Artificial Intelligence (AI) in Biopharmaceutical Market Size to Record US$ 14.07 billion by 2032

According to a recent research report titled ” Artificial Intelligence (AI) in Biopharmaceutical Market (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) – Global Industry Analysis, Size, Share, Growth, Trends, Regional Outlook, and Forecast 2023-2032″ published by Precedence Research, the global artificial intelligence (AI) in biopharmaceutical market size is projected to touch around USD 14.07 billion by 2032 and growing at a CAGR of 32.3% over the forecast period 2023 to 2032. This comprehensive study examines various factors and their impact on the growth of the artificial intelligence (AI) in biopharmaceutical market.

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.

The report primarily focuses on the volume and value of the artificial intelligence (AI) in biopharmaceutical market at the global, regional, and company levels. At the global level, the report analyzes historical data and future prospects to present an overview of the overall market size. Regionally, the study emphasizes key regions such as North America, Europe, the Middle East & Africa, Latin America, and others.

Furthermore, the research report provides specific segmentations based on regions (countries), companies, and all market segments. This analysis offers insights into the growth and revenue trends during the historical period of 2017 to 2032, as well as the projected period. By understanding these segments, it becomes possible to identify the significance of different factors that contribute to market growth.

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The research also highlights significant progressions in both organic and inorganic growth strategies within the global artificial intelligence (AI) in biopharmaceutical market. Numerous companies are placing emphasis on new product launches, gaining product approvals, and implementing various business expansion tactics. Moreover, the report presents detailed profiles of firms operating in the artificial intelligence (AI) in biopharmaceutical market, along with their respective market strategies. Additionally, the study concentrates on prominent industry participants, furnishing details such as company profiles, product offerings, financial updates, and noteworthy advancements.

Artificial Intelligence (AI) in Biopharmaceutical Market Scope

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Major Key Points Covered in Report:

Executive Summary: It includes key trends of the electric vehicle fuel cell market related to products, applications, and other crucial factors. It also provides analysis of the competitive landscape and CAGR and market size of the electric vehicle fuel cell market based on production and revenue.

Production and Consumption by Region: It covers all regional markets to which the research study relates. Prices and key players in addition to production and consumption in each regional market are discussed.

Key Players: Here, the report throws light on financial ratios, pricing structure, production cost, gross profit, sales volume, revenue, and gross margin of leading and prominent companies competing in the Electric vehicle fuel cell market.

Market Segments: This part of the report discusses product, application and other segments of the electric vehicle fuel cell market based on market share, CAGR, market size, and various other factors.

Research Methodology: This section discusses the research methodology and approach used to prepare the report. It covers data triangulation, market breakdown, market size estimation, and research design and/or programs.

Market Key Players

The report incorporates company profiles of key players in the market. These profiles encompass vital information such as product portfolio, key strategies, and a comprehensive SWOT analysis for each player. Additionally, the report presents a matrix illustrating the presence of each prominent player, enabling readers to gain actionable insights. This facilitates a thoughtful assessment of the market status and aids in predicting the level of competition in the artificial intelligence (AI) in biopharmaceutical market.

Artificial Intelligence (AI) in Biopharmaceutical Market 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

 

Market Segmentations 

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

Table of Contents:

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

Why should you invest in this report?

This report presents a compelling investment opportunity for those interested in the global artificial intelligence (AI) in biopharmaceutical market. It serves as an extensive and informative guide, offering clear insights into this niche market. By delving into the report, you will gain a comprehensive understanding of the various major application areas for artificial intelligence (AI) in biopharmaceutical. Furthermore, it provides crucial information about the key regions worldwide that are expected to experience substantial growth within the forecast period of 2023-2030. Armed with this knowledge, you can strategically plan your market entry approaches.

Moreover, this report offers a deep analysis of the competitive landscape, equipping you with valuable insights into the level of competition prevalent in this highly competitive market. If you are already an established player, it will enable you to assess the strategies employed by your competitors, allowing you to stay ahead as market leaders. For newcomers entering this market, the extensive data provided in this report is invaluable, providing a solid foundation for informed decision-making.

Some of the key questions answered in this report:       

• What is the size of the overall Artificial intelligence (AI) in biopharmaceutical market and its segments?
• What are the key segments and sub-segments in the market?
• What are the key drivers, restraints, opportunities and challenges of the Artificial intelligence (AI) in biopharmaceutical market and how they are expected to impact the market?
• What are the attractive investment opportunities within the Artificial intelligence (AI) in biopharmaceutical market?
• What is the Artificial intelligence (AI) in biopharmaceutical market size at the regional and country-level?
• Who are the key market players and their key competitors?
• What are the strategies for growth adopted by the key players in Artificial intelligence (AI) in biopharmaceutical market?
• What are the recent trends in Artificial intelligence (AI) in biopharmaceutical market? (M&A, partnerships, new product developments, expansions)?
• What are the challenges to the Artificial intelligence (AI) in biopharmaceutical market growth?
• What are the key market trends impacting the growth of Artificial intelligence (AI) in biopharmaceutical market?

 

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