Global Machine Learning in Drug Discovery and Development Market Research Report 2024(Status and Outlook)
Report Overview:
The Global Machine Learning in Drug Discovery and Development Market Size was estimated at USD 1421.31 million in 2023 and is projected to reach USD 6428.87 million by 2029, exhibiting a CAGR of 28.60% during the forecast period.
This report provides a deep insight into the global Machine Learning in Drug Discovery and Development market covering all its essential aspects. This ranges from a macro overview of the market to micro details of the market size, competitive landscape, development trend, niche market, key market drivers and challenges, SWOT analysis, Porter’s five forces analysis, value chain analysis, etc.
The analysis helps the reader to shape the competition within the industries and strategies for the competitive environment to enhance the potential profit. Furthermore, it provides a simple framework for evaluating and accessing the position of the business organization. The report structure also focuses on the competitive landscape of the Global Machine Learning in Drug Discovery and Development Market, this report introduces in detail the market share, market performance, product situation, operation situation, etc. of the main players, which helps the readers in the industry to identify the main competitors and deeply understand the competition pattern of the market.
In a word, this report is a must-read for industry players, investors, researchers, consultants, business strategists, and all those who have any kind of stake or are planning to foray into the Machine Learning in Drug Discovery and Development market in any manner.
Global Machine Learning in Drug Discovery and Development Market: Market Segmentation Analysis
The research report includes specific segments by region (country), manufacturers, Type, and Application. Market segmentation creates subsets of a market based on product type, end-user or application, Geographic, and other factors. By understanding the market segments, the decision-maker can leverage this targeting in the product, sales, and marketing strategies. Market segments can power your product development cycles by informing how you create product offerings for different segments.
Key Company
IBM
Exscientia
Google(Alphabet)
Microsoft
Atomwise
Schrodinger
Aitia
Insilico Medicine
NVIDIA
XtalPi
BPGbio
Owkin
CytoReason
Deep Genomics
Cloud Pharmaceuticals
BenevolentAI
Cyclica
Verge Genomics
Valo Health
Envisagenics
Euretos
BioAge Labs
Iktos
BioSymetrics
Evaxion Biotech
Aria Pharmaceuticals, Inc
Market Segmentation (by Type)
Supervised Learning
Semi-supervised Learning
Unsupervised Learning
Reinforcement Learning
Market Segmentation (by Application)
Early Drug Discovery
Preclinical Phase
Clinical Phase
Regulatory Approval
Geographic Segmentation
North America (USA, Canada, Mexico)
Europe (Germany, UK, France, Russia, Italy, Rest of Europe)
Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Rest of Asia-Pacific)
South America (Brazil, Argentina, Columbia, Rest of South America)
The Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria, South Africa, Rest of MEA)
Key Benefits of This Market Research:
Industry drivers, restraints, and opportunities covered in the study
Neutral perspective on the market performance
Recent industry trends and developments
Competitive landscape & strategies of key players
Potential & niche segments and regions exhibiting promising growth covered
Historical, current, and projected market size, in terms of value
In-depth analysis of the Machine Learning in Drug Discovery and Development Market
Overview of the regional outlook of the Machine Learning in Drug Discovery and Development Market:
Key Reasons to Buy this Report:
Access to date statistics compiled by our researchers. These provide you with historical and forecast data, which is analyzed to tell you why your market is set to change
This enables you to anticipate market changes to remain ahead of your competitors
You will be able to copy data from the Excel spreadsheet straight into your marketing plans, business presentations, or other strategic documents
The concise analysis, clear graph, and table format will enable you to pinpoint the information you require quickly
Provision of market value (USD Billion) data for each segment and sub-segment
Indicates the region and segment that is expected to witness the fastest growth as well as to dominate the market
Analysis by geography highlighting the consumption of the product/service in the region as well as indicating the factors that are affecting the market within each region
Competitive landscape which incorporates the market ranking of the major players, along with new service/product launches, partnerships, business expansions, and acquisitions in the past five years of companies profiled
Extensive company profiles comprising of company overview, company insights, product benchmarking, and SWOT analysis for the major market players
The current as well as the future market outlook of the industry concerning recent developments which involve growth opportunities and drivers as well as challenges and restraints of both emerging as well as developed regions
Includes in-depth analysis of the market from various perspectives through Porter’s five forces analysis
Provides insight into the market through Value Chain
Market dynamics scenario, along with growth opportunities of the market in the years to come
Chapter Outline
Chapter 1 mainly introduces the statistical scope of the report, market division standards, and market research methods.
