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| A04876 | Pages: 210 | Jun 2020 | 3094 Views | | |
| Author(s) : Sayali Shinde, Sagar Mukhekar, Smita Nerkar , Onkar Sumant | Tables: 90 | Charts: 34 |
| |
Pandemic disrupted the entire world and affected many industries.
Get detailed COVID-19 impact analysis on the Artificial Intelligence For Drug Development And Discovery Market
Request Now !The artificial intelligence for drug discovery and development market size was valued at $520 million in 2019 and is projected to reach $4,815 million by 2027, registering a CAGR of 31.6% from 2020 to 2027.
Artificial intelligence is a branch in computer science that deals with the simulation of intelligent behavior. It gives computers an ability to think and perform different tasks, such as humans and animals, while learning through the errors during this process. Artificial Intelligence is usually an algorithm built in such a way that permits the computer to perform tasks efficiently while making nominal errors. It uses personified knowledge by applying deep learning and machine learning algorithms while performing several tasks.
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Artificial intelligence has significant applications in the drug discovery field as it helps track diseases, create disease cures and predict which animal viruses appear to mutate. Artificial intelligence has been known to enhance R&D in drug discovery, which has helped researchers to discover chronic disease treatments. Drug discovery and development in the fields of medicine, pharmacology, and biotechnology are processes for the creation, design, and procurement of a drug through identifying a biological target, such as enzyme protein, gene, or receptor. Previously, the drugs were discovered by identifying the active ingredient conventional treatments. Thus, drug discovery is the first step in the process of identifying potential novel drugs and their medicinal purpose. New criteria for drugs are measured based on their bioavailability, efficacy, potency, and toxicity.
In the healthcare industry, artificial intelligence has been widely used, specifically in finding novel drugs. This has the ability to identify drug targets, and plays a significant role in efficiently identifying, developing, detecting and screening small molecules in less time. Furthermore, market is expected to witness an exponential growth during the forecast period, owing to benefits of using these advanced techniques over conventional procedures. Moreover, the market is majorly driven by growing number of industry collaborations and partnerships. In addition, artificial intelligence reduces cost and time utilized in the drug discovery process, which further boosts the market growth. However, lack of skilled professionals and lack of data sets in the field of drug discovery hinder the market growth. On the contrary, increase in awareness related to artificial intelligence is expected to provide significant profitable opportunities for manufacturers in the artificial intelligence for drug discovery and development industry.
It is estimated that artificial intelligence for drug discovery and development market would show a significant market growth due to Covid-19 pandemic, owing to rise in adoption of AI to discover & develop drugs for treatment of COVID-19. For instance, in June 2020 Repurpose.AI collaborated with Scripps Research to develop COVID-19 therapeutics with a focus on drug repurposing. Artificial Intelligence based drug screening techniques will theoretically help to explain important part of the virus (such as protein structure) to assess how the functions of the virus can play an integral role in drug design and accelerate vaccine technologies to fight COVID-19. Moreover, Artificial intelligence can boost drug discovery and development process by quickly identifying drugs having efficacy against COVID-19. This bridge the gap between number of repurposed drugs (using existing drugs for other diseases), clinical testing and final drug authorization process.
The artificial intelligence for drug discovery and development market is segmented on the type, indication, end user and region. By type, it is divided into target identification, molecules screening, de novo drug design & drug optimization and preclinical &clinical testing. On the basis of indication, it is classified into oncology, infectious disease, neurology, and others. By end user, it is segmented into pharmaceutical & biotechnology companies, and CROs. Region wise, the market is analyzed across North America (US, Canada), Europe (Germany, France, UK, Rest of Europe), Asia-Pacific (Japan, China, Australia, India, Rest of Asia-Pacific), and LAMEA (Latin America and Middle East and Africa).
