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PUBLISHER: Bizwit Research & Consulting LLP | PRODUCT CODE: 1300847

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PUBLISHER: Bizwit Research & Consulting LLP | PRODUCT CODE: 1300847

Global Machine Learning in the Life Sciences Market Size study & Forecast, by Component, by Application, by End User and Regional Analysis, 2023-2030

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Global Machine Learning in the Life Sciences Market is valued approximately USD XX billion in 2022 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2023-2030. The global machine learning in the life sciences market refers to the application of machine learning techniques and algorithms in various areas of the life sciences industry. Machine learning involves the use of computer algorithms that can learn from and make predictions or decisions based on patterns and data, without being explicitly programmed. The global machine learning in the life sciences market is influenced by factors such as advancements in AI and machine learning technologies, increasing availability of large-scale biological and clinical datasets, growing demand for personalized medicine. Moreover, the need for efficient drug discovery and development processes and rising initatives by key market players is creating lucrative growth opportunity for the market over the forecast period 2023-2030.

India is witnessing market growth as the software's adoption is increase with growing digitalization in healthcare by the region. For instance, according to the Indian Society for Clinical Research (ISCR), a report was published in 2021 which stated that the digital adoption of clinical trials is witnessing growth for the market. Along with this, the government is supporting the healthcare industry in the country which is driving the growth of the market. As owing to this support, the companies can develop new and advanced technology for the proper management of patient's data. For instance, in June 2021, the Indian government is planning to introduce a USD 6.8 billion worth credit incentive program in order to boost the country's healthcare infrastructure. Along with this, the research and development activities for the clinical trial is increasing in Japan which is driving the growth for the market. For instance, in September 2020, The Medical Research Council (MRC) and Japan Agency for Medical Research and Development (AMED) have joined forces in order to support eight new regenerative medicine research partnerships. In this collaboration, MRC and AMED agreed to make almost USD 7.95 million available for supporting the collaborative projects that seek to advance regenerative approaches towards clinical use. However, the high cost of Machine Learning in the Life Sciences stifles market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Machine Learning in the Life Sciences Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America, particularly the United States, is a leading region in the machine learning in the life sciences market. The presence of major technology companies, research institutions, and pharmaceutical companies contributes to the growth of the market. The region has a well-established healthcare system, advanced research infrastructure, and supportive government initiatives promoting AI and machine learning applications in the life sciences sector. The Asia Pacific region is witnessing significant growth in the machine learning in the life sciences market. Countries such as China, Japan, and India are investing in AI and machine learning technologies to advance their healthcare systems and support research activities. The region has a large population, increasing healthcare expenditure, and a growing focus on precision medicine and personalized healthcare, driving the adoption of machine learning in the life sciences sector. Governments and industry players in the region are actively promoting AI and machine learning in healthcare and life sciences through policies, collaborations, and research initiatives.

Major market players included in this report are:

  • IBM Corporation
  • Microsoft Corporation
  • Alphabet Inc. (Google)
  • NVIDIA Corporation
  • Amazon Web Services (AWS)
  • Intel Corporation
  • Medtronic plc
  • Johnson & Johnson Services, Inc.
  • Koninklijke Philips N.V.
  • Roche Holding AG

Recent Developments in the Market:

  • In February 2020, IBM Watson Health announced a collaboration with Pfizer to use machine learning to accelerate drug discovery in immunology and oncology.
  • In September 2021, Verily launched the Project Baseline Health System Consortium, which aims to leverage machine learning to generate insights for personalized health management.
  • In December 2020, Microsoft Research collaborated with biotech company Adaptive Biotechnologies to use machine learning for decoding the human immune system and developing personalized diagnostics and therapeutics.

Global Machine Learning in the Life Sciences Market Report Scope:

  • Historical Data: 2020 - 2021
  • Base Year for Estimation: 2022
  • Forecast period: 2023-2030
  • Report Coverage: Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
  • Segments Covered: Component, Application, End User, Region
  • Regional Scope: North America; Europe; Asia Pacific; Latin America; Middle East & Africa
  • Customization Scope: Free report customization (equivalent up to 8 analyst's working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and Component offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Component:

  • Software
  • Services

By Application:

  • Drug Discovery and Development
  • Precision Medicine
  • Genomics and Proteomics
  • Medical Imaging and Diagnostics
  • Clinical Research and Trials

By End User:

  • Pharmaceutical and Biotechnology Companies
  • Academic and Research Institutions
  • Healthcare Providers
  • Contract Research Organizations (CROs)

