Global AI in Drug Discovery Market
Global AI in Drug Discovery Market

AI in Drug Discovery Comprehensive Study by Application (Immuno-oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases, Others), Technology (Machine Learning, Deep Learning, Others), End-User (Pharmaceutical & Biotechnology, Research Organizations, Academic & Government Institutes), Component (Software, Services)

AI in Drug Discovery Market Segmented into XX Submarkets. | Forecast Years: 2020- 2025 | CAGR: 39.5%  

Mar 2020 Edition 213 Pages 212 Tables & Figures
  • Summary
  • Market Segments
  • Table of Content
  • List of Tables & Figures
  • Companies Mentioned
AI in Drug Discovery Market Definition
Artificial intelligence for drug discovery is a technology that uses and different algorithms that value add in decision-making processes for drug discovery. The increasing cases of rare diseases and demand for personalized drugs are the major factor fueling the growth of the global Al for Drug Discovery marker.

The market study is broken down, by Application (Immuno-oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases and Others) and major geographies with country level splits. According to AMA, the Global AI in Drug Discovery market is expected to see growth rate of 39.5%

Research Analyst at AMA estimates that United States Players will contribute to the maximum growth of Global AI in Drug Discovery market throughout the predicted period.

IBM Corporation (United States), Microsoft (United States), Google (United States), NVIDIA Corporation (United States), Atomwise, Inc. (United States), Deep Genomics (Canada), Cloud Pharmaceuticals (United States), Insilico Medicine (United States), Benevolent AI (United Kingdom) and Exscientia (United Kingdom) are some of the key players that are part of study coverage. Additionally, the Players which are also part of the research are Cyclica (Canada), BIOAGE (United States), Numerate (United States), Numedii (United States), Envisagenics (United States), twoXAR (United States), OWKIN, Inc. (United States), XtalPi (United States), Verge Genomics (United States) and Berg LLC (United States).

Segmentation Overview
AdvanceMarketAnalytics has segmented the market of Global AI in Drug Discovery market by Type, Application and Region.

On the basis of geography, the market of AI in Drug Discovery has been segmented into . If we see Market by Technology, the sub-segment i.e. Machine Learning will boost the AI in Drug Discovery market. Additionally, the rising demand from SMEs and various industry verticals gives enough cushion to market growth. If we see Market by End-User, the sub-segment i.e. Pharmaceutical & Biotechnology will boost the AI in Drug Discovery market. Additionally, the rising demand from SMEs and various industry verticals gives enough cushion to market growth. If we see Market by Component, the sub-segment i.e. Software will boost the AI in Drug Discovery market. Additionally, the rising demand from SMEs and various industry verticals gives enough cushion to market growth.




Market Trend
  • Research Applying AI to Drug Discovery is Accelerating
  • Data Sharing

Market Drivers
  • Increasing Pressure on the Drug Manufacturer to Reduce Drug Price
  • Growing Number of Cross-Industry Collaborations and Partnerships

Opportunities
  • Implementation of AI reduces researches and development gap in the drug manufacturing process and help in the targeted manufacturing of the drugs.
  • Huge Investments in Research & Developments

Restraints
  • Limited Awareness, High Cost and Technical Limitation of AI Decision-Making

Challenges
  • Protecting Intellectual Property and Data


Key Target Audience
Al in Drug Discovery Vendors, Pharmaceutical & Healthcare Organizations, Research Institutes, Governments and Others

About Approach
The research aims to propose a patent-based approach in searching for potential technology partners as a supporting tool for enabling open innovation. The study also proposes a systematic searching process of technology partners as a preliminary step to select the emerging and key players that are involved in implementing market estimations. While patent analysis is employed to overcome the aforementioned data- and process-related limitations, as expenses occurred in that technology allows us to estimate the market size by evolving segments as target market from total available market.

