AI in Drug Discovery Market by Offering (Software, Service), Technology (Machine Learning, Deep Learning), Application (Cardiovascular, Metabolic, Neurodegenerative), End User (Pharma, Biotech, CROs) - Global Forecast to 2027
The global AI in drug discovery market in terms of revenue was estimated to be worth $0.6 billion in 2022 and is poised to reach $5.0 billion by 2027, growing at a CAGR of 45.7% from 2022 to 2027. The growing need to curb drug discovery costs and reduce time involved in the drug development process, the rising adoption of cloud-based applications and services, and the impending patent expiry of blockbuster drugs are some of the key factors driving the growth of this market.
However, shortage of AI workforce and ambiguous regulatory guidelines for medical software and lack of data sets in this field are some of the factors expected to restrain the growth of this market in the coming years.
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Ai In Drug Discovery Market Dynamics
Growth Drivers: What benefits AI show in drug discovery and development process?
Drug discovery is a very costly and lengthy process, owing to which there is a need for alternative tools for discovering new drugs. Drug discovery and development are commonly conducted through in vivo and in vitro methods, which are very costly and time-consuming. Several players operating in AI drug discovery market are developing platforms that can help in the rapid discovery of drugs.
Growth Opportunities: What are the emerging markets for AI in drug discovery?
Emerging economies such as India, China, and countries in the Middle East are expected to offer potential growth opportunities for players operating in the AI in drug discovery market. In most of these countries, the demand for pharmaceuticals is expected to increase significantly, owing to the rising incidence of chronic and infectious diseases, increasing income levels, and improving healthcare infrastructure. As a result, these markets are very attractive for companies whose profit margins are affected by stagnation in mature markets, the patent expiration of drugs, and increasing regulatory hurdles.
Restraints: How and why AI workforce shortage is important retraining factor holding back the growth?
AI is a complex system, and companies require a workforce with specific skill sets to design, manage, and implement AI systems. Personnel dealing with AI systems should be familiar and aware of technologies such as machine intelligence, deep learning, cognitive computing, image recognition and other AI technologies. Additionally, integrating AI technologies into existing systems is a challenging task that necessitates substantial data processing in order to replicate human brain behavior. Even slight errors might cause system failure and have a negative impact on the desired outcome. The absence of professional standards and certifications in AI/ML technologies is restraining the growth of this market
Deep learning technology segment accounted for the largest share
Based on type, the machine learning technology segment further segmented into deep learning, supervised learning. reinforcement learning, unsupervised learning, and other machine learning technologies. Deep learning segment accounted for the largest share of the market, and this segment also expected to grow at the highest CAGR during the forecast period. Deep learning helps in managing data in a consistent manner, saves time, reduces the chances of errors in the drug discovery process, and reduces the workload for end users are some of the key factors for the market growth of this segment.
Services segment expected to hold the largest share
Based on offering, this market is segmented into software and services. The services segment expected to account for the largest market share of this market, and also expected to grow at the highest CAGR ahead. The benefits associated with AI services and the strong demand for AI services among end users are the key factors driving the growth of this market segment.
The neurodegenerative diseases segment projected to grow at the highest CAGR during the forecast period
On the basis of application, this market is segmented into neurodegenerative diseases, immuno-oncology, cardiovascular diseases, metabolic diseases, and other applications. Neurodegenerative diseases form the fastest-growing application segment in this market. The ability of AI to discover drugs for complex diseases and the emphasis of market players on providing AI-based platforms for neurological diseases are responsible for the high growth rate of the neurodegenerative diseases segment
North America accounted for the largest share of the global AI in drug discovery market
This market is segmented into four key regions—North America, Europe, APAC, and the Rest of the World (RoW). North America, being the early adopter of advanced technologies, has captured the largest share of this market, followed by Europe and APAC. It is also projected to register the highest CAGR. Currently, North America is home to a number of prominent AI technology providers as well as leading start-up firms. Other market drivers include the well-established pharmaceutical industry, high focus on R&D and substantial R&D investments, and the strong presence of leading pharmaceutical companies such as Pfizer (US), Abbott Laboratories (US), and Johnson & Johnson (US) in the region.
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Some of the key players of AI in drug discovery market are Microsoft Corporation (US), Exscientia (UK), NVIDIA Corporation (US), Schrödinger (US), Atomwise, Inc. (US), BenevolentAI (UK), NuMedii (US), Google (US), Insilico Medicine (US), BERG LLC (US), Cloud Pharmaceuticals (US), Cyclica (Canada), Deep Genomics (Canada), IBM (US), BIOAGE (US), Valo Health (US), Envisagenics (US), twoXAR (US), XtalPi (US), Verge Genomics (US), Owkin, Inc. (US), Biovista (US), Evaxion Biotech (Denmark), Iktos (France), Standigm (South Korea), and BenchSci (Canada). These players are increasingly focusing on collaboration, partnership, acquisition and product/services upgrade to expand their product offerings and presence in the global market.