By Region:

  • North America
  • U.S.
  • Canada
  • Europe
  • UK
  • Germany
  • France
  • Spain
  • Italy
  • ROE
  • Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
  • RoAPAC
  • Latin America
  • Brazil
  • Mexico
  • Middle East & Africa
  • Saudi Arabia
  • South Africa
  • Rest of Middle East & Africa

Table of Contents

Chapter 1. Executive Summary

  • 1.1. Market Snapshot
  • 1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
    • 1.2.1. Machine Learning in the Life Sciences Market, by Region, 2020-2030 (USD Billion)
    • 1.2.2. Machine Learning in the Life Sciences Market, by Component, 2020-2030 (USD Billion)
    • 1.2.3. Machine Learning in the Life Sciences Market, by Application, 2020-2030 (USD Billion)
    • 1.2.4. Machine Learning in the Life Sciences Market, by End User, 2020-2030 (USD Billion)
  • 1.3. Key Trends
  • 1.4. Estimation Methodology
  • 1.5. Research Assumption

Chapter 2. Global Machine Learning in the Life Sciences Market Definition and Scope

  • 2.1. Objective of the Study
  • 2.2. Market Definition & Scope
    • 2.2.1. Industry Evolution
    • 2.2.2. Scope of the Study
  • 2.3. Years Considered for the Study
  • 2.4. Currency Conversion Rates

Chapter 3. Global Machine Learning in the Life Sciences Market Dynamics

  • 3.1. Machine Learning in the Life Sciences Market Impact Analysis (2020-2030)
    • 3.1.1. Market Drivers
      • 3.1.1.1. Advancements in AI and machine learning technologies
      • 3.1.1.2. Increasing availability of large-scale biological and clinical datasets
      • 3.1.1.3. Growing demand for personalized medicine
    • 3.1.2. Market Challenges
      • 3.1.2.1. High Cost of Machine Learning in the Life Sciences
    • 3.1.3. Market Opportunities
      • 3.1.3.1. Rising need for efficient drug discovery
      • 3.1.3.2. Growing initiatives by key market players

Chapter 4. Global Machine Learning in the Life Sciences Market Industry Analysis

  • 4.1. Porter's 5 Force Model
    • 4.1.1. Bargaining Power of Suppliers
    • 4.1.2. Bargaining Power of Buyers
    • 4.1.3. Threat of New Entrants
    • 4.1.4. Threat of Substitutes
    • 4.1.5. Competitive Rivalry
  • 4.2. Porter's 5 Force Impact Analysis
  • 4.3. PEST Analysis
    • 4.3.1. Political
    • 4.3.2. Economical
    • 4.3.3. Social
    • 4.3.4. Technological
    • 4.3.5. Environmental
    • 4.3.6. Legal
  • 4.4. Top investment opportunity
  • 4.5. Top winning strategies
  • 4.6. COVID-19 Impact Analysis
  • 4.7. Disruptive Trends
  • 4.8. Industry Expert Perspective
  • 4.9. Analyst Recommendation & Conclusion

Chapter 5. Global Machine Learning in the Life Sciences Market, by Component

  • 5.1. Market Snapshot
  • 5.2. Global Machine Learning in the Life Sciences Market by Component, Performance - Potential Analysis
  • 5.3. Global Machine Learning in the Life Sciences Market Estimates & Forecasts by Component 2020-2030 (USD Billion)
  • 5.4. Machine Learning in the Life Sciences Market, Sub Segment Analysis
    • 5.4.1. Software
    • 5.4.2. Services

Chapter 6. Global Machine Learning in the Life Sciences Market, by Application

  • 6.1. Market Snapshot
  • 6.2. Global Machine Learning in the Life Sciences Market by Application, Performance - Potential Analysis
  • 6.3. Global Machine Learning in the Life Sciences Market Estimates & Forecasts by Application 2020-2030 (USD Billion)
  • 6.4. Machine Learning in the Life Sciences Market, Sub Segment Analysis
    • 6.4.1. Drug Discovery and Development
    • 6.4.2. Precision Medicine
    • 6.4.3. Genomics and Proteomics
    • 6.4.4. Medical Imaging and Diagnostics
    • 6.4.5. Clinical Research and Trials

