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Artificial Intelligence / AI in Drug Discovery Market by Offering, Process (Target selection, Validation, Lead Generation, Optimization), Drug Design (Small Molecule, Vaccine, Antibody, PK/PD), Dry Lab, Wet Lab (Single Cell analysis) & Region - Global Forecast to 2028

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  • 369 Pages
  • November 2023
  • Region: Global
  • Markets and Markets
  • ID: 4858630
The artificial intelligence (AI) in drug discovery market is projected to reach USD 4.9 billion by 2028 from USD 0.9 billion in 2023, at a CAGR of 40.2% during the forecast period. AI expedites the identification and validation of potential drug targets by analyzing intricate biological data. This accelerates the selection of biologically relevant targets for therapeutic interventions. AI techniques such as machine learning enable rapid analysis and decision-making, reducing the time and resources required for drug discovery processes. This efficiency gains a competitive edge in the fast-paced pharmaceutical landscape. Therefore, aforementioned factors will drive the growth of this market. On the other hand, the inadequate availability of skilled labor is key factor restraining the market growth to a certain extent over the forecast period.   

Services segment is estimated to hold the major share in 2022 and also expected to grow at the highest over the forecast period.

Based on offering, the AI in drug discovery market is bifurcated into software and services. The2022 and segment expected to account for the largest market share of the global AI in drug discovery services market in 2022 and expected to grow fastest CAGR during the forecast period. Access to AI technology and expertise through services reduces the barriers for pharmaceutical companies to adopt AI in drug discovery. This is particularly beneficial for smaller companies without extensive in-house AI capabilities, enabling them to harness the power of AI without significant upfront investments.  

Machine learning technology segment accounted for the largest share of the global AI in drug discovery market.

Based on technology, the AI in drug discovery market is segmented into machine learning, natural language processing (NLP), context aware processing, and other technologies. The machine learning segment accounted for the largest share of the global market in 2022 and expected to grow at the highest CAGR during the forecast period. Machine learning enables the creation of predictive models that anticipate the behavior of potential drug candidates within the human body. This aids in identifying compounds with the highest likelihood of success, reducing the costs and time associated with unsuccessful candidates. Machine learning contributes to the development of personalized treatment strategies by analyzing patient data to predict individual responses to drugs. This facilitates tailoring treatments based on genetic, molecular, and clinical information, leading to more effective outcomes, which helps accelerate the drug discovery process are some of the factors supporting the market growth of this segment.   

Small Molecule Design and Optimization segment expected to hold the largest share of use case segment of the market in 2022.

Based on use cases, the AI in drug discovery market is divided into small molecule design and optimization, understanding disease, safety and toxicity, vaccine design and optimization, antibody and other biologics design and optimization. In 2022, the small molecule design and optimization segment accounted for the largest share of the AI in drug discovery market. AI is employed in small molecule design and optimization for two main purposes. Firstly, it aids in identifying hit-like or lead-like compounds by screening existing chemical libraries or through generative de novo design. Secondly, AI optimizes the identified hits, ensuring favorable properties like binding affinity, toxicity, and synthesis, ultimately leading to the development of more effective and safer drug candidates. These factors contribute to the development and refinement of AI algorithms tailored for drug discovery use cases.  

North America to dominate the AI in drug discovery market in 2022.

The global AI in the drug discovery market is segmented into four major regions, namely, North America, Europe, APAC, and the Rest of the World. In 2022, North America accounted for the largest and the fastest-growing regional market for AI in drug discovery. North America hosts numerous pharmaceutical giants and biotechnology innovators that are actively exploring AI's capabilities in drug discovery. These industry leaders are investing significantly in AI-driven research and development, driving market growth. North America's well-established regulatory framework for pharmaceuticals and healthcare facilitates the integration of AI technologies while ensuring compliance with industry standards and guidelines. The above-mentioned factors will drive the market of AI in drug discovery in North America.  