AI in Drug Discovery Market Report Scope
|
Report Metric |
Details |
|
Market Revenue in 2022 |
$0.6 billion |
|
Estimated Value by 2027 |
$4.0 billion |
|
Growth Rate |
poised to grow at a CAGR of 45.7% |
|
Largest Share Segments |
Deep learning technology & Services |
|
Market Report Segmentation |
Offering, Technology, Application, End User & Region |
|
Growth Drivers |
|
|
Growth Opportunities |
|
|
Geographies covered |
North America, Europe, APAC, MEA, and Latin America |
The study categorizes the global AI in drug discovery market into the following segments and subsegments:
By Offering
- Software
- Services
By Technology
- Machine Learning
- Deep Learning
- Supervised Learning
- Reinforcement Learning
- Unsupervised Learning
- Other Machine Learning Technologies
- Other Technologies
By Application
- Immuno-oncology
- Neurodegenerative diseases
- Cardiovascular diseases
- Metabolic diseases
- Other Applications
By End User
- Pharmaceutical & biotechnology companies
- Contract research organizations
- Research centers and academic & government institutes
By Region
-
North America
- US
- Canada
-
Europe
- Germany
- France
- UK
- Italy
- Rest of Europe
-
Asia Pacific
- Japan
- China
- India
- Rest of Asia Pacific
- ROW
Frequently Asked Questions (FAQs):
What is the size of AI in Drug Discovery Market?
The global ai in drug discovery Market size is projected to reach USD 4.0 billion by 2027, growing at a CAGR of 45.7%.
Why is AI in Drug Discovery Market Growing?
The growing need to curb drug discovery costs and reduce time involved in the drug development process, the rising adoption of cloud-based applications and services, and the impending patent expiry of blockbuster drugs are some of the key factors driving the growth of this market.
Who all are the prominent players of AI in Drug Discovery Market?
Some of the key players of AI in drug discovery market are Microsoft Corporation (US), Exscientia (UK), NVIDIA Corporation (US), Schrödinger (US), Atomwise, Inc. (US), BenevolentAI (UK), NuMedii (US), Google (US), Insilico Medicine (US), BERG LLC (US), Cloud Pharmaceuticals (US), Cyclica (Canada), Deep Genomics (Canada), IBM (US), BIOAGE (US), Valo Health (US), Envisagenics (US), twoXAR (US), XtalPi (US), Verge Genomics (US), Owkin, Inc. (US), Biovista (US), Evaxion Biotech (Denmark), Iktos (France), Standigm (South Korea), and BenchSci (Canada). These players are increasingly focusing on collaboration, partnership, acquisition and product/services upgrade to expand their product offerings and presence in the global market.
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TABLE OF CONTENTS
1 INTRODUCTION (Page No. - 26)
1.1 OBJECTIVES OF THE STUDY
1.2 MARKET DEFINITION
1.2.1 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET: INCLUSIONS & EXCLUSIONS
1.3 MARKET SCOPE
1.3.1 MARKETS COVERED
FIGURE 1 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY: MARKET SEGMENTATION
1.3.2 YEARS CONSIDERED FOR THE STUDY
1.4 CURRENCY
1.5 LIMITATIONS
1.6 STAKEHOLDERS
1.7 SUMMARY OF CHANGES
2 RESEARCH METHODOLOGY (Page No. - 31)
2.1 RESEARCH DATA
FIGURE 2 RESEARCH DESIGN
2.2 SECONDARY SOURCES
2.2.1 KEY DATA FROM SECONDARY SOURCES
2.3 PRIMARY DATA
2.3.1 PRIMARY SOURCES
2.3.2 BREAKDOWN OF PRIMARY INTERVIEWS
FIGURE 3 BREAKDOWN OF PRIMARY INTERVIEWS: BY DEMAND SIDE, SUPPLY SIDE, DESIGNATION, AND REGION
2.3.2.1 Key industry insights
2.4 MARKET SIZE ESTIMATION
FIGURE 4 SUPPLY-SIDE MARKET ESTIMATION: REVENUE SHARE ANALYSIS
FIGURE 5 BOTTOM-UP APPROACH: END-USER SPENDING ON AI IN DRUG DISCOVERY
TABLE 1 FACTOR ANALYSIS
FIGURE 6 CAGR PROJECTIONS FROM THE ANALYSIS OF DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES IN THE GLOBAL MARKET (2022–2027)
FIGURE 7 CAGR PROJECTIONS: SUPPLY-SIDE ANALYSIS
FIGURE 8 TOP-DOWN APPROACH
2.5 MARKET BREAKDOWN AND DATA TRIANGULATION
FIGURE 9 DATA TRIANGULATION METHODOLOGY
TABLE 2 MARKET SIZING ASSUMPTIONS
2.6 OVERALL STUDY ASSUMPTIONS
2.7 LIMITATIONS
2.8 RISK ASSESSMENT
TABLE 3 RISK ASSESSMENT: AI IN DRUG DISCOVERY MARKET
3 EXECUTIVE SUMMARY (Page No. - 45)
