October 5, 2024

Generative AI in Drug Discovery Market Size To Cross USD 1,417.83 Mn By 2032

The global generative AI in drug discovery market size accounted for US$ 126.07 Mn in 2022 and is projected to reach around USD 1,417.83 Mn by 2032, growing at a CAGR of 27.38% from 2023 to 2032.

Generative AI in Drug Discovery Market Size 2023 to 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.

Report Summary

The global generative AI in drug discovery market report provides a Point-by-Point and In-Depth analysis of global market size, regional and country-level market size, market share, segmentation market growth, competitive landscape, sales analysis, opportunities analysis, strategic market growth analysis, the impact of domestic and global market key players, value chain optimization, trade regulations, recent developments, product launches, area marketplace expanding, and technological innovations.

The study offers a comprehensive analysis on diverse features, including production capacities, demand, product developments, revenue generation, and sales in the generative AI in drug discovery market across the globe.

A comprehensive estimate on the generative AI in drug discovery market has been provided through an optimistic scenario as well as a conservative scenario, taking into account the sales of generative AI in drug discovery during the forecast period. Price point comparison by region with global average price is also considered in the study.

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Generative AI in Drug Discovery Market Report Scope 

Report CoverageDetails
Market Size in 2023USD 160.59 Million
Market Size by 2032USD 1,417.83 Million
Growth Rate from 2023 to 2032CAGR of 27.38%
Largest MarketNorth America
Base Year2022
Forecast Period2023 to 2032
Segments CoveredBy Technology and By End User
Regions CoveredNorth America, Europe, Asia-Pacific, Latin America, and Middle East & Africa

Key Highlights:

Reports Coverage: It incorporates key market sections, key makers secured, the extent of items offered in the years considered, worldwide containerized generative AI in drug discovery market and study goals. Moreover, it contacts the division study gave in the report based on the sort of item and applications.

Market Outline: This area stresses the key investigations, market development rate, serious scene, market drivers, patterns, and issues notwithstanding the naturally visible pointers.

Market Production by Region: The report conveys information identified with import and fare, income, creation, and key players of every single local market contemplated are canvassed right now.

Also Read: Polyvinyl Butyral Market Size To Cross USD 8.06 Bn By 2032

Market Segments:

Technology:

In the realm of technology, the market can be categorized into various segments, including machine learning, reinforcement learning, deep learning, molecular docking, and quantum computing. Among these segments, the deep learning category stands out as the dominant force in the generative AI for the ecommerce market, holding an impressive market share of xx%.

Deep learning is a specialized branch of machine learning that places emphasis on artificial neural networks comprising multiple layers. This architecture enables the model to learn and extract intricate patterns and features from complex datasets. Its inspiration lies in the structure and function of the human brain, mimicking the interconnected neural networks present in our biological system.

One of the primary reasons behind the popularity and widespread adoption of deep learning is its exceptional capability to handle vast amounts of data, even in high-dimensional spaces. Moreover, it possesses the remarkable ability to automatically learn hierarchical representations of data. This is achieved through the utilization of multiple interconnected layers of neurons, allowing deep learning models to capture and understand intricate patterns and relationships within the data. As a result, deep learning has garnered significant attention and recognition in various industries.

According to the end-user categorization, the market can be divided into various segments, including pharmaceutical and biotechnology companies, academic and research institutions, contract research organizations, and other end-users. Among these, the pharmaceutical and biotechnology sector stands out as the dominant player, holding a substantial revenue share of 42% during the projected period. This strong position can be attributed to pharmaceutical and biotechnology companies being the primary users of generative AI in the field of drug discovery.

These companies leverage generative AI technologies to expedite the drug discovery process, enabling them to identify new potential drug candidates, optimize lead compounds, and enhance target selection. By investing in generative AI platforms and tools, pharmaceutical and biotechnology firms aim to bolster their research and development capabilities, thereby expediting the introduction of innovative drugs to the market with greater efficiency.

End user:

According to the end-user categorization, the market can be divided into various segments, including pharmaceutical and biotechnology companies, academic and research institutions, contract research organizations, and other end-users. Among these, the pharmaceutical and biotechnology sector stands out as the dominant player, holding a substantial revenue share of 42% during the projected period. This strong position can be attributed to pharmaceutical and biotechnology companies being the primary users of generative AI in the field of drug discovery.

These companies leverage generative AI technologies to expedite the drug discovery process, enabling them to identify new potential drug candidates, optimize lead compounds, and enhance target selection. By investing in generative AI platforms and tools, pharmaceutical and biotechnology firms aim to bolster their research and development capabilities, thereby expediting the introduction of innovative drugs to the market with greater efficiency.

Market Players

The report includes the profiles of key generative AI in drug discovery market companies along with their SWOT analysis and market strategies. In addition, the report focuses on leading industry players with information such as company profiles, components and services offered, financial information, key development in past five years.

Major companies operating in this area

  • Insilico Medicine
  • Atomwise Inc.
  • BenevolentAI
  • XtalPi Inc
  • Numerate Inc
  • Cyclica Inc
  • BioSymetrics
  • Variational AI Inc.
  • Merck KGaA
  • NVIDIA

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

Regional Segmentation

  • North America (U.S., Canada, Mexico)
  • Europe (Germany, France, U.K., Italy, Spain, Rest of Europe)
  • Asia-Pacific (China, Japan, India, Southeast Asia and Rest of APAC)
  • Latin America (Brazil and Rest of Latin America)
  • Middle East and Africa (GCC, North Africa, South Africa, Rest of MEA)

Research Methodology

Secondary Research

It involves company databases such as Hoover’s: This assists us to recognize financial information, the structure of the market participants and industry’s competitive landscape.

The secondary research sources referred in the process are as follows:

  • Governmental bodies, and organizations creating economic policies
  • National and international social welfare institutions
  • Company websites, financial reports and SEC filings, broker and investor reports
  • Related patent and regulatory databases
  • Statistical databases and market reports
  • Corporate Presentations, news, press release, and specification sheet of Manufacturers

Primary Research

Primary research includes face-to-face interviews, online surveys, and telephonic interviews.

  • Means of primary research: Email interactions, telephonic discussions and Questionnaire-based research etc.
  • In order to validate our research findings and analysis, we conduct primary interviews of key industry participants. Insights from primary respondents help in validating the secondary research findings. It also develops Research Team’s expertise and market understanding.

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

Thanks for reading you can also get individual chapter-wise sections or region-wise report versions such as North America, Europe, or the Asia Pacific.

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