Chapter 7. Global Machine Learning in the Life Sciences Market, by End User

  • 7.1. Market Snapshot
  • 7.2. Global Machine Learning in the Life Sciences Market by End User, Performance - Potential Analysis
  • 7.3. Global Machine Learning in the Life Sciences Market Estimates & Forecasts by End User 2020-2030 (USD Billion)
  • 7.4. Machine Learning in the Life Sciences Market, Sub Segment Analysis
    • 7.4.1. Pharmaceutical and Biotechnology Companies
    • 7.4.2. Academic and Research Institutions
    • 7.4.3. Healthcare Providers
    • 7.4.4. Contract Research Organizations (CROs)

Chapter 8. Global Machine Learning in the Life Sciences Market, Regional Analysis

  • 8.1. Top Leading Countries
  • 8.2. Top Emerging Countries
  • 8.3. Machine Learning in the Life Sciences Market, Regional Market Snapshot
  • 8.4. North America Machine Learning in the Life Sciences Market
    • 8.4.1. U.S. Machine Learning in the Life Sciences Market
      • 8.4.1.1. Component breakdown estimates & forecasts, 2020-2030
      • 8.4.1.2. Application breakdown estimates & forecasts, 2020-2030
      • 8.4.1.3. End User breakdown estimates & forecasts, 2020-2030
    • 8.4.2. Canada Machine Learning in the Life Sciences Market
  • 8.5. Europe Machine Learning in the Life Sciences Market Snapshot
    • 8.5.1. U.K. Machine Learning in the Life Sciences Market
    • 8.5.2. Germany Machine Learning in the Life Sciences Market
    • 8.5.3. France Machine Learning in the Life Sciences Market
    • 8.5.4. Spain Machine Learning in the Life Sciences Market
    • 8.5.5. Italy Machine Learning in the Life Sciences Market
    • 8.5.6. Rest of Europe Machine Learning in the Life Sciences Market
  • 8.6. Asia-Pacific Machine Learning in the Life Sciences Market Snapshot
    • 8.6.1. China Machine Learning in the Life Sciences Market
    • 8.6.2. India Machine Learning in the Life Sciences Market
    • 8.6.3. Japan Machine Learning in the Life Sciences Market
    • 8.6.4. Australia Machine Learning in the Life Sciences Market
    • 8.6.5. South Korea Machine Learning in the Life Sciences Market
    • 8.6.6. Rest of Asia Pacific Machine Learning in the Life Sciences Market
  • 8.7. Latin America Machine Learning in the Life Sciences Market Snapshot
    • 8.7.1. Brazil Machine Learning in the Life Sciences Market
    • 8.7.2. Mexico Machine Learning in the Life Sciences Market
  • 8.8. Middle East & Africa Machine Learning in the Life Sciences Market
    • 8.8.1. Saudi Arabia Machine Learning in the Life Sciences Market
    • 8.8.2. South Africa Machine Learning in the Life Sciences Market
    • 8.8.3. Rest of Middle East & Africa Machine Learning in the Life Sciences Market

Chapter 9. Competitive Intelligence

  • 9.1. Key Company SWOT Analysis
    • 9.1.1. Company 1
    • 9.1.2. Company 2
    • 9.1.3. Company 3
  • 9.2. Top Market Strategies
  • 9.3. Company Profiles
    • 9.3.1. IBM Corporation
      • 9.3.1.1. Key Information
      • 9.3.1.2. Overview
      • 9.3.1.3. Financial (Subject to Data Availability)
      • 9.3.1.4. Product Summary
      • 9.3.1.5. Recent Developments
    • 9.3.2. Microsoft Corporation
    • 9.3.3. Alphabet Inc. (Google)
    • 9.3.4. NVIDIA Corporation
    • 9.3.5. Amazon Web Services (AWS)
    • 9.3.6. Intel Corporation
    • 9.3.7. Medtronic plc
    • 9.3.8. Johnson & Johnson Services, Inc.
    • 9.3.9. Koninklijke Philips N.V.
    • 9.3.10. Roche Holding AG

Chapter 10. Research Process

  • 10.1. Research Process
    • 10.1.1. Data Mining
    • 10.1.2. Analysis
    • 10.1.3. Market Estimation
    • 10.1.4. Validation
    • 10.1.5. Publishing
  • 10.2. Research Attributes
  • 10.3. Research Assumption