FIGURE 10 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2022 VS. 2027 (USD MILLION)
FIGURE 11 GLOBAL MARKET, BY APPLICATION, 2022 VS. 2027 (USD MILLION)
FIGURE 12 GLOBAL MARKET, BY END USER, 2022 VS. 2027 (USD MILLION)
FIGURE 13 GEOGRAPHICAL SNAPSHOT OF THE GLOBAL MARKET
4 PREMIUM INSIGHTS (Page No. - 48)
4.1 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET OVERVIEW
FIGURE 14 GROWING NEED TO CONTROL DRUG DISCOVERY & DEVELOPMENT COSTS IS A KEY FACTOR DRIVING THE ADOPTION OF AI IN DRUG DISCOVERY SOLUTIONS
4.2 GLBOAL MARKET, BY OFFERING (2021–2027)
FIGURE 15 SERVICES SEGMENT TO WITNESS THE HIGHEST GROWTH DURING THE FORECAST PERIOD
4.3 GLOBAL MARKET FOR MACHINE LEARNING, BY TYPE & REGION (2021)
FIGURE 16 DEEP LEARNING SEGMENT ACCOUNTED FOR THE LARGEST MARKET SHARE IN 2021
4.4 GLOBAL MARKET: GEOGRAPHIC GROWTH OPPORTUNITIES
FIGURE 17 NORTH AMERICA IS THE FASTEST-GROWING REGIONAL MARKET FOR AI IN DRUG DISCOVERY
5 MARKET OVERVIEW (Page No. - 52)
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
FIGURE 18 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES
5.2.1 MARKET DRIVERS
5.2.1.1 Growing number of cross-industry collaborations and partnerships
TABLE 4 INDICATIVE LIST OF COLLABORATIONS AND PARTNERSHIPS (2019−2021)
5.2.1.2 Growing need to control drug discovery & development costs and reduce time involved in drug development
5.2.1.3 Patent expiry of several drugs
TABLE 5 INDICATIVE LIST OF DRUGS LOSING PATENTS IN 2022
5.2.2 MARKET RESTRAINTS
5.2.2.1 Shortage of AI workforce and ambiguous regulatory guidelines for medical software
5.2.3 MARKET OPPORTUNITIES
5.2.3.1 Growing biotechnology industry
5.2.3.2 Emerging markets
5.2.3.3 Focus on developing human-aware AI systems
5.2.3.4 Growth in the drugs and biologics market despite the COVID-19 pandemic
5.2.4 MARKET CHALLENGES
5.2.4.1 Limited availability of data sets
5.3 VALUE CHAIN ANALYSIS
FIGURE 19 AI IN DRUG DISCOVERY MARKET: VALUE CHAIN ANALYSIS (2021)
5.4 PORTER’S FIVE FORCES ANALYSIS
TABLE 6 GLOBAL MARKET: PORTER’S FIVE FORCES ANALYSIS
5.5 ECOSYSTEM
FIGURE 20 GLOBAL MARKET ECOSYSTEM
5.6 TECHNOLOGY ANALYSIS
5.7 PRICING ANALYSIS
5.8 BUSINESS MODELS
FIGURE 21 AI IN LIFE SCIENCES: BUSINESS MODELS
FIGURE 22 BENEFITS OF HYBRID BUSINESS MODELS
FIGURE 23 SPECIALIZATION OF AI COMPANIES OVER TIME
5.9 REGULATIONS
5.10 CONFERENCES AND WEBINARS
5.11 CASE STUDY ANALYSIS
5.11.1 CASE STUDY 1
5.11.2 CASE STUDY 2
6 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING (Page No. - 66)
6.1 INTRODUCTION
TABLE 7 GLOBAL MARKET, BY OFFERING, 2020–2027 (USD MILLION)
6.2 SOFTWARE
6.2.1 BENEFITS OFFERED BY SOFTWARE IN DRUG DISCOVERY & STRONG DEMAND AMONG END USERS ARE DRIVING SEGMENT GROWTH
TABLE 8 GLOBAL MARKET FOR SOFTWARE, BY REGION, 2020–2027 (USD MILLION)
TABLE 9 NORTH AMERICA: MARKET FOR SOFTWARE, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 10 EUROPE: MARKET FOR SOFTWARE, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 11 APAC: MARKET FOR SOFTWARE, BY COUNTRY, 2020–2027 (USD MILLION)
6.3 SERVICES
6.3.1 SERVICES SEGMENT TO WITNESS THE HIGHEST GROWTH DURING THE FORECAST PERIOD
TABLE 12 MARKET FOR SERVICES, BY REGION, 2020–2027 (USD MILLION)
TABLE 13 NORTH AMERICA: MARKET FOR SERVICES, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 14 EUROPE: MARKET FOR SERVICES, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 15 APAC: MARKET FOR SERVICES, BY COUNTRY, 2020–2027 (USD MILLION)
7 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY (Page No. - 72)
7.1 INTRODUCTION
TABLE 16 GLOBAL MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
7.2 MACHINE LEARNING
TABLE 17 GLOBAL MARKET FOR MACHINE LEARNING, BY TYPE, 2020–2027 (USD MILLION)
TABLE 18 GLOBAL MARKET FOR MACHINE LEARNING, BY REGION, 2020–2027 (USD MILLION)
TABLE 19 NORTH AMERICA: MARKET FOR MACHINE LEARNING, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 20 EUROPE: MARKET FOR MACHINE LEARNING, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 21 APAC: MARKET FOR MACHINE LEARNING, BY COUNTRY, 2020–2027 (USD MILLION)