Chapter 2 is an executive summary of different market segments (by region, product type, application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the Machine Learning in Drug Discovery and Development Market and its likely evolution in the short to mid-term, and long term.
Chapter 3 makes a detailed analysis of the Market's Competitive Landscape of the market and provides the market share, capacity, output, price, latest development plan, merger, and acquisition information of the main manufacturers in the market.
Chapter 4 is the analysis of the whole market industrial chain, including the upstream and downstream of the industry, as well as Porter's five forces analysis.
Chapter 5 introduces the latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 6 provides the analysis of various market segments according to product types, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 7 provides the analysis of various market segments according to application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 8 provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 9 introduces the basic situation of the main companies in the market in detail, including product sales revenue, sales volume, price, gross profit margin, market share, product introduction, recent development, etc.
Chapter 10 provides a quantitative analysis of the market size and development potential of each region in the next five years.
Chapter 11 provides a quantitative analysis of the market size and development potential of each market segment (product type and application) in the next five years.
Chapter 12 is the main points and conclusions of the report.
- 1 Research Methodology and Statistical Scope
- 1.1 Market Definition and Statistical Scope of Machine Learning in Drug Discovery and Development
- 1.2 Key Market Segments
- 1.2.1 Machine Learning in Drug Discovery and Development Segment by Type
- 1.2.2 Machine Learning in Drug Discovery and Development Segment by Application
- 1.3 Methodology & Sources of Information
- 1.3.1 Research Methodology
- 1.3.2 Research Process
- 1.3.3 Market Breakdown and Data Triangulation
- 1.3.4 Base Year
- 1.3.5 Report Assumptions & Caveats
- 2 Machine Learning in Drug Discovery and Development Market Overview
- 2.1 Global Market Overview
- 2.2 Market Segment Executive Summary
- 2.3 Global Market Size by Region
- 3 Machine Learning in Drug Discovery and Development Market Competitive Landscape
- 3.1 Global Machine Learning in Drug Discovery and Development Revenue Market Share by Company (2019-2024)
- 3.2 Machine Learning in Drug Discovery and Development Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
- 3.3 Company Machine Learning in Drug Discovery and Development Market Size Sites, Area Served, Product Type
- 3.4 Machine Learning in Drug Discovery and Development Market Competitive Situation and Trends
- 3.4.1 Machine Learning in Drug Discovery and Development Market Concentration Rate
- 3.4.2 Global 5 and 10 Largest Machine Learning in Drug Discovery and Development Players Market Share by Revenue
- 3.4.3 Mergers & Acquisitions, Expansion
- 4 Machine Learning in Drug Discovery and Development Value Chain Analysis
- 4.1 Machine Learning in Drug Discovery and Development Value Chain Analysis
- 4.2 Midstream Market Analysis
- 4.3 Downstream Customer Analysis
- 5 The Development and Dynamics of Machine Learning in Drug Discovery and Development Market
- 5.1 Key Development Trends
- 5.2 Driving Factors
- 5.3 Market Challenges
- 5.4 Market Restraints
- 5.5 Industry News
- 5.5.1 Mergers & Acquisitions
- 5.5.2 Expansions
- 5.5.3 Collaboration/Supply Contracts
- 5.6 Industry Policies
- 6 Machine Learning in Drug Discovery and Development Market Segmentation by Type
- 6.1 Evaluation Matrix of Segment Market Development Potential (Type)
- 6.2 Global Machine Learning in Drug Discovery and Development Market Size Market Share by Type (2019-2024)
- 6.3 Global Machine Learning in Drug Discovery and Development Market Size Growth Rate by Type (2019-2024)
- 7 Machine Learning in Drug Discovery and Development Market Segmentation by Application
- 7.1 Evaluation Matrix of Segment Market Development Potential (Application)
- 7.2 Global Machine Learning in Drug Discovery and Development Market Size (M USD) by Application (2019-2024)
- 7.3 Global Machine Learning in Drug Discovery and Development Market Size Growth Rate by Application (2019-2024)
- 8 Machine Learning in Drug Discovery and Development Market Segmentation by Region
- 8.1 Global Machine Learning in Drug Discovery and Development Market Size by Region
- 8.1.1 Global Machine Learning in Drug Discovery and Development Market Size by Region
- 8.1.2 Global Machine Learning in Drug Discovery and Development Market Size Market Share by Region
- 8.2 North America
- 8.2.1 North America Machine Learning in Drug Discovery and Development Market Size by Country
- 8.2.2 U.S.
