Artificial Intelligence (AI) in Biopharmaceutical Market Size to Garner USD 14.07 Billion by 2032

The global artificial intelligence (AI) in biopharmaceutical market size was estimated to be around US$ 0.86 billion in 2022. It is projected to reach US$ 14.07 billion by 2032, indicating a CAGR of 32.3% from 2023 to 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.

The market research report on the Artificial intelligence (AI) in biopharmaceutical market provides a comprehensive analysis of various key aspects. It includes the definition, classification, and application of Artificial intelligence (AI) in biopharmaceutical products. The report examines the development trends, competitive landscape, and industrial chain structure within the industry. Furthermore, it presents an overview of the industry, analyzes national policies and planning, and offers insights into the latest market dynamics and opportunities at a global level.

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Artificial Intelligence (AI) in Biopharmaceutical Market Scope

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The report presents the volume and value-based market size for the base year 2022 and forecasts the market’s growth between 2023 and 2032. It estimates market numbers based on product form and application, providing size and forecast for each application segment in both global and regional markets.

Focusing on the global Artificial intelligence (AI) in biopharmaceutical market, the report highlights its status, future forecasts, growth opportunities, key market players, and key market regions such as the United States, Europe, and China. The study aims to present the development of the Artificial intelligence (AI) in biopharmaceutical market by considering factors like Year-on-Year (Y-o-Y) growth, in addition to Compound Annual Growth Rate (CAGR). This approach enables a better understanding of market certainty and the identification of lucrative opportunities.

Regarding production, the report investigates the capacity, production, value, ex-factory price, growth rate, and market share of major manufacturers, regions, and product types. On the consumption side, the report focuses on the regional consumption of Artificial intelligence (AI) in biopharmaceutical products across different countries and applications.

Buyers of the report gain access to verified market figures, including global market size in terms of revenue and volume. The report provides reliable estimations and calculations for global revenue and volume by product type from 2023 to 2032. It also includes accurate figures for production capacity and production by region during the same period.

The research includes product parameters, production processes, cost structures, and data classified by region, technology, and application. Furthermore, it conducts SWOT analysis and investment feasibility studies for new projects.

This in-depth research report offers valuable insights into the Artificial intelligence (AI) in biopharmaceutical market. It employs an objective and fair approach to analyze industry trends, supporting customer competition analysis, development planning, and investment decision-making. The project received support and assistance from technicians and marketing personnel across various links in the industry chain.

The competitive landscape section of the report provides detailed information on Artificial intelligence (AI) in biopharmaceutical market competitors. It includes company overviews, financials, revenue generation, market potential, research and development investments, new market initiatives, global presence, production sites, production capacities, strengths and weaknesses, product launches, product range, and application dominance. However, the data points provided only focus on the companies’ activities related to the Artificial intelligence (AI) in biopharmaceutical market.

Prominent players in the market are expected to face tough competition from new entrants. Key players are targeting acquisitions of startup companies to maintain their dominance. The report

Reasons to Purchase this Report:

• Comprehensive market segmentation analysis incorporating qualitative and quantitative research, considering the impact of economic and policy factors.
• In-depth regional and country-level analysis, examining the demand and supply dynamics that influence market growth.
• Market size in USD million and volume in million units provided for each segment and sub-segment.
• Detailed competitive landscape, including market share of major players, recent projects, and strategies implemented over the past five years.
• Comprehensive company profiles encompassing product offerings, key financial information, recent developments, SWOT analysis, and employed strategies by major market players.

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

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 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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