7.2.1 DEEP LEARNING
7.2.1.1 Deep learning accelerates the discovery process of life-saving drugs and precision medicine
TABLE 22 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR DEEP LEARNING, BY REGION, 2020–2027 (USD MILLION)
TABLE 23 NORTH AMERICA: MARKET FOR DEEP LEARNING, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 24 EUROPE: MARKET FOR DEEP LEARNING, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 25 APAC: MARKET FOR DEEP LEARNING, BY COUNTRY, 2020–2027 (USD MILLION)
7.2.2 SUPERVISED LEARNING
7.2.2.1 Supervised learning can be applied in drug repositioning
TABLE 26 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR SUPERVISED LEARNING, BY REGION, 2020–2027 (USD MILLION)
TABLE 27 NORTH AMERICA: MARKET FOR SUPERVISED LEARNING, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 28 EUROPE: MARKET FOR SUPERVISED LEARNING, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 29 APAC: MARKET FOR SUPERVISED LEARNING, BY COUNTRY, 2020–2027 (USD MILLION)
7.2.3 REINFORCEMENT LEARNING
7.2.3.1 Insilico Medicine is a pioneer in the application of reinforcement learning in drug discovery
TABLE 30 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR REINFORCEMENT LEARNING, BY REGION, 2020–2027 (USD MILLION)
TABLE 31 NORTH AMERICA: MARKET FOR REINFORCEMENT LEARNING, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 32 EUROPE: MARKET FOR REINFORCEMENT LEARNING, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 33 APAC: MARKET FOR REINFORCEMENT LEARNING, BY COUNTRY, 2020–2027 (USD MILLION)
7.2.4 UNSUPERVISED LEARNING
7.2.4.1 Unsupervised learning can be more unpredictable than alternate models
TABLE 34 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR UNSUPERVISED LEARNING, BY REGION, 2020–2027 (USD MILLION)
TABLE 35 NORTH AMERICA: MARKET FOR UNSUPERVISED LEARNING, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 36 EUROPE: MARKET FOR UNSUPERVISED LEARNING, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 37 APAC: MARKET FOR UNSUPERVISED LEARNING, BY COUNTRY, 2020–2027 (USD MILLION)
7.2.5 OTHER MACHINE LEARNING TECHNOLOGIES
TABLE 38 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR OTHER MACHINE LEARNING TECHNOLOGIES, BY REGION, 2020–2027 (USD MILLION)
TABLE 39 NORTH AMERICA: MARKET FOR OTHER MACHINE LEARNING TECHNOLOGIES, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 40 EUROPE: MARKET FOR OTHER MACHINE LEARNING TECHNOLOGIES, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 41 APAC: MARKET FOR OTHER MACHINE LEARNING TECHNOLOGIES, BY COUNTRY, 2020–2027 (USD MILLION)
7.3 OTHER TECHNOLOGIES
TABLE 42 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR OTHER TECHNOLOGIES, BY REGION, 2020–2027 (USD MILLION)
TABLE 43 NORTH AMERICA: MARKET FOR OTHER TECHNOLOGIES, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 44 EUROPE: MARKET FOR OTHER TECHNOLOGIES, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 45 APAC: MARKET FOR OTHER TECHNOLOGIES, BY COUNTRY, 2020–2027 (USD MILLION)
8 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY APPLICATION (Page No. - 87)
8.1 INTRODUCTION
TABLE 46 GLOBAL MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
8.2 IMMUNO-ONCOLOGY
8.2.1 HIGH PREVALENCE OF CANCER AND SHORTAGE OF EFFECTIVE CANCER DRUGS TO DRIVE SEGMENT GROWTH
TABLE 47 INDICATIVE LIST OF INITIATIVES IN IMMUNO-ONCOLOGY DRUG DEVELOPMENT
TABLE 48 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR IMMUNO-ONCOLOGY, BY REGION, 2020–2027 (USD MILLION)
TABLE 49 NORTH AMERICA: MARKET FOR IMMUNO-ONCOLOGY, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 50 EUROPE: MARKET FOR IMMUNO-ONCOLOGY, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 51 APAC: MARKET FOR IMMUNO-ONCOLOGY, BY COUNTRY, 2020–2027 (USD MILLION)
8.3 NEURODEGENERATIVE DISEASES
8.3.1 AI IS BEING USED TO RESOLVE EXISTING CHALLENGES IN NEUROLOGICAL DISEASE DRUG DEVELOPMENT
TABLE 52 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR NEURODEGENERATIVE DISEASES, BY REGION, 2020–2027 (USD MILLION)