- 8.2.3 Canada
- 8.2.4 Mexico
- 8.3 Europe
- 8.3.1 Europe Machine Learning in Drug Discovery and Development Market Size by Country
- 8.3.2 Germany
- 8.3.3 France
- 8.3.4 U.K.
- 8.3.5 Italy
- 8.3.6 Russia
- 8.4 Asia Pacific
- 8.4.1 Asia Pacific Machine Learning in Drug Discovery and Development Market Size by Region
- 8.4.2 China
- 8.4.3 Japan
- 8.4.4 South Korea
- 8.4.5 India
- 8.4.6 Southeast Asia
- 8.5 South America
- 8.5.1 South America Machine Learning in Drug Discovery and Development Market Size by Country
- 8.5.2 Brazil
- 8.5.3 Argentina
- 8.5.4 Columbia
- 8.6 Middle East and Africa
- 8.6.1 Middle East and Africa Machine Learning in Drug Discovery and Development Market Size by Region
- 8.6.2 Saudi Arabia
- 8.6.3 UAE
- 8.6.4 Egypt
- 8.6.5 Nigeria
- 8.6.6 South Africa
- 9 Key Companies Profile
- 9.1 IBM
- 9.1.1 IBM Machine Learning in Drug Discovery and Development Basic Information
- 9.1.2 IBM Machine Learning in Drug Discovery and Development Product Overview
- 9.1.3 IBM Machine Learning in Drug Discovery and Development Product Market Performance
- 9.1.4 IBM Machine Learning in Drug Discovery and Development SWOT Analysis
- 9.1.5 IBM Business Overview
- 9.1.6 IBM Recent Developments
- 9.2 Exscientia
- 9.2.1 Exscientia Machine Learning in Drug Discovery and Development Basic Information
- 9.2.2 Exscientia Machine Learning in Drug Discovery and Development Product Overview
- 9.2.3 Exscientia Machine Learning in Drug Discovery and Development Product Market Performance
- 9.2.4 IBM Machine Learning in Drug Discovery and Development SWOT Analysis
- 9.2.5 Exscientia Business Overview
- 9.2.6 Exscientia Recent Developments
- 9.3 Google(Alphabet)
- 9.3.1 Google(Alphabet) Machine Learning in Drug Discovery and Development Basic Information
- 9.3.2 Google(Alphabet) Machine Learning in Drug Discovery and Development Product Overview
- 9.3.3 Google(Alphabet) Machine Learning in Drug Discovery and Development Product Market Performance
- 9.3.4 IBM Machine Learning in Drug Discovery and Development SWOT Analysis
- 9.3.5 Google(Alphabet) Business Overview
- 9.3.6 Google(Alphabet) Recent Developments
- 9.4 Microsoft
- 9.4.1 Microsoft Machine Learning in Drug Discovery and Development Basic Information
- 9.4.2 Microsoft Machine Learning in Drug Discovery and Development Product Overview
- 9.4.3 Microsoft Machine Learning in Drug Discovery and Development Product Market Performance
- 9.4.4 Microsoft Business Overview
- 9.4.5 Microsoft Recent Developments
- 9.5 Atomwise
- 9.5.1 Atomwise Machine Learning in Drug Discovery and Development Basic Information
- 9.5.2 Atomwise Machine Learning in Drug Discovery and Development Product Overview
- 9.5.3 Atomwise Machine Learning in Drug Discovery and Development Product Market Performance
- 9.5.4 Atomwise Business Overview
- 9.5.5 Atomwise Recent Developments
- 9.6 Schrodinger
- 9.6.1 Schrodinger Machine Learning in Drug Discovery and Development Basic Information
- 9.6.2 Schrodinger Machine Learning in Drug Discovery and Development Product Overview
- 9.6.3 Schrodinger Machine Learning in Drug Discovery and Development Product Market Performance
- 9.6.4 Schrodinger Business Overview
- 9.6.5 Schrodinger Recent Developments
- 9.7 Aitia
- 9.7.1 Aitia Machine Learning in Drug Discovery and Development Basic Information
- 9.7.2 Aitia Machine Learning in Drug Discovery and Development Product Overview
- 9.7.3 Aitia Machine Learning in Drug Discovery and Development Product Market Performance
- 9.7.4 Aitia Business Overview
- 9.7.5 Aitia Recent Developments
- 9.8 Insilico Medicine
- 9.8.1 Insilico Medicine Machine Learning in Drug Discovery and Development Basic Information
- 9.8.2 Insilico Medicine Machine Learning in Drug Discovery and Development Product Overview
- 9.8.3 Insilico Medicine Machine Learning in Drug Discovery and Development Product Market Performance
- 9.8.4 Insilico Medicine Business Overview
- 9.8.5 Insilico Medicine Recent Developments