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By type, the preclinical and clinical testing segment occupied the highest share in 2019, owing to rise in number of collaborations between pharma companies and AI providers for clinical and preclinical testing. Preclinical trial is a stage of research that starts before clinical trials, during which iterative testing, important feasibility and drug safety data are collected for the development of drugs. Preclinical trials require analytics software to follow a precise scientific standard of drug development and to discover more advanced drug candidates from laboratory to clinical trials. The De Novo drug design and drug optimization segment is projected to witness the fastest growth rate during the forecast period owing to increase in adoption of AI for De novo studies.
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By indication, the oncology segment is projected to witness growth at the highest CAGR during the forecast period, owing to increase in adoption of AI to discover drug for treatment of different forms of cancer, large number of promising drugs in the oncology pipeline, higher adoption of AI to discover & develop oncology drugs and increase in number of collaborations between large pharma companies and AI providers are majorly driving the growth of this segment.
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North America held the major artificial intelligence for drug discovery and development market share in 2019 and is expected to continue its dominance during the forecast period, owing to strong economies such as the U.S. and Canada; high adoption rate of AI technologies due to large number of investments to boost the drug discovery industry; and large number of cross industry collaborations and partnerships, which majorly fuel the market growth. However, Asia-Pacific is expected to grow at the highest CAGR during the forecast period, owing to rise in adoption of advanced AI technologies, and growth in focus of major players on increasing their presence in emerging Asian countries.
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Comprehensive competitive analysis and profiles of the major artificial intelligence for drug discovery and development market players such as Alphabet Inc., Atomwise, Inc., Benevolent AI, Cloud Pharmaceutical, Deep Genomics, Exscientia, IBM Corporation, Insilico Medicine Inc., Microsoft Corporation, and Nvidia Corporation are provided in this report.
Key Benefits For Stakeholders
The study provides an in-depth analysis of the global artificial intelligence for drug discovery and development market along with the current trends and future estimations to elucidate the imminent investment pockets.
It offers a quantitative analysis from 2019 to 2027, which is expected to enable the stakeholders to capitalize on the prevailing artificial intelligence for drug discovery and development market opportunities.
A comprehensive analysis of all the regions is provided to determine the existing opportunities.
The profiles and growth strategies of the key players are thoroughly analyzed to understand the competitive outlook of the global market.