Customization available in this Study:
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Data related to EXIM [Export- Import], production & consumption by country or regional level break-up can be provided based on client request**
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Report Objectives / Segmentation Covered
By Application
  • Immuno-oncology
  • Neurodegenerative Diseases
  • Cardiovascular Diseases
  • Metabolic Diseases
  • Others
By Technology
  • Machine Learning
  • Deep Learning
  • Others

By End-User
  • Pharmaceutical & Biotechnology
  • Research Organizations
  • Academic & Government Institutes

By Component
  • Software
  • Services

By Regions
    • 1. Market Overview
      • 1.1. Introduction
      • 1.2. Scope/Objective of the Study
        • 1.2.1. Research Objective
    • 2. Executive Summary
      • 2.1. Introduction
    • 3. Market Dynamics
      • 3.1. Introduction
      • 3.2. Market Drivers
        • 3.2.1. Increasing Pressure on the Drug Manufacturer to Reduce Drug Price
        • 3.2.2. Growing Number of Cross-Industry Collaborations and Partnerships
      • 3.3. Market Challenges
        • 3.3.1. Protecting Intellectual Property and Data
      • 3.4. Market Trends
        • 3.4.1. Research Applying AI to Drug Discovery is Accelerating
        • 3.4.2. Data Sharing
    • 4. Market Factor Analysis
      • 4.1. Porters Five Forces
      • 4.2. Supply/Value Chain
      • 4.3. PESTEL analysis
      • 4.4. Market Entropy
      • 4.5. Patent/Trademark Analysis
    • 5. Global AI in Drug Discovery, by Application, Technology, End-User and Component (value) (2014-2019)
      • 5.1. Introduction
      • 5.2. Global AI in Drug Discovery (Value)
        • 5.2.1. Global AI in Drug Discovery by: Application (Value)
          • 5.2.1.1. Immuno-oncology
          • 5.2.1.2. Neurodegenerative Diseases
          • 5.2.1.3. Cardiovascular Diseases
          • 5.2.1.4. Metabolic Diseases
          • 5.2.1.5. Others
        • 5.2.2. Global AI in Drug Discovery by: Technology (Value)
          • 5.2.2.1. Machine Learning
          • 5.2.2.2. Deep Learning
          • 5.2.2.3. Others
        • 5.2.3. Global AI in Drug Discovery by: End-User (Value)
          • 5.2.3.1. Pharmaceutical & Biotechnology
          • 5.2.3.2. Research Organizations
          • 5.2.3.3. Academic & Government Institutes
        • 5.2.4. Global AI in Drug Discovery by: Component (Value)
          • 5.2.4.1. Software
          • 5.2.4.2. Services
    • 6. AI in Drug Discovery: Manufacturers/Players Analysis
      • 6.1. Competitive Landscape
        • 6.1.1. Market Share Analysis
          • 6.1.1.1. Top 3
          • 6.1.1.2. Top 5
      • 6.2. Peer Group Analysis (2019)
      • 6.3. BCG Matrix
      • 6.4. Company Profile
        • 6.4.1. IBM Corporation (United States)
          • 6.4.1.1. Business Overview
          • 6.4.1.2. Products/Services Offerings
          • 6.4.1.3. Financial Analysis
          • 6.4.1.4. SWOT Analysis
        • 6.4.2. Microsoft (United States)
          • 6.4.2.1. Business Overview
          • 6.4.2.2. Products/Services Offerings
          • 6.4.2.3. Financial Analysis
          • 6.4.2.4. SWOT Analysis
        • 6.4.3. Google (United States)
          • 6.4.3.1. Business Overview
          • 6.4.3.2. Products/Services Offerings
          • 6.4.3.3. Financial Analysis
          • 6.4.3.4. SWOT Analysis
        • 6.4.4. NVIDIA Corporation (United States)
          • 6.4.4.1. Business Overview
          • 6.4.4.2. Products/Services Offerings
          • 6.4.4.3. Financial Analysis
          • 6.4.4.4. SWOT Analysis
        • 6.4.5. Atomwise, Inc. (United States)
          • 6.4.5.1. Business Overview