- 9.9 NVIDIA
- 9.9.1 NVIDIA Machine Learning in Drug Discovery and Development Basic Information
- 9.9.2 NVIDIA Machine Learning in Drug Discovery and Development Product Overview
- 9.9.3 NVIDIA Machine Learning in Drug Discovery and Development Product Market Performance
- 9.9.4 NVIDIA Business Overview
- 9.9.5 NVIDIA Recent Developments
- 9.10 XtalPi
- 9.10.1 XtalPi Machine Learning in Drug Discovery and Development Basic Information
- 9.10.2 XtalPi Machine Learning in Drug Discovery and Development Product Overview
- 9.10.3 XtalPi Machine Learning in Drug Discovery and Development Product Market Performance
- 9.10.4 XtalPi Business Overview
- 9.10.5 XtalPi Recent Developments
- 9.11 BPGbio
- 9.11.1 BPGbio Machine Learning in Drug Discovery and Development Basic Information
- 9.11.2 BPGbio Machine Learning in Drug Discovery and Development Product Overview
- 9.11.3 BPGbio Machine Learning in Drug Discovery and Development Product Market Performance
- 9.11.4 BPGbio Business Overview
- 9.11.5 BPGbio Recent Developments
- 9.12 Owkin
- 9.12.1 Owkin Machine Learning in Drug Discovery and Development Basic Information
- 9.12.2 Owkin Machine Learning in Drug Discovery and Development Product Overview
- 9.12.3 Owkin Machine Learning in Drug Discovery and Development Product Market Performance
- 9.12.4 Owkin Business Overview
- 9.12.5 Owkin Recent Developments
- 9.13 CytoReason
- 9.13.1 CytoReason Machine Learning in Drug Discovery and Development Basic Information
- 9.13.2 CytoReason Machine Learning in Drug Discovery and Development Product Overview
- 9.13.3 CytoReason Machine Learning in Drug Discovery and Development Product Market Performance
- 9.13.4 CytoReason Business Overview
- 9.13.5 CytoReason Recent Developments
- 9.14 Deep Genomics
- 9.14.1 Deep Genomics Machine Learning in Drug Discovery and Development Basic Information
- 9.14.2 Deep Genomics Machine Learning in Drug Discovery and Development Product Overview
- 9.14.3 Deep Genomics Machine Learning in Drug Discovery and Development Product Market Performance
- 9.14.4 Deep Genomics Business Overview
- 9.14.5 Deep Genomics Recent Developments
- 9.15 Cloud Pharmaceuticals
- 9.15.1 Cloud Pharmaceuticals Machine Learning in Drug Discovery and Development Basic Information
- 9.15.2 Cloud Pharmaceuticals Machine Learning in Drug Discovery and Development Product Overview
- 9.15.3 Cloud Pharmaceuticals Machine Learning in Drug Discovery and Development Product Market Performance
- 9.15.4 Cloud Pharmaceuticals Business Overview
- 9.15.5 Cloud Pharmaceuticals Recent Developments
- 9.16 BenevolentAI
- 9.16.1 BenevolentAI Machine Learning in Drug Discovery and Development Basic Information
- 9.16.2 BenevolentAI Machine Learning in Drug Discovery and Development Product Overview
- 9.16.3 BenevolentAI Machine Learning in Drug Discovery and Development Product Market Performance
- 9.16.4 BenevolentAI Business Overview
- 9.16.5 BenevolentAI Recent Developments
- 9.17 Cyclica
- 9.17.1 Cyclica Machine Learning in Drug Discovery and Development Basic Information
- 9.17.2 Cyclica Machine Learning in Drug Discovery and Development Product Overview
- 9.17.3 Cyclica Machine Learning in Drug Discovery and Development Product Market Performance
- 9.17.4 Cyclica Business Overview
- 9.17.5 Cyclica Recent Developments
- 9.18 Verge Genomics
- 9.18.1 Verge Genomics Machine Learning in Drug Discovery and Development Basic Information
- 9.18.2 Verge Genomics Machine Learning in Drug Discovery and Development Product Overview
- 9.18.3 Verge Genomics Machine Learning in Drug Discovery and Development Product Market Performance
- 9.18.4 Verge Genomics Business Overview
- 9.18.5 Verge Genomics Recent Developments
- 9.19 Valo Health
- 9.19.1 Valo Health Machine Learning in Drug Discovery and Development Basic Information
- 9.19.2 Valo Health Machine Learning in Drug Discovery and Development Product Overview