Key Market Segments
By Type
By Indication
By End User
By Geography
CHAPTER 1: INTRODUCTION
1.1. Report description
1.1. Key benefits for stakeholders
1.2. Key market segments
1.2.1. List of key players profiled in the report
1.3. Research methodology
1.3.1. Secondary research
1.3.2. Primary research
1.3.3. Analyst tools and models
CHAPTER 2: EXECUTIVE SUMMARY
2.1. CXO perspective
CHAPTER 3: MARKET OVERVIEW
3.1. Market definition and scope
3.2. Key findings
3.2.1. Top investment pockets
3.2.2. Top winning strategies
3.3. Top player positioning, 2019
3.4. Porter’s five forces analysis
3.5. Market dynamics
3.5.1. Drivers
3.5.1.1. Growing number of cross industry collaborations and partnerships
3.5.1.2. Artificial intelligence reduces cost and time utilized in the drug discovery& development process.
3.5.2. Restraints
3.5.2.1. Lack of skilled professionals
3.5.2.2. Lack of data sets in the field of drug discovery
3.5.3. Opportunity
3.5.3.1. Increase in awareness related to artificial intelligence
3.5.3.2. Untapped market in developing regions
3.5.4. Impact Analysis
CHAPTER 4: ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT MARKET, BY TYPE
4.1. Overview
4.1.1. Market size and forecast
4.2. Target Identification
4.2.1. Key market trends, growth factors, and opportunities
4.2.2. Market size and forecast, by region
4.2.3. Market analysis, by country
4.3. Molecule Screening
4.3.1. Key market trends, growth factors, and opportunities
4.3.2. Market size and forecast, by region
4.3.3. Market analysis, by country
4.4. De Novo Drug Design and Drug Optimization
4.4.1. Key market trends, growth factors, and opportunities
4.4.2. Market size and forecast, by region
4.4.3. Market analysis, by country
4.5. Preclinical and clinical testing
4.5.1. Key market trends, growth factors, and opportunities
4.5.2. Market size and forecast, by region
4.5.3. Market analysis, by country
CHAPTER 5: ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENTMARKET, BY INDICATION
5.1. Overview
5.1.1. Market size and forecast
5.2. Oncology
5.2.1. Market size and forecast, by region
5.2.2. Market analysis, by country
5.3. Neurology
5.3.1. Market size and forecast, by region
5.3.2. Market analysis, by country
5.4. Infectious Disease
5.4.1. Market size and forecast, by region
5.4.2. Market analysis, by country
5.5. Others
5.5.1. Market size and forecast, by region
5.5.2. Market analysis, by country
CHAPTER 6: ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT, BY END USER
6.1. Overview
6.1.1. Market size and forecast
6.2. Pharmaceutical and biotechnology companies
6.2.1. Market size and forecast, by region
6.2.2. Market analysis, by country
6.3. Contract Research Organization
6.3.1. Market size and forecast, by region
6.3.2. Market analysis, by country
CHAPTER 7: GLOBAL ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT MARKET, BY REGION
7.1. Overview
7.1.1. Market size and forecast
7.2. North America
7.2.1. Key market trends, growth factors, and opportunities
7.2.2. North America artificial intelligence for drug discovery and development , by country
7.2.2.1. U.S.
7.2.2.1.1. U.S. artificial intelligence for drug discovery and development market, by type
7.2.2.1.2. U.S artificial intelligence for drug discovery and development market, by indication
7.2.2.1.3. U.S. artificial intelligence for drug discovery and development market, by end user
7.2.2.2. Canada
7.2.2.2.1. Canada artificial intelligence for drug discovery and development market, by type
7.2.2.2.2. Canada artificial intelligence for drug discovery and development market, by indication
7.2.2.2.3. Canada artificial intelligence for drug discovery and development market, by end user
7.2.3. North America artificial intelligence for drug discovery and development market, by type
7.2.4. North America artificial intelligence for drug discovery and development , by indication
7.2.5. North America artificial intelligence for drug discovery and development , by end user
7.3. Europe
7.3.1. Key market trends, growth factors, and opportunities
7.3.2. Europe artificial intelligence for drug discovery and development , by country
7.3.2.1. UK artificial intelligence for drug discovery and development market, by type
7.3.2.1.1. UK artificial intelligence for drug discovery and development market, by type
7.3.2.1.2. UK artificial intelligence for drug discovery and development market, by indication
7.3.2.1.3. UK artificial intelligence for drug discovery and development market, by end user
7.3.2.2. Germany
7.3.2.2.1. Germany artificial intelligence for drug discovery and development market, by type
7.3.2.2.2. Germany artificial intelligence for drug discovery and development market, by indication
7.3.2.2.3. Germany artificial intelligence for drug discovery and development market, by end user
7.3.2.3. France
7.3.2.3.1. France artificial intelligence for drug discovery and development market, by type
7.3.2.3.2. France artificial intelligence for drug discovery and development market, by indication
7.3.2.3.3. France artificial intelligence for drug discovery and development market, by end user
7.3.2.4. Rest of Europe
7.3.2.4.1. Rest of Europe artificial intelligence for drug discovery and development market, by type
7.3.2.4.2. Rest of Europe artificial intelligence for drug discovery and development market, by indication
7.3.2.4.3. Rest of Europe artificial intelligence for drug discovery and development market, by end user
7.3.3. Europe artificial intelligence for drug discovery and development , by type
7.3.4. Europe artificial intelligence for drug discovery and development , by indication
7.3.5. Europe artificial intelligence for drug discovery and development , by end user
7.4. Asia-pacific
7.4.1. Key market trends, growth factors, and opportunities
7.4.2. Asia-Pacific artificial intelligence for drug discovery and development , by country
7.4.2.1. Japan
7.4.2.1.1. Japan artificial intelligence for drug discovery and development market, by type
7.4.2.1.2. Japan artificial intelligence for drug discovery and development market, by indication
7.4.2.1.3. Japan artificial intelligence for drug discovery and development market, by end user
7.4.2.2. China
7.4.2.2.1. China artificial intelligence for drug discovery and development market, by type
7.4.2.2.2. China artificial intelligence for drug discovery and development market, by indication
7.4.2.2.3. China artificial intelligence for drug discovery and development market, by end user
7.4.2.3. Australia
7.4.2.3.1. .Australia artificial intelligence for drug discovery and development market, by type