Breakdown of supply-side, demand side, primary interviews, by company type, designation, and region: 

  • By Supply Side: Tier 1 (31%), Tier 2 (28%), and Tier 3 (41%)
  • By Demand Side: Purchase Managers (45%), Head of Artificial Intelligence, Machine Learning, Drug Discovery, and Computational Molecular Design (30%) and Research Scientists (25%).
  • By Designation: C-level (31%), Director-level (25%), and Others (44%)
  • By Region: North America (45%), Europe (20%), Asia Pacific (28%), South America (4%) and Middle East & Africa (3%).
The prominent players in this market are NVIDIA Corporation (US), Exscientia (UK), BenevolentAI (UK), Recursion (US), Insilico Medicine (US), Schrödinger, Inc. (US), Microsoft Corporation (US), Google (US), Atomwise Inc. (US), Illumina, Inc. (US), NuMedii, Inc. (US), XtalPi Inc. (US), Iktos (France), Tempus Labs (US), Deep Genomics, Inc. (Canada), Verge Genomics (US), BenchSci (Canada), Insitro (US), Valo Health (US), BPGbio, Inc. (US), IQVIA Inc (US), Labcorp (US), Tencent Holdings Limited (China), Predictive Oncology, Inc. (US), Celsius Therapeutics (US), CytoReason (Israel), Owkin, Inc. (US), Cloud Pharmaceuticals (US), Evaxion Biotech (Denmark), Standigm (South Korea), BIOAGE (US), Envisagenics (US), and Aria Pharmaceuticals, Inc. (US). Players adopted organic as well as inorganic growth strategies such as product launches and enhancements, and investments, partnerships, collaborations, joint ventures, funding, acquisition, expansions, agreements, sales contracts, and alliances to increase their offerings, cater to the unmet needs of customers, increase their profitability, and expand their presence in the global market.  

Research Coverage

  • The report studies the AI in drug discovery market based on offering, technology, therapeutic area, use case, process, end user, and region. 
  • The report analyzes factors (such as drivers, restraints, opportunities, and challenges) affecting the market growth. 
  • The report evaluates the opportunities and challenges in the market for stakeholders and provides details of the competitive landscape for market leaders. 
  • The report studies micro-markets with respect to their growth trends, prospects, and contributions to the total AI in drug discovery market.
  • The report forecasts the revenue of market segments with respect to five major regions. 

Reasons to Buy the Report 

The report can help established firms as well as new entrants/smaller firms to gauge the pulse of the market, which, in turn, would help them garner a greater share. Firms purchasing the report could use one or a combination of the below-mentioned five strategies.  

This report provides insights into the following pointers:

  • Analysis of key drivers (growing number of cross-industry collaborations and partnerships, growing need to control drug discovery & development costs and reduce time involved in drug development, patent expiry of several drugs), restraints (shortage of AI workforce and ambiguous regulatory guidelines for medical software), opportunities (growing biotechnology industry, emerging markets, focus on developing human-aware AI systems, growth in the drugs and biologics market despite the COVID-19 pandemic), and challenges (limited availability of data sets) influencing the growth of AI in drug discovery market.
  • Product Development/Innovation: Detailed insights on upcoming technologies, research and development activities, and product launches in the AI in drug discovery market.
  • Market Development: Comprehensive information about lucrative emerging markets. The report analyzes the markets for various types of AI in drug discovery solutions across regions.
  • Market Diversification: Exhaustive information about products, untapped regions, recent developments, and investments in the AI in drug discovery market.
  • Competitive Assessment: In-depth assessment of market shares, strategies, products, distribution networks, and manufacturing capabilities of the leading players in the AI in drug discovery market.

Table of Contents

1 Introduction
1.1 Objectives of the Study
1.2 Market Definition
1.3 Inclusions & Exclusions
1.4 Market Scope
1.4.1 Market Segmentation
1.4.2 Regional Scope
1.5 Years Considered
1.6 Currency Considered
1.7 Stakeholders
1.8 Summary of Changes
1.8.1 Recession Impact

2 Research Methodology
2.1 Research Data
2.2 Secondary Data
2.2.1 Key Data from Secondary Sources
2.3 Primary Data
2.3.1 Key Data from Primary Sources
2.3.2 Key Industry Insights
2.3.3 Breakdown of Primary Interviews
2.4 Market Size Estimation
2.4.1 Bottom Up Approach
2.4.2 Top Down Approach
2.5 Market Share Estimation
2.6 Market Breakdown and Data Triangulation
2.6.1 AI in Drug Discovery Market Analysis Through Primary Interviews
2.7 Research Assumptions
2.8 Risk Assessment
2.9 Limitations
2.10 Impact of Recession on AI in Drug Discovery Market

