Revenue and Forecast, by End-User (2020-2032)
11.3.6. Japan
11.3.6.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.3.6.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.3.6.3. Market Revenue and Forecast, by End-User (2020-2032)
11.3.7. Rest of APAC
11.3.7.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.3.7.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.3.7.3. Market Revenue and Forecast, by End-User (2020-2032)
11.4. MEA
11.4.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.4.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.4.3. Market Revenue and Forecast, by End-User (2020-2032)
11.4.4. GCC
11.4.4.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.4.4.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.4.4.3. Market Revenue and Forecast, by End-User (2020-2032)
11.4.5. North Africa
11.4.5.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.4.5.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.4.5.3. Market Revenue and Forecast, by End-User (2020-2032)
11.4.6. South Africa
11.4.6.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.4.6.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.4.6.3. Market Revenue and Forecast, by End-User (2020-2032)
11.4.7. Rest of MEA
11.4.7.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.4.7.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.4.7.3. Market Revenue and Forecast, by End-User (2020-2032)
11.5. Latin America
11.5.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.5.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.5.3. Market Revenue and Forecast, by End-User (2020-2032)
11.5.4. Brazil
11.5.4.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.5.4.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.5.4.3. Market Revenue and Forecast, by End-User (2020-2032)
11.5.5. Rest of LATAM
11.5.5.1. Market Revenue and Forecast, by Personalized Medicine Therapeutics (2020-2032)
11.5.5.2. Market Revenue and Forecast, by Deployment Model (2020-2032)
11.5.5.3. Market Revenue and Forecast, by End-User (2020-2032)
Chapter 12. Company Profiles
12.1. Butterfly Network
12.1.1. Company Overview
12.1.2. Product Offerings
12.1.3. Financial Performance
12.1.4. Recent Initiatives
12.2. Deep Genomics
12.2.1. Company Overview
12.2.2. Product Offerings
12.2.3. Financial Performance
12.2.4. Recent Initiatives
12.3. Google LLC
12.3.1. Company Overview
12.3.2. Product Offerings
12.3.3. Financial Performance
12.3.4. Recent Initiatives
12.4. IBM Watson Health
12.4.1. Company Overview
12.4.2. Product Offerings
12.4.3. Financial Performance
12.4.4. Recent Initiatives
12.5. Microsoft Corporation
12.5.1. Company Overview
12.5.2. Product Offerings
12.5.3. Financial Performance
12.5.4. Recent Initiatives
12.6. Aidoc
12.6.1. Company Overview
12.6.2. Product Offerings
12.6.3. Financial Performance
12.6.4. Recent Initiatives
12.7. Insilico Medicine
12.7.1. Company Overview
12.7.2. Product Offerings
12.7.3. Financial Performance
12.7.4. Recent Initiatives
12.8. PathAI
12.8.1. Company Overview
12.8.2. Product Offerings
12.8.3. Financial Performance
12.8.4. Recent Initiatives
12.9. Tencent Holdings Ltd.
12.9.1. Company Overview
12.9.2. Product Offerings
12.9.3. Financial Performance
12.9.4. Recent Initiatives
12.10. Neuralink Corporation
12.10.1. Company Overview
12.10.2. Product Offerings
12.10.3. Financial Performance
12.10.4. Recent Initiatives
Chapter 13. Research Methodology
13.1. Primary Research
13.2. Secondary Research
13.3. Assumptions
Chapter 14. Appendix
14.1. About Us
14.2. Glossary of Terms
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