7.4.2.3.2. Australia artificial intelligence for drug discovery and development market, by indication
7.4.2.3.3. Australia artificial intelligence for drug discovery and development market, by end user
7.4.2.4. India
7.4.2.4.1. India artificial intelligence for drug discovery and development market, by type
7.4.2.4.2. India artificial intelligence for drug discovery and development market, by indication
7.4.2.4.3. India artificial intelligence for drug discovery and development market, by end user
7.4.2.5. Rest of Asia-Pacific
7.4.2.5.1. Rest of Asia-Pacific artificial intelligence for drug discovery and development market, by type
7.4.2.5.2. Rest of Asia-Pacific artificial intelligence for drug discovery and development market, by indication
7.4.2.5.3. Rest of Asia-Pacific artificial intelligence for drug discovery and development market, by end user
7.4.3. Asia-Pacific artificial intelligence for drug discovery and development , by type
7.4.4. Asia-Pacific artificial intelligence for drug discovery and development , by indication
7.4.5. Asia-Pacific artificial intelligence for drug discovery and development , by end user
7.5. LAMEA
7.5.1. Key market trends, growth factors, and opportunities
7.5.2. LAMEA artificial intelligence for drug discovery and development , by country
7.5.2.1. Latin America
7.5.2.1.1. Latin America artificial intelligence for drug discovery and development market, by type
7.5.2.1.2. Latin America artificial intelligence for drug discovery and development market, by indication
7.5.2.1.3. Latin America artificial intelligence for drug discovery and development market, by end user
7.5.2.2. Middle east and Africa
7.5.2.2.1. Middle east and Africa artificial intelligence for drug discovery and development market, by type
7.5.2.2.2. Middle east and Africa artificial intelligence for drug discovery and development market, by indication
7.5.2.2.3. Middle east and Africa artificial intelligence for drug discovery and development market, by end user
CHAPTER 8: COMPANY PROFILES
8.1. ALPHABET INC.
8.1.1. Company overview
8.1.2. Company snapshot
8.1.3. Operating business segments
8.1.4. Product portfolio
8.1.5. Business performance
8.2. ATOMWISE, INC.
8.2.1. Company overview
8.2.2. Company snapshot
8.2.3. Operating business segment
8.2.4. Product portfolio
8.2.5. Key strategic moves and developments
8.3. BENEVOLENT AI
8.3.1. Company overview
8.3.2. Company snapshot
8.3.3. Operating business segment
8.3.4. Product portfolio
8.3.5. Key strategic moves and developments
8.4. CLOUD PHARMACEUTICAL
8.4.1. Company overview
8.4.2. Company snapshot
8.4.3. Operating business segment
8.4.4. Product portfolio
8.4.5. Key strategic moves and developments
8.5. DEEP GENOMICS
8.5.1. Company overview
8.5.2. Company snapshot
8.5.3. Operating business segment
8.5.4. Product portfolio
8.6. EXSCIENTIA.
8.6.1. Company overview
8.6.2. Company snapshot
8.6.3. Operating business segment
8.6.4. Product portfolio
8.6.5. Key strategic moves and developments
8.7. IBM CORPORATION
8.7.1. Company overview
8.7.2. Company snapshot
8.7.3. Operating business segments
8.7.4. Product portfolio
8.7.5. Business performance
8.7.6. Key strategic moves and developments
8.8. INSILICO MEDICINE INC.
8.8.1. Company overview
8.8.2. Company snapshot
8.8.3. Operating business segment
8.8.4. Product portfolio
8.8.5. Key strategic moves and developments
8.9. MICROSOFT CORPORATION
8.9.1. Company overview
8.9.2. Company snapshot
8.9.3. Operating business segments
8.9.4. Product portfolio
8.9.5. Business performance
8.9.6. Key strategic moves and developments
8.10. NVIDIA CORPORATION
8.10.1. Company overview
8.10.2. Company snapshot
8.10.3. Operating business segments