TABLE 53 NORTH AMERICA: MARKET FOR NEURODEGENERATIVE DISEASES, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 54 EUROPE: MARKET FOR NEURODEGENERATIVE DISEASES, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 55 APAC: MARKET FOR NEURODEGENERATIVE DISEASES, BY COUNTRY, 2020–2027 (USD MILLION)
8.4 CARDIOVASCULAR DISEASES
8.4.1 RISING DEMAND FOR CVD DRUGS IS DRIVING SEGMENT GROWTH
TABLE 56 INDICATIVE LIST OF DEVELOPMENTS IN CARDIOVASCULAR DRUG DEVELOPMENT
TABLE 57 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR CARDIOVASCULAR DISEASES, BY REGION, 2020–2027 (USD MILLION)
TABLE 58 NORTH AMERICA: MARKET FOR CARDIOVASCULAR DISEASES, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 59 EUROPE: MARKET FOR CARDIOVASCULAR DISEASES, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 60 APAC: MARKET FOR CARDIOVASCULAR DISEASES, BY COUNTRY, 2020–2027 (USD MILLION)
8.5 METABOLIC DISEASES
8.5.1 ROLE OF AI IN UNCOVERING SMALL-MOLECULE THERAPIES IS DRIVING ITS ADOPTION IN THIS SEGMENT
TABLE 61 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR METABOLIC DISEASES, BY REGION, 2020–2027 (USD MILLION)
TABLE 62 NORTH AMERICA: MARKET FOR METABOLIC DISEASES, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 63 EUROPE: MARKET FOR METABOLIC DISEASES, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 64 APAC: MARKET FOR METABOLIC DISEASES, BY COUNTRY, 2020–2027 (USD MILLION)
8.6 OTHER APPLICATIONS
TABLE 65 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR OTHER APPLICATIONS, BY REGION, 2020–2027 (USD MILLION)
TABLE 66 NORTH AMERICA: MARKET FOR OTHER APPLICATIONS, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 67 EUROPE: MARKET FOR OTHER APPLICATIONS, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 68 APAC: MARKET FOR OTHER APPLICATIONS, BY COUNTRY, 2020–2027 (USD MILLION)
9 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER (Page No. - 98)
9.1 INTRODUCTION
TABLE 69 GLOBAL MARKET, BY END USER, 2020–2027 (USD MILLION)
9.2 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES
9.2.1 RISING DEMAND FOR SOLUTIONS TO CUT TIME AND COSTS OF DRUG DEVELOPMENT HAS DRAWN END-USER ATTENTION TO AI
TABLE 70 INDICATIVE LIST OF DEVELOPMENTS RELATED TO THE USE OF AI IN THE PHARMACEUTICAL & BIOTECHNOLOGY INDUSTRY
TABLE 71 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES, BY REGION, 2020–2027 (USD MILLION)
TABLE 72 NORTH AMERICA: MARKET FOR PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 73 EUROPE: MARKET FOR PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 74 APAC: MARKET FOR PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES, BY COUNTRY, 2020–2027 (USD MILLION)
9.3 CONTRACT RESEARCH ORGANIZATIONS
9.3.1 GROWING TREND OF OUTSOURCING TO PROVIDE SIGNIFICANT OPPORTUNITIES FOR CONTRACT RESEARCH ORGANIZATIONS
TABLE 75 INDICATIVE LIST OF COLLABORATIONS WITH CROS
TABLE 76 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR CONTRACT RESEARCH ORGANIZATIONS, BY REGION, 2020–2027 (USD MILLION)
TABLE 77 NORTH AMERICA: MARKET FOR CONTRACT RESEARCH ORGANIZATIONS, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 78 EUROPE: MARKET FOR CONTRACT RESEARCH ORGANIZATIONS, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 79 APAC: MARKET FOR CONTRACT RESEARCH ORGANIZATIONS, BY COUNTRY, 2020–2027 (USD MILLION)
9.4 RESEARCH CENTERS AND ACADEMIC & GOVERNMENT INSTITUTES
9.4.1 THIS SEGMENT IS EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
TABLE 80 INDICATIVE LIST OF RESEARCH COLLABORATIONS
TABLE 81 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR RESEARCH CENTERS AND ACADEMIC & GOVERNMENT INSTITUTES, BY REGION, 2020–2027 (USD MILLION)
TABLE 82 NORTH AMERICA: MARKET FOR RESEARCH CENTERS AND ACADEMIC & GOVERNMENT INSTITUTES, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 83 EUROPE: MARKET FOR RESEARCH CENTERS AND ACADEMIC & GOVERNMENT INSTITUTES, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 84 APAC: MARKET FOR RESEARCH CENTERS AND ACADEMIC & GOVERNMENT INSTITUTES, BY COUNTRY, 2020–2027 (USD MILLION)
10 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY REGION (Page No. - 106)
10.1 INTRODUCTION