          • 6.4.5.2. Products/Services Offerings
          • 6.4.5.3. Financial Analysis
          • 6.4.5.4. SWOT Analysis
        • 6.4.6. Deep Genomics (Canada)
          • 6.4.6.1. Business Overview
          • 6.4.6.2. Products/Services Offerings
          • 6.4.6.3. Financial Analysis
          • 6.4.6.4. SWOT Analysis
        • 6.4.7. Cloud Pharmaceuticals (United States)
          • 6.4.7.1. Business Overview
          • 6.4.7.2. Products/Services Offerings
          • 6.4.7.3. Financial Analysis
          • 6.4.7.4. SWOT Analysis
        • 6.4.8. Insilico Medicine (United States)
          • 6.4.8.1. Business Overview
          • 6.4.8.2. Products/Services Offerings
          • 6.4.8.3. Financial Analysis
          • 6.4.8.4. SWOT Analysis
        • 6.4.9. Benevolent AI (United Kingdom)
          • 6.4.9.1. Business Overview
          • 6.4.9.2. Products/Services Offerings
          • 6.4.9.3. Financial Analysis
          • 6.4.9.4. SWOT Analysis
        • 6.4.10. Exscientia (United Kingdom)
          • 6.4.10.1. Business Overview
          • 6.4.10.2. Products/Services Offerings
          • 6.4.10.3. Financial Analysis
          • 6.4.10.4. SWOT Analysis
    • 7. Global AI in Drug Discovery Sale, by Application, Technology, End-User and Component (value) (2020-2025)
      • 7.1. Introduction
      • 7.2. Global AI in Drug Discovery (Value)
        • 7.2.1. Global AI in Drug Discovery by: Application (Value)
          • 7.2.1.1. Immuno-oncology
          • 7.2.1.2. Neurodegenerative Diseases
          • 7.2.1.3. Cardiovascular Diseases
          • 7.2.1.4. Metabolic Diseases
          • 7.2.1.5. Others
        • 7.2.2. Global AI in Drug Discovery by: Technology (Value)
          • 7.2.2.1. Machine Learning
          • 7.2.2.2. Deep Learning
          • 7.2.2.3. Others
        • 7.2.3. Global AI in Drug Discovery by: End-User (Value)
          • 7.2.3.1. Pharmaceutical & Biotechnology
          • 7.2.3.2. Research Organizations
          • 7.2.3.3. Academic & Government Institutes
        • 7.2.4. Global AI in Drug Discovery by: Component (Value)
          • 7.2.4.1. Software
          • 7.2.4.2. Services
    • 8. Appendix
      • 8.1. Acronyms
    • 9. Methodology and Data Source
      • 9.1. Methodology/Research Approach
        • 9.1.1. Research Programs/Design
        • 9.1.2. Market Size Estimation
        • 9.1.3. Market Breakdown and Data Triangulation
      • 9.2. Data Source
        • 9.2.1. Secondary Sources
        • 9.2.2. Primary Sources
      • 9.3. Disclaimer
    List of Tables
    • Table 1. AI in Drug Discovery: by Application(USD Million)
    • Table 2. AI in Drug Discovery: by Technology(USD Million)
    • Table 3. AI in Drug Discovery: by End-User(USD Million)
    • Table 4. AI in Drug Discovery: by Component(USD Million)
    • Table 5. Company Basic Information, Sales Area and Its Competitors
    • Table 6. Company Basic Information, Sales Area and Its Competitors
    • Table 7. Company Basic Information, Sales Area and Its Competitors
    • Table 8. Company Basic Information, Sales Area and Its Competitors
    • Table 9. Company Basic Information, Sales Area and Its Competitors
    • Table 10. Company Basic Information, Sales Area and Its Competitors
    • Table 11. Company Basic Information, Sales Area and Its Competitors
    • Table 12. Company Basic Information, Sales Area and Its Competitors
    • Table 13. Company Basic Information, Sales Area and Its Competitors
    • Table 14. Company Basic Information, Sales Area and Its Competitors
    • Table 15. AI in Drug Discovery: by Application(USD Million)
    • Table 16. AI in Drug Discovery: by Technology(USD Million)
    • Table 17. AI in Drug Discovery: by End-User(USD Million)