8.10.4. Product portfolio
8.10.5. Business performance
LIST OF TABLES
TABLE 01. ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY & DEVELOPMENT MARKET, BY TYPE, 2019–2027 ($MILLION)
TABLE 02. ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY & DEVELOPMENT MARKET FORTARGET IDENTIFICATION, BY REGION, 2019–2027 ($MILLION)
TABLE 03. ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY & DEVELOPMENT MARKET FOR MOLECULE SCREENING, BY REGION, 2019–2027 ($MILLION)
TABLE 04. ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY & DEVELOPMENT MARKET FORDE NOVO DRUG DESIGN AND DRUG OPTIMIZATION, BY REGION, 2019–2027 ($MILLION)
TABLE 05. ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY & DEVELOPMENT MARKET FOR DE NOVO DRUG DESIGN AND DRUG OPTIMIZATION, BY REGION, 2019–2027 ($MILLION)
TABLE 06. ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENTMARKET, BY INDICATION, 2019–2027($MILLION)
TABLE 07. ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENTMARKET REVENUE, BY ONCOLOGY, 2019–2027 ($MILLION)
TABLE 08. ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENTMARKET REVENUE, BY NEUROLOGY, 2019–2027 ($MILLION)
TABLE 09. ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENTMARKET REVENUE, BY INFECTIOUS DISEASE, 2019–2027 ($MILLION)
TABLE 10. ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENTMARKET REVENUE, BY OTHERS, 2019–2027 ($MILLION)
TABLE 11. GLOBAL ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT MARKET, BY END USER, 2019–2027 ($MILLION)
TABLE 12. GLOBAL ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT MARKET REVENUE, BY PHARMACEUTICAL AND BIOTECHNOLOGY COMPANIES, 2019–2027 ($MILLION)
TABLE 13. GLOBAL ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT MARKET REVENUE, BY CONTRACT RESEARCH ORGANIZATION, 2019–2027 ($MILLION)
TABLE 14. GLOBAL ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT MARKET REVENUE, BY REGION, 2019–2027 ($MILLION)
TABLE 15. NORTH AMERICA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY COUNTRY, 2019-2027 ($MILLION)
TABLE 16. U.S. ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY TYPE, 2019-2027 ($MILLION)
TABLE 17. U.S. ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY INDICATION, 2019-2027 ($MILLION)
TABLE 18. U.S. ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT, BY END USER, 2019-2027 ($MILLION)
TABLE 19. CANADA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY TYPE, 2019-2027 ($MILLION)
TABLE 20. CANADA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY INDICATION, 2019-2027 ($MILLION)
TABLE 21. CANADA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY END USER, 2019-2027 ($MILLION)
TABLE 22. NORTH AMERICA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY TYPE, 2019-2027 ($MILLION)
TABLE 23. NORTH AMERICA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY INDICATION, 2019-2027 ($MILLION)
TABLE 24. NORTH AMERICA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY END USER, 2019-2027 ($MILLION)
TABLE 25. EUROPE ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY COUNTRY, 2019-2027 ($MILLION)
TABLE 26. UK ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY TYPE, 2019-2027 ($MILLION)
TABLE 27. UK ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY INDICATION, 2019-2027 ($MILLION)
TABLE 28. UK ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY END USER, 2019-2027 ($MILLION)
TABLE 29. GERMANY ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY TYPE, 2019-2027 ($MILLION)
TABLE 30. GERMANY ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY INDICATION, 2019-2027 ($MILLION)
TABLE 31. GERMANY ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY END USER, 2019-2027 ($MILLION)