TABLE 85 GLOBAL MARKET, BY REGION, 2020–2027 (USD MILLION)
10.2 NORTH AMERICA
FIGURE 24 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET SNAPSHOT
TABLE 86 NORTH AMERICA: MARKET, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 87 NORTH AMERICA: MARKET, BY OFFERING, 2020–2027 (USD MILLION)
TABLE 88 NORTH AMERICA: MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
TABLE 89 NORTH AMERICA: MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
TABLE 90 NORTH AMERICA: MARKET, BY END USER, 2020–2027 (USD MILLION)
10.2.1.1 Strong economy and trend of early adoption of technologies are driving market growth in the US
TABLE 91 INDICATIVE LIST OF STRATEGIC DEVELOPMENTS IN THE US MARKET
TABLE 92 US: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2020–2027 (USD MILLION)
TABLE 93 US: MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
TABLE 94 US: MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
TABLE 95 US: MARKET, BY END USER, 2020–2027 (USD MILLION)
10.2.2 CANADA
10.2.2.1 Growing research on AI technologies and emergence of new AI-based start-ups will support market growth in Canada
TABLE 96 CANADA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2020–2027 (USD MILLION)
TABLE 97 CANADA: MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
TABLE 98 CANADA: MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
TABLE 99 CANADA: MARKET, BY END USER, 2020–2027 (USD MILLION)
10.2.3 MEXICO
10.2.3.1 Government initiatives to support market growth in Mexico
TABLE 100 MEXICO: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2020–2027 (USD MILLION)
TABLE 101 MEXICO: MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
TABLE 102 MEXICO: MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
TABLE 103 MEXICO: MARKET, BY END USER, 2020–2027 (USD MILLION)
10.3 EUROPE
FIGURE 25 EUROPE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET SNAPSHOT
TABLE 104 EUROPE: MARKET, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 105 EUROPE: MARKET, BY OFFERING, 2020–2027 (USD MILLION)
TABLE 106 EUROPE: MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
TABLE 107 EUROPE: MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
TABLE 108 EUROPE: MARKET, BY END USER, 2020–2027 (USD MILLION)
10.3.1 UK
10.3.1.1 UK holds the largest share of the European market
TABLE 109 INDICATIVE LIST OF STRATEGIC DEVELOPMENTS IN THE UK
TABLE 110 UK: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2020–2027 (USD MILLION)
TABLE 111 UK: MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
TABLE 112 UK: MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
TABLE 113 UK: MARKET, BY END USER, 2020–2027 (USD MILLION)
10.3.2 GERMANY
10.3.2.1 Government support and favorable training programs are key market drivers in Germany
TABLE 114 GERMANY: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2020–2027 (USD MILLION)
TABLE 115 GERMANY: MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
TABLE 116 GERMANY: MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
TABLE 117 GERMANY: MARKET, BY END USER, 2020–2027 (USD MILLION)
10.3.3 FRANCE
10.3.3.1 Strong government support and favorable strategies & initiatives to drive market growth in France
TABLE 118 FRANCE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2020–2027 (USD MILLION)
TABLE 119 FRANCE: MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
TABLE 120 FRANCE: MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
TABLE 121 FRANCE: MARKET, BY END USER, 2020–2027 (USD MILLION)
10.3.4 ITALY
10.3.4.1 Presence of a strong pharmaceutical industry in Italy to drive market growth
TABLE 122 ITALY: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2020–2027 (USD MILLION)
TABLE 123 ITALY: MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
TABLE 124 ITALY: MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
TABLE 125 ITALY: MARKET, BY END USER, 2020–2027 (USD MILLION)
10.3.5 REST OF EUROPE
TABLE 126 ROE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2020–2027 (USD MILLION)