3 Executive Summary
4 Premium Insights
4.1 Opportunities in AI in Drug Discovery Market
4.2 Market, by Region
4.3 Market: Geographic Growth Opportunities
4.4 North American Market, by Use Case and Country, 2022
4.5 Market, by Offering
4.6 Market, by Technology
4.7 Market, by Therapeutic Area
4.8 Market, by Process
4.9 Market, by Use Case
4.10 Market, by End-user

5 Market Overview
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.2 Restraints
5.2.3 Opportunities
5.2.4 Challenges

6 Industry Trends
6.1 Introduction
6.2 Key Industry Trends
6.2.1 Evolution of AI in Discovery
6.3 Technology Analysis
6.3.1 AI in Dry Lab
6.3.2 AI in Wet Lab Chemistry Software and Services Biology Software and Services Single-Cell Analysis
6.4 Porter's Five Forces Analysis
6.5 Ecosystem Analysis
6.6 Pricing Analysis
6.6.1 Average Selling Price Trend, by Region
6.6.2 Indicative Pricing Analysis, by Process
6.7 Regulatory Landscape
6.7.1 Regulatory Bodies, Government Agencies, and Other Organizations
6.8 Supply Chain Analysis
6.9 Case Study Analysis
6.10 Business Models
6.11 Patent Analysis
6.12 Key Conferences and Events (2023-2024)
6.13 Trends/Disruptions Impacting Customers’ Businesses
6.14 Ai-Derived Clinical Assets
6.15 Unmet Needs
6.15.1 Unmet Needs in AI in Drug Discovery
6.16 Key Stakeholders and Buying Criteria
6.16.1 Key Stakeholders in Buying Process
6.16.2 Buying Criteria

* Information on the Abovementioned Pointers Will be Provided Based on the Data Available in the Public Domain
* Trade Analysis is Not Included as this Market Covers Software and Services. Thus, Trade Data is Not Available for the Same.

7 AI in Drug Discovery Market, by Offering, 2021-2028 (USD Million)
7.1 Introduction
7.2 Software
7.3 Services

8 AI in Drug Discovery Market, by Technology, 2021-2028 (USD Million)
8.1 Introduction
8.2 Machine Learning
8.2.1 Deep Learning
8.2.2 Supervised Learning
8.2.3 Reinforcement Learning
8.2.4 Unsupervised Learning
8.2.5 Other Machine Learning Technologies (Semi-Supervised Learning and Others)
8.3 Natural Language Processing (Nlp)
8.4 Context-Aware Processing and Computing
8.5 Others (Bayesian Networks, and Image Processing)

9 AI in Drug Discovery Market, by Therapeutic Area, 2021-2028 (USD Million)
9.1 Introduction
9.2 Oncology
9.3 Infectious Diseases
9.4 Neurology
9.5 Metabolic
9.6 Cardiovascular
9.7 Immunology
9.8 Others (Respiratory, Nephrology, Dermatology, Genetic Disorders, Gastrointestinal, Rare Diseases, and Mental Health)

10 AI in Drug Discovery Market, by Process, 2021-2028 (USD Million)
10.1 Introduction
10.2 Target Identification & Selection
10.3 Target Validation
10.4 Hit Identification & Prioritization
10.5 Hit-To-Lead Identification/Lead Generation
10.6 Lead Optimization
10.7 Candidate Selection and Validation

11 AI in Drug Discovery Market, by Use Case, 2021-2028 (USD Million)
11.1 Introduction
11.2 Understanding Disease
11.3 Small Molecule Design and Optimization
11.4 Vaccine Design and Optimization
11.5 Antibody & Other Biologics Design and Optimization
11.6 Safety and Toxicity

12 AI in Drug Discovery Market, by End-user, 2021-2028 (USD Million)
12.1 Introduction
12.2 Pharmaceutical & Biotechnology Companies
12.3 Contract Research Organizations
12.4 Research Centers, Academic Institutes, & Government Organizations