TABLE 32. FRANCE ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY TYPE, 2019-2027 ($MILLION)
TABLE 33. FRANCE ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY INDICATION, 2019-2027 ($MILLION)
TABLE 34. FRANCE ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY END USER, 2019-2027 ($MILLION)
TABLE 35. REST OF EUROPE ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY TYPE, 2019-2027 ($MILLION)
TABLE 36. REST OF EUROPE ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY INDICATION, 2019-2027 ($MILLION)
TABLE 37. REST OF EUROPE ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY END USER, 2019-2027 ($MILLION)
TABLE 38. EUROPE ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY TYPE, 2019-2027 ($MILLION)
TABLE 39. EUROPE ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY INDICATION, 2019-2027 ($MILLION)
TABLE 40. EUROPE ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY END USER, 2019-2027 ($MILLION)
TABLE 41. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY COUNTRY, 2019-2027 ($MILLION)
TABLE 42. JAPAN ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY TYPE, 2019-2027 ($MILLION)
TABLE 43. JAPAN ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY INDICATION, 2019-2027 ($MILLION)
TABLE 44. JAPAN ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY END USER, 2019-2027 ($MILLION)
TABLE 45. CHINA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY TYPE, 2019-2027 ($MILLION)
TABLE 46. CHINA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY INDICATION, 2019-2027 ($MILLION)
TABLE 47. CHINA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY END USER, 2019-2027 ($MILLION)
TABLE 48. AUSTRALIA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY TYPE, 2019-2027 ($MILLION)
TABLE 49. AUSTRALIA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY INDICATION, 2019-2027 ($MILLION)
TABLE 50. AUSTRALIA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY END USER, 2019-2027 ($MILLION)
TABLE 51. INDIA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY TYPE, 2019-2027 ($MILLION)
TABLE 52. INDIA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY INDICATION, 2019-2027 ($MILLION)
TABLE 53. INDIA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY END USER, 2019-2027 ($MILLION)
TABLE 54. REST OF ASIA-PACIFIC ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY TYPE, 2019-2027 ($MILLION)
TABLE 55. REST OF ASIA-PACIFIC ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY INDICATION, 2019-2027 ($MILLION)
TABLE 56. REST OF ASIA-PACIFIC ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY END USER, 2019-2027 ($MILLION)
TABLE 57. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY TYPE, 2019-2027 ($MILLION)
TABLE 58. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY INDICATION, 2019-2027 ($MILLION)
TABLE 59. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY END USER, 2019-2027 ($MILLION)
TABLE 60. LAMEA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY COUNTRY, 2019-2027 ($MILLION)
TABLE 61. LATIN AMERICA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY TYPE, 2019-2027 ($MILLION)
TABLE 62. LATIN AMERICA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY INDICATION, 2019-2027 ($MILLION)
TABLE 63. LATIN AMERICA ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY END USER, 2019-2027 ($MILLION)
TABLE 64. MIDDLE EAST AND AFRICAARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY TYPE, 2019-2027 ($MILLION)
TABLE 65. MIDDLE EAST AND AFRICAARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY INDICATION, 2019-2027 ($MILLION)
TABLE 66. MIDDLE EAST AND AFRICAARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT , BY END USER, 2019-2027 ($MILLION)