TABLE 127 ROE: MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
TABLE 128 ROE: MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
TABLE 129 ROE: MARKET, BY END USER, 2020–2027 (USD MILLION)
10.4 ASIA PACIFIC
TABLE 130 APAC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY COUNTRY, 2020–2027 (USD MILLION)
TABLE 131 APAC: MARKET, BY OFFERING, 2020–2027 (USD MILLION)
TABLE 132 APAC: MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
TABLE 133 APAC: MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
TABLE 134 APAC: MARKET, BY END USER, 2020–2027 (USD MILLION)
10.4.1 JAPAN
10.4.1.1 Japan dominates the APAC market for AI in drug discovery
TABLE 135 JAPAN: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2020–2027 (USD MILLION)
TABLE 136 JAPAN: MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
TABLE 137 JAPAN: MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
TABLE 138 JAPAN: MARKET, BY END USER, 2020–2027 (USD MILLION)
10.4.2 CHINA
10.4.2.1 Growing CMO market and cross-industry collaborations are factors responsible for market growth in China
TABLE 139 CHINA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2020–2027 (USD MILLION)
TABLE 140 CHINA: MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
TABLE 141 CHINA: MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
TABLE 142 CHINA: MARKET, BY END USER, 2020–2027 (USD MILLION)
10.4.3 INDIA
10.4.3.1 Steady adoption of AI technologies will drive market growth in India
TABLE 143 INDIA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2020–2027 (USD MILLION)
TABLE 144 INDIA: MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
TABLE 145 INDIA: MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
TABLE 146 INDIA: MARKET, BY END USER, 2020–2027 (USD MILLION)
10.4.4 REST OF ASIA PACIFIC
TABLE 147 ROAPAC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2020–2027 (USD MILLION)
TABLE 148 ROAPAC: MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
TABLE 149 ROAPAC: MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
TABLE 150 ROAPAC: MARKET, BY END USER, 2020–2027 (USD MILLION)
10.5 REST OF THE WORLD
TABLE 151 ROW: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2020–2027 (USD MILLION)
TABLE 152 ROW: MARKET, BY TECHNOLOGY, 2020–2027 (USD MILLION)
TABLE 153 ROW: MARKET, BY APPLICATION, 2020–2027 (USD MILLION)
TABLE 154 ROW: MARKET, BY END USER, 2020–2027 (USD MILLION)
11 COMPETITIVE LANDSCAPE (Page No. - 140)
11.1 OVERVIEW
11.2 KEY PLAYER STRATEGIES/RIGHT TO WIN
11.2.1 OVERVIEW OF STRATEGIES ADOPTED BY PLAYERS IN THE AI IN DRUG DISCOVERY MARKET
11.3 MARKET RANKING ANALYSIS
TABLE 155 GLOBAL MARKET RANKING ANALYSIS, BY KEY PLAYER, 2021
11.4 COMPETITIVE BENCHMARKING
TABLE 156 GLOBAL MARKET: COMPETITIVE BENCHMARKING OF KEY PLAYERS
TABLE 157 GLOBAL MARKET: APPLICATION FOOTPRINT OF KEY PLAYERS
TABLE 158 GLOBAL MARKET: REGIONAL FOOTPRINT OF KEY PLAYERS
11.5 COMPETITIVE LEADERSHIP MAPPING
11.5.1 STARS
11.5.2 EMERGING LEADERS
11.5.3 PERVASIVE PLAYERS
11.5.4 PARTICIPANTS
FIGURE 26 AI IN DRUG DISCOVERY MARKET: GLOBAL COMPANY EVALUATION MATRIX, 2021
11.6 COMPETITIVE LEADERSHIP MAPPING – START-UPS/SMES
11.6.1 PROGRESSIVE COMPANIES
11.6.2 STARTING BLOCKS
11.6.3 RESPONSIVE COMPANIES
11.6.4 DYNAMIC COMPANIES
FIGURE 27 GLOBAL MARKET: COMPANY EVALUATION MATRIX FOR START-UPS/SMES, 2021
11.7 COMPETITIVE SITUATIONS AND TRENDS
TABLE 159 PRODUCT LAUNCHES
TABLE 160 DEALS
12 COMPANY PROFILES (Page No. - 151)
(Business Overview, Products Offered, Recent Developments, MnM View Right to win, Strategic choices made, Weaknesses and competitive threats) *
12.1 KEY PLAYERS
12.1.1 MICROSOFT
TABLE 161 MICROSOFT: BUSINESS OVERVIEW
FIGURE 28 MICROSOFT: COMPANY SNAPSHOT (2020)
TABLE 162 MICROSOFT: DEALS
12.1.2 NVIDIA
TABLE 163 NVIDIA: BUSINESS OVERVIEW
FIGURE 29 NVIDIA: COMPANY SNAPSHOT (2022)
TABLE 164 NVIDIA: EXPANSIONS
TABLE 165 NVIDIA: DEALS
12.1.3 EXSCIENTIA
TABLE 166 EXSCIENTIA: BUSINESS OVERVIEW
FIGURE 30 EXSCIENTIA: COMPANY SNAPSHOT (2021)
12.1.4 GOOGLE
TABLE 167 GOOGLE: BUSINESS OVERVIEW
FIGURE 31 GOOGLE: COMPANY SNAPSHOT (2021)