    • Table 18. AI in Drug Discovery: by Component(USD Million)
    • Table 19. Research Programs/Design for This Report
    • Table 20. Key Data Information from Secondary Sources
    • Table 21. Key Data Information from Primary Sources
    List of Figures
    • Figure 1. Porters Five Forces
    • Figure 2. Supply/Value Chain
    • Figure 3. PESTEL analysis
    • Figure 4. Global AI in Drug Discovery: by Application USD Million (2014-2019)
    • Figure 5. Global AI in Drug Discovery: by Technology USD Million (2014-2019)
    • Figure 6. Global AI in Drug Discovery: by End-User USD Million (2014-2019)
    • Figure 7. Global AI in Drug Discovery: by Component USD Million (2014-2019)
    • Figure 8. Global AI in Drug Discovery share by Players 2019 (%)
    • Figure 9. Global AI in Drug Discovery share by Players (Top 3) 2019(%)
    • Figure 10. Global AI in Drug Discovery share by Players (Top 5) 2019(%)
    • Figure 11. BCG Matrix for key Companies
    • Figure 12. IBM Corporation (United States) Revenue, Net Income and Gross profit
    • Figure 13. IBM Corporation (United States) Revenue: by Geography 2019
    • Figure 14. Microsoft (United States) Revenue, Net Income and Gross profit
    • Figure 15. Microsoft (United States) Revenue: by Geography 2019
    • Figure 16. Google (United States) Revenue, Net Income and Gross profit
    • Figure 17. Google (United States) Revenue: by Geography 2019
    • Figure 18. NVIDIA Corporation (United States) Revenue, Net Income and Gross profit
    • Figure 19. NVIDIA Corporation (United States) Revenue: by Geography 2019
    • Figure 20. Atomwise, Inc. (United States) Revenue, Net Income and Gross profit
    • Figure 21. Atomwise, Inc. (United States) Revenue: by Geography 2019
    • Figure 22. Deep Genomics (Canada) Revenue, Net Income and Gross profit
    • Figure 23. Deep Genomics (Canada) Revenue: by Geography 2019
    • Figure 24. Cloud Pharmaceuticals (United States) Revenue, Net Income and Gross profit
    • Figure 25. Cloud Pharmaceuticals (United States) Revenue: by Geography 2019
    • Figure 26. Insilico Medicine (United States) Revenue, Net Income and Gross profit
    • Figure 27. Insilico Medicine (United States) Revenue: by Geography 2019
    • Figure 28. Benevolent AI (United Kingdom) Revenue, Net Income and Gross profit
    • Figure 29. Benevolent AI (United Kingdom) Revenue: by Geography 2019
    • Figure 30. Exscientia (United Kingdom) Revenue, Net Income and Gross profit
    • Figure 31. Exscientia (United Kingdom) Revenue: by Geography 2019
    • Figure 32. Global AI in Drug Discovery: by Application USD Million (2020-2025)
    • Figure 33. Global AI in Drug Discovery: by Technology USD Million (2020-2025)
    • Figure 34. Global AI in Drug Discovery: by End-User USD Million (2020-2025)
    • Figure 35. Global AI in Drug Discovery: by Component USD Million (2020-2025)
    Some of the key companies/manufacturers profiled in the report
    • IBM Corporation (United States)
    • Microsoft (United States)
    • Google (United States)
    • NVIDIA Corporation (United States)
    • Atomwise, Inc. (United States)
    • Deep Genomics (Canada)
    • Cloud Pharmaceuticals (United States)
    • Insilico Medicine (United States)
    • Benevolent AI (United Kingdom)
    • Exscientia (United Kingdom)
    Additional players considered in the study are as follows:
    Cyclica (Canada) , BIOAGE (United States) , Numerate (United States) , Numedii (United States) , Envisagenics (United States) , twoXAR (United States) , OWKIN, Inc. (United States) , XtalPi (United States) , Verge Genomics (United States) , Berg LLC (United States)
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