TABLE 67. ALPHABET INC.: COMPANY SNAPSHOT
TABLE 68. ALPHABET INC.: OPERATING SEGMENTS
TABLE 69. ALPHABET INC.: PRODUCT PORTFOLIO
TABLE 70. ATOMWISE: COMPANY SNAPSHOT
TABLE 71. ATOMWISE: PRODUCT PORTFOLIO
TABLE 72. BENEVOLENT: COMPANY SNAPSHOT
TABLE 73. BENEVOLENT: PRODUCT PORTFOLIO
TABLE 74. CLOUD: COMPANY SNAPSHOT
TABLE 75. CLOUD: PRODUCT PORTFOLIO
TABLE 76. DEEP: COMPANY SNAPSHOT
TABLE 77. DEEP: PRODUCT PORTFOLIO
TABLE 78. EXSCIENTIA: COMPANY SNAPSHOT
TABLE 79. EXSCIENTIA: PRODUCT PORTFOLIO
TABLE 80. IBM CORPORATION: COMPANY SNAPSHOT
TABLE 81. IBM: OPERATING SEGMENTS
TABLE 82. IBM: PRODUCT PORTFOLIO
TABLE 83. INSILICO: COMPANY SNAPSHOT
TABLE 84. INSILICO: PRODUCT PORTFOLIO
TABLE 85. MICROSOFT CORPORATION: COMPANY SNAPSHOT
TABLE 86. MICROSOFT CORPORATION: OPERATING SEGMENTS
TABLE 87. MICROSOFT: PRODUCT PORTFOLIO
TABLE 88. NVIDIA: COMPANY SNAPSHOT
TABLE 89. NVIDIA: OPERATING SEGMENTS
TABLE 90. NVIDIA: PRODUCT PORTFOLIO
LIST OF FIGURES
FIGURE 01. ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT MARKET SEGMENTATION
FIGURE 02. TOP INVESTMENT POCKETS
FIGURE 03. TOP WINNING STRATEGIES, BY YEAR, 2017–2020*
FIGURE 04. TOP WINNING STRATEGIES, BY DEVELOPMENT, 2017–2020* (%)
FIGURE 05. TOP WINNING STRATEGIES, BY COMPANY, 2017–2020*
FIGURE 06. TOP PLAYER POSITIONING, 2019
FIGURE 07. MODERATE BARGANING POWER OF SUPPLIER
FIGURE 08. MODERATE BARGAINING POWER OF BUYERS
FIGURE 09. LOW THREAT OF NEW ENTRANT
FIGURE 10. LOW THREAT OF SUBSTITUTION
FIGURE 11. HIGH COMPETITIVE RIVALRY
FIGURE 12. IMPACT ANALYSIS
FIGURE 13. COMPARATIVE ANALYSIS OF ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY & DEVELOPMENT MARKET, FOR TARGET IDENTIFICATIONBY COUNTRY, 2019 & 2027(%)
FIGURE 14. COMPARATIVE ANALYSIS OF ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY & DEVELOPMENT MARKET, FOR MOLECULE SCREENINGBY COUNTRY, 2019 &2027 (%)
FIGURE 15. COMPARATIVE ANALYSIS OF ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY & DEVELOPMENT MARKET, FOR DE NOVO DRUG DESIGN AND DRUG OPTIMIZATION BY COUNTRY, 2019 &2027(%)
FIGURE 16. COMPARATIVE ANALYSIS OF ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY & DEVELOPMENT MARKET, FOR DE NOVO DRUG DESIGN AND DRUG OPTIMIZATION BY COUNTRY, 2019 &2027(%)
FIGURE 17. COMPARATIVE ANALYSIS OF ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENTMARKET, FOR ONCOLOGYBY COUNTRY, 2019 & 2027 (%)
FIGURE 18. COMPARATIVE ANALYSIS OF ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENTMARKET, FOR NEUROLOGY BY COUNTRY, 2019 & 2027 (%)
FIGURE 19. COMPARATIVE ANALYSIS OF ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENTMARKET, FOR INFECTIOUS DISEASEBY COUNTRY, 2019 & 2027 (%)
FIGURE 20. COMPARATIVE ANALYSIS OF ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENTMARKET, FOR OTHERSBY COUNTRY, 2019 & 2027 (%)
FIGURE 21. COMPARATIVE ANALYSIS OF ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT MARKET, FOR PHARMACEUTICAL AND BIOTECHNOLOGY COMPANIESBY COUNTRY, 2019 & 2027 (%)
FIGURE 22. COMPARATIVE ANALYSIS OF ARTIFICIAL INTELLIGENCE FOR DRUG DISCOVERY AND DEVELOPMENT MARKET, FOR CONTRACT RESEARCH ORGANIZATION BY COUNTRY, 2019 & 2027 (%)
FIGURE 23. ALPHABET INC.: REVENUE, 20187–2019 ($MILLION)
FIGURE 24. ALPHABET INC.: REVENUE SHARE BY SEGMENT, 2019 (%)
FIGURE 25. ALPHABET INC.: REVENUE SHARE BY REGION, 2019 (%)
FIGURE 26. IBM: REVENUE, 2017–2019 ($MILLION)
FIGURE 27. IBM: REVENUE SHARE BY SEGMENT, 2019 (%)
FIGURE 28. IBM: REVENUE SHARE BY REGION 2019 (%)
FIGURE 29. MICROSOFT CORPORATION: REVENUE, 2017–2019 ($MILLION)
FIGURE 30. MICROSOFT CORPORATION: REVENUE SHARE BY SEGMENT, 2019 (%)
FIGURE 31. MICROSOFT CORPORATION: REVENUE SHARE BY REGION, 2019 (%)
FIGURE 32. NVIDIA: REVENUE, 2018–2020 ($MILLION)