13 AI in Drug Discovery Market, by Region, 2021-2028 (USD Million)
13.1 Introduction
13.2 North America
13.2.1 Recession Impact
13.2.2 US
13.2.3 Canada
13.2.4 Mexico
13.3 Europe
13.3.1 Recession Impact
13.3.2 Germany
13.3.3 France
13.3.4 UK
13.3.5 Italy
13.3.6 Rest of Europe
13.4 Asia-Pacific
13.4.1 Recession Impact
13.4.2 Japan
13.4.3 China
13.4.4 India
13.4.5 Rest of Asia-Pacific
13.5 South America
13.5.1 Recession Impact
13.6 Middle East & Africa
13.6.1 Recession Impact

14 Competitive Landscape
14.1 Overview
14.2 Strategies Adopted by Key Market Players
14.3 Revenue Share Analysis of Top Market Players, 2022
14.4 Market Share Analysis, 2022
14.5 Company Evaluation Quadrant for Key Players
14.5.1 Stars
14.5.2 Emerging Leaders
14.5.3 Pervasive Players
14.5.4 Participants
14.5.5 Company Footprint
14.6 Company Evaluation Quadrant for Startups/Smes
14.6.1 Progressive Companies
14.6.2 Responsive Companies
14.6.3 Dynamic Companies
14.6.4 Starting Blocks
14.6.5 Competitive Benchmarking
14.7 Competitive Scenarios and Trends
14.7.1 Product Launches & Upgrades
14.7.2 Deals
14.7.3 Others

15 Company Profiles
15.1 Key Players
15.1.1 Nvidia Corporation
15.1.2 Exscientia
15.1.3 Google
15.1.4 Benevolentai
15.1.5 Recursion
15.1.6 Insilico Medicine
15.1.7 Schrödinger, Inc.
15.1.8 Microsoft Corporation
15.1.9 Atomwise Inc.
15.1.10 Illumina, Inc.
15.1.11 Numedii, Inc.
15.1.12 Xtalpi Inc.
15.1.13 Iktos
15.1.14 Tempus Labs
15.1.15 Deep Genomics, Inc.
15.1.16 Verge Genomics
15.1.17 Bpgbio, Inc.
15.1.18 Benchsci
15.1.19 Valo Health
15.1.20 Insitro
15.2 Other Players
15.2.1 Tencent
15.2.2 Predictive Oncology, Inc.
15.2.3 Iqvia Inc
15.2.4 Labcorp
15.2.5 Celsius Therapeutics
15.2.6 Cytoreason
15.2.7 Owkin
15.2.8 Cloud Pharmaceuticals
15.2.9 Evaxion Biotech
15.2.10 Standigm
15.2.11 Bioage Labs
15.2.12 Envisagenics
15.2.13 Aria Pharmaceuticals, Inc.

* Financial Information and Analyst's View Would be Provided for Public Listed Companies Only.
* this is a Non-Exhaustive List of Companies and Might Change at the Time of Report Delivery.
*Details on Company Overview, Financials, Product & Services, Strategy, and Developments Might Not be Captured in Case of Unlisted Companies

16 Appendix
16.1 Insights of Industry Experts
16.2 Discussion Guide
16.3 Knowledge Store: The Subscription Portal
16.4 Customization Options

Companies Mentioned

  • Aria Pharmaceuticals, Inc.
  • Atomwise Inc.
  • Benchsci
  • Benevolentai
  • Bioage Labs
  • Bpgbio, Inc.
  • Celsius Therapeutics
  • Cloud Pharmaceuticals
  • Cytoreason
  • Deep Genomics, Inc.
  • Envisagenics
  • Evaxion Biotech
  • Exscientia
  • Google
  • Iktos
  • Illumina, Inc.
  • Insilico Medicine
  • Insitro
  • Iqvia Inc
  • Labcorp
  • Microsoft Corporation
  • Numedii, Inc.
  • Nvidia Corporation
  • Owkin
  • Predictive Oncology, Inc.
  • Recursion
  • Schrödinger, Inc.
  • Standigm
  • Tempus Labs
  • Tencent
  • Valo Health
  • Verge Genomics
  • Xtalpi Inc.

Table Information