- 9.19.3 Valo Health Machine Learning in Drug Discovery and Development Product Market Performance
- 9.19.4 Valo Health Business Overview
- 9.19.5 Valo Health Recent Developments
- 9.20 Envisagenics
- 9.20.1 Envisagenics Machine Learning in Drug Discovery and Development Basic Information
- 9.20.2 Envisagenics Machine Learning in Drug Discovery and Development Product Overview
- 9.20.3 Envisagenics Machine Learning in Drug Discovery and Development Product Market Performance
- 9.20.4 Envisagenics Business Overview
- 9.20.5 Envisagenics Recent Developments
- 9.21 Euretos
- 9.21.1 Euretos Machine Learning in Drug Discovery and Development Basic Information
- 9.21.2 Euretos Machine Learning in Drug Discovery and Development Product Overview
- 9.21.3 Euretos Machine Learning in Drug Discovery and Development Product Market Performance
- 9.21.4 Euretos Business Overview
- 9.21.5 Euretos Recent Developments
- 9.22 BioAge Labs
- 9.22.1 BioAge Labs Machine Learning in Drug Discovery and Development Basic Information
- 9.22.2 BioAge Labs Machine Learning in Drug Discovery and Development Product Overview
- 9.22.3 BioAge Labs Machine Learning in Drug Discovery and Development Product Market Performance
- 9.22.4 BioAge Labs Business Overview
- 9.22.5 BioAge Labs Recent Developments
- 9.23 Iktos
- 9.23.1 Iktos Machine Learning in Drug Discovery and Development Basic Information
- 9.23.2 Iktos Machine Learning in Drug Discovery and Development Product Overview
- 9.23.3 Iktos Machine Learning in Drug Discovery and Development Product Market Performance
- 9.23.4 Iktos Business Overview
- 9.23.5 Iktos Recent Developments
- 9.24 BioSymetrics
- 9.24.1 BioSymetrics Machine Learning in Drug Discovery and Development Basic Information
- 9.24.2 BioSymetrics Machine Learning in Drug Discovery and Development Product Overview
- 9.24.3 BioSymetrics Machine Learning in Drug Discovery and Development Product Market Performance
- 9.24.4 BioSymetrics Business Overview
- 9.24.5 BioSymetrics Recent Developments
- 9.25 Evaxion Biotech
- 9.25.1 Evaxion Biotech Machine Learning in Drug Discovery and Development Basic Information
- 9.25.2 Evaxion Biotech Machine Learning in Drug Discovery and Development Product Overview
- 9.25.3 Evaxion Biotech Machine Learning in Drug Discovery and Development Product Market Performance
- 9.25.4 Evaxion Biotech Business Overview
- 9.25.5 Evaxion Biotech Recent Developments
- 9.26 Aria Pharmaceuticals, Inc
- 9.26.1 Aria Pharmaceuticals, Inc Machine Learning in Drug Discovery and Development Basic Information
- 9.26.2 Aria Pharmaceuticals, Inc Machine Learning in Drug Discovery and Development Product Overview
- 9.26.3 Aria Pharmaceuticals, Inc Machine Learning in Drug Discovery and Development Product Market Performance
- 9.26.4 Aria Pharmaceuticals, Inc Business Overview
- 9.26.5 Aria Pharmaceuticals, Inc Recent Developments
- 10 Machine Learning in Drug Discovery and Development Regional Market Forecast
- 10.1 Global Machine Learning in Drug Discovery and Development Market Size Forecast
- 10.2 Global Machine Learning in Drug Discovery and Development Market Forecast by Region
- 10.2.1 North America Market Size Forecast by Country
- 10.2.2 Europe Machine Learning in Drug Discovery and Development Market Size Forecast by Country
- 10.2.3 Asia Pacific Machine Learning in Drug Discovery and Development Market Size Forecast by Region
- 10.2.4 South America Machine Learning in Drug Discovery and Development Market Size Forecast by Country
- 10.2.5 Middle East and Africa Forecasted Consumption of Machine Learning in Drug Discovery and Development by Country
- 11 Forecast Market by Type and by Application (2025-2030)
- 11.1 Global Machine Learning in Drug Discovery and Development Market Forecast by Type (2025-2030)
- 11.2 Global Machine Learning in Drug Discovery and Development Market Forecast by Application (2025-2030)
- 12 Conclusion and Key Findings
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