FIGURE 33. NVIDIA: REVENUE SHARE BY SEGMENT, 2020 (%)
FIGURE 34. NVIDIA: REVENUE SHARE BY REGION, 2020 (%)
Artificial intelligence for drug discovery and development market is witnessing intense competition, owing to rise in number of industry collaborations and partnership. In addition, artificial intelligence reduces cost and time utilized in the drug discovery process, which further boosts the market growth. Increase in awareness related to artificial intelligence is expected to provide significant opportunities for artificial intelligence providers in the pharmaceutical and biotech industry.
Analysis reports that the use of AI for drug discovery and development is highest in the North American region, owing to developed economies in the U.S. and Canada with higher adoption rate of AI technologies. In addition, large number of investments in R&D and surge in cross-industry collaborations and partnerships majorly fuels the market growth. However, Asia-Pacific is expected to grow at the highest CAGR during the forecast period, owing to rise in adoption of advanced AI technologies, and growth in focus of major players on increasing their presence in developing Asian countries..
A. The total market value of artificial intelligence for drug discovery and development Market is $519.5 million in 2019.
A. The forcast period for artificial intelligence for drug discovery and development Market is 2020 to 2027
A. The market value of artificial intelligence for drug discovery and development market in 2020 is $706.1 million.
A. The base year is 2019 in artificial intelligence for drug discovery and development Market
A. Top companies such as, Alphabet Inc., Atomwise, Inc., Benevolent AI, Cloud Pharmaceutical, Deep Genomics, Exscientia, IBM Corporation, Insilico Medicine Inc., Microsoft Corporation, and Nvidia Corporation held a high market position in 2019. These key players held a high market postion owing to the strong geographical foothold in rigions.
A. Type segment is the most influencing segment owing to rise in number of collaborations of pharma companies with AI providers for clinical and preclinical testing further contributes the market growth.
A. The major factor that fuels the growth of the artificial intelligence for drug discovery and development market includes driven by growing number of industry collaborations and partnership. In addition, artificial intelligence reduces cost and time utilized in the drug discovery process further boosts the market growth. On the contrary, increase in awareness related to artificial intelligence is expected to provide significant profitable opportunities for manufacturers in the artificial intelligence for drug discovery and development industry
A. North America has the highest growth rate in the market which is growing due to the contribution of the emerging countries. This is due to high adoption rate of AI technologies due to large number of investments to boost the drug discovery industry; and large number of cross industry collaborations and partnerships majorly fuels the market growth.
A. Artificial intelligence has known to have significant applications in the drug discovery field as it helps track diseases, create disease cures and predict which animal viruses appear to mutate. Artificial intelligence has been known to enhance research and development in drug discovery which has helped researchers to discover chronic disease treatments.
A. AI is helping drug discovery, it can help identify drug targets, find good molecules from data libraries, suggest chemical modifications, identify candidates for repurposing and so on.
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