12.1.5 BENEVOLENTAI
TABLE 168 BENEVOLENTAI: BUSINESS OVERVIEW
12.1.6 NUMEDII, INC.
TABLE 169 NUMEDII: BUSINESS OVERVIEW
12.1.7 BERG, LLC
TABLE 170 BERG, LLC: BUSINESS OVERVIEW
12.1.8 ATOMWISE
TABLE 171 ATOMWISE: BUSINESS OVERVIEW
12.1.9 DEEP GENOMICS
TABLE 172 DEEP GENOMICS: BUSINESS OVERVIEW
12.1.10 INSILICO MEDICINE
TABLE 173 INSILICO MEDICINE: BUSINESS OVERVIEW
12.1.11 SCHRÖDINGER, INC.
TABLE 174 SCHRÖDINGER: BUSINESS OVERVIEW
FIGURE 32 SCHRÖDINGER: COMPANY SNAPSHOT (2021)
12.1.12 IBM
TABLE 175 IBM: BUSINESS OVERVIEW
FIGURE 33 IBM: COMPANY SNAPSHOT (2022)
TABLE 176 IBM: DEALS
TABLE 177 IBM: OTHER DEVELOPMENTS
12.2 OTHER PLAYERS
12.2.1 CYCLICA INC.
12.2.2 CLOUD PHARMACEUTICALS
12.2.3 BIOAGE
12.2.4 ENVISAGENICS
12.2.5 TWOXAR, INC. (ARIA PHARMACEUTICALS)
12.2.6 OWKIN, INC.
12.2.7 XTALPI, INC.
12.2.8 VERGE GENOMICS
12.2.9 IKTOS
12.2.10 EVAXION BIOTECH
12.2.11 STANDIGM
12.2.12 VALO HEALTH
12.2.13 BIOVISTA
12.2.14 BENCHSCI
*Details on Business Overview, Products Offered, Recent Developments, MnM View, Right to win, Strategic choices made, Weaknesses and competitive threats might not be captured in case of unlisted companies.
13 APPENDIX (Page No. - 192)
13.1 DISCUSSION GUIDE
13.2 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
13.3 AVAILABLE CUSTOMIZATIONS
13.4 RELATED REPORTS
13.5 AUTHOR DETAILS
This market research study involved the extensive use of secondary sources, directories, and databases to identify and collect information useful for this technical, market-oriented, and financial study of the AI in drug discovery market. In-depth interviews were conducted with various primary respondents, including key industry participants, subject-matter experts (SMEs), C-level executives of key market players, and industry consultants, among other experts, to obtain and verify critical qualitative and quantitative information and to assess market prospects. The size of the AI in drug discovery market was estimated through various secondary research approaches and triangulated with inputs from primary research to arrive at the final market size.
Secondary Research
The secondary sources referred to for this research study include publications from government sources, such as WHO, AAAI, EurAI, GCAAI. Secondary sources also include corporate and regulatory filings (such as annual reports, SEC filings, investor presentations, and financial statements); business magazines and research journals; press releases; and trade, business, and professional associations. Secondary data was collected and analyzed to arrive at the overall size of the global AI in drug discovery market, which was validated through primary research.
Primary Research
Extensive primary research was conducted after acquiring basic knowledge about the global AI in drug discovery market scenario through secondary research. Several primary interviews were conducted with market experts from both the demand side (Purchase manager, Heads of Artificial Intelligence, Machine Learning, Drug Discovery, and Computational Molecular Design, research scientist) and supply-side (such as C-level and D-level executives, technology experts, product managers, marketing and sales managers, distributors, and channel partners, among others) across five major regions-North America, Europe, the Asia Pacific, Latin America, Middle East and the Africa. Approximately 70% and 30% of primary interviews were conducted with supply-side and demand-side participants, respectively. This primary data was collected through questionnaires, e-mails, online surveys, personal interviews, and telephonic interviews.
To know about the assumptions considered for the study, download the pdf brochure
AI in Drug Discovery Market Size Estimation
Both top-down and bottom-up approaches were used to estimate and validate the total size of the global AI in drug discovery market. These methods were also used extensively to estimate the size of various subsegments in the market. The research methodology used to estimate the market size includes the following:
- The key players in the industry and markets have been identified through extensive secondary research.
- The revenue generated from the sale of AI in drug discovery products by leading players has been determined through primary and secondary research.
- All percentage shares, splits, and breakdowns have been determined using secondary sources and verified through primary sources.
Data Triangulation
After arriving at the overall market size, from the market size estimation process explained above, the AI in drug discovery market was split into segments and subsegments. To complete the overall market engineering process and to arrive at the exact statistics for all segments and subsegments, the data triangulation and market breakdown procedures were employed, wherever applicable. The data was triangulated by studying various factors and trends from both the demand and supply sides in the remote patient monitoring market
Report Objectives
- To define, describe, and forecast the global AI in drug discovery market based on offering, application, technology, end user, and region
- To provide detailed information regarding the major factors (such as drivers, restraints, opportunities, and challenges) influencing the market growth
- To strategically analyze micromarkets1 with respect to individual growth trends, prospects, and contributions to the overall AI in drug discovery market
- To analyze opportunities in the market for stakeholders and provide details of the competitive landscape for market leaders
- To strategically analyze the market structure and profile the key players of the AI in drug discovery market and comprehensively analyze their core competencies2
- To forecast the size of the market segments with respect to four regions, namely, North America, Europe, Asia Pacific, and the Rest of the World (Latin America and the Middle East & Africa)
- To track and analyze competitive developments such as product launches, acquisitions, partnerships, agreements, and collaborations in the AI in drug discovery market during the forecast period
Available Customizations:
With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:
Company information
- Detailed analysis and profiling of additional market players (up to 10)
Growth opportunities and latent adjacency in AI in Drug Discovery Market
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