LIST OF TABLES

  • TABLE 1. Global Machine Learning in the Life Sciences Market, report scope
  • TABLE 2. Global Machine Learning in the Life Sciences Market estimates & forecasts by Region 2020-2030 (USD Billion)
  • TABLE 3. Global Machine Learning in the Life Sciences Market estimates & forecasts by Component 2020-2030 (USD Billion)
  • TABLE 4. Global Machine Learning in the Life Sciences Market estimates & forecasts by Application 2020-2030 (USD Billion)
  • TABLE 5. Global Machine Learning in the Life Sciences Market estimates & forecasts by End User 2020-2030 (USD Billion)
  • TABLE 6. Global Machine Learning in the Life Sciences Market by segment, estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 7. Global Machine Learning in the Life Sciences Market by region, estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 8. Global Machine Learning in the Life Sciences Market by segment, estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 9. Global Machine Learning in the Life Sciences Market by region, estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 10. Global Machine Learning in the Life Sciences Market by segment, estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 11. Global Machine Learning in the Life Sciences Market by region, estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 12. Global Machine Learning in the Life Sciences Market by segment, estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 13. Global Machine Learning in the Life Sciences Market by region, estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 14. Global Machine Learning in the Life Sciences Market by segment, estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 15. Global Machine Learning in the Life Sciences Market by region, estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 16. U.S. Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 17. U.S. Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 18. U.S. Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 19. Canada Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 20. Canada Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 21. Canada Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 22. UK Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 23. UK Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 24. UK Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 25. Germany Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 26. Germany Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 27. Germany Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 28. France Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 29. France Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 30. France Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 31. Italy Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 32. Italy Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 33. Italy Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 34. Spain Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 35. Spain Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 36. Spain Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 37. RoE Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 38. RoE Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 39. RoE Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 40. China Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 41. China Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 42. China Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 43. India Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 44. India Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 45. India Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 46. Japan Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 47. Japan Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 48. Japan Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 49. South Korea Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 50. South Korea Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 51. South Korea Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 52. Australia Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 53. Australia Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 54. Australia Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 55. RoAPAC Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 56. RoAPAC Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 57. RoAPAC Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 58. Brazil Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 59. Brazil Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 60. Brazil Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 61. Mexico Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 62. Mexico Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 63. Mexico Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 64. RoLA Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 65. RoLA Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 66. RoLA Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 67. Saudi Arabia Machine Learning in the Life Sciences Market estimates & forecasts, 2020-2030 (USD Billion)
  • TABLE 68. South Africa Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 69. RoMEA Machine Learning in the Life Sciences Market estimates & forecasts by segment 2020-2030 (USD Billion)
  • TABLE 70. List of secondary sources, used in the study of global Machine Learning in the Life Sciences Market
  • TABLE 71. List of primary sources, used in the study of global Machine Learning in the Life Sciences Market
  • TABLE 72. Years considered for the study
  • TABLE 73. Exchange rates considered

List of tables and figures and dummy in nature, final lists may vary in the final deliverable

LIST OF FIGURES

  • FIG 1. Global Machine Learning in the Life Sciences Market, research methodology
  • FIG 2. Global Machine Learning in the Life Sciences Market, Market estimation techniques
  • FIG 3. Global Market size estimates & forecast methods
  • FIG 4. Global Machine Learning in the Life Sciences Market, key trends 2022
  • FIG 5. Global Machine Learning in the Life Sciences Market, growth prospects 2023-2030
  • FIG 6. Global Machine Learning in the Life Sciences Market, porters 5 force model
  • FIG 7. Global Machine Learning in the Life Sciences Market, pest analysis
  • FIG 8. Global Machine Learning in the Life Sciences Market, value chain analysis
  • FIG 9. Global Machine Learning in the Life Sciences Market by segment, 2020 & 2030 (USD Billion)
  • FIG 10. Global Machine Learning in the Life Sciences Market by segment, 2020 & 2030 (USD Billion)
  • FIG 11. Global Machine Learning in the Life Sciences Market by segment, 2020 & 2030 (USD Billion)
  • FIG 12. Global Machine Learning in the Life Sciences Market by segment, 2020 & 2030 (USD Billion)
  • FIG 13. Global Machine Learning in the Life Sciences Market by segment, 2020 & 2030 (USD Billion)
  • FIG 14. Global Machine Learning in the Life Sciences Market, regional snapshot 2020 & 2030
  • FIG 15. North America Machine Learning in the Life Sciences Market 2020 & 2030 (USD Billion)
  • FIG 16. Europe Machine Learning in the Life Sciences Market 2020 & 2030 (USD Billion)
  • FIG 17. Asia pacific Machine Learning in the Life Sciences Market 2020 & 2030 (USD Billion)
  • FIG 18. Latin America Machine Learning in the Life Sciences Market 2020 & 2030 (USD Billion)
  • FIG 19. Middle East & Africa Machine Learning in the Life Sciences Market 2020 & 2030 (USD Billion)

List of tables and figures and dummy in nature, final lists may vary in the final deliverable

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