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AI in Drug Discovery Market Poised for Rapid Growth Through 2035, Fueled by Faster R&D, Precision Medicine and Rising Biopharma Investment

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AI in Drug Discovery Market Poised for Rapid Growth Through 2035, Fueled by Faster R&D, Precision Medicine and Rising Biopharma Investment Dublin, Sept. 23, 2026 (GLOBE NEWSWIRE) -- "Artificial Intelligence in Drug Discovery Market Size, Share - Growth Analysis Report and Forecast Trends (2026-2035)" has been added to ResearchAndMarkets.com's offering.

Global Artificial Intelligence in Drug Discovery Market to Reach USD 31.79 Billion by 2035

The global artificial intelligence in drug discovery market was valued at USD 2.55 billion in 2025 and is projected to reach USD 31.79 billion by 2035. The market is expected to expand at a compound annual growth rate of 28.70% between 2026 and 2035, supported by rising pharmaceutical research and development costs, lengthy development timelines, and growing demand for more efficient drug discovery platforms.

Artificial intelligence is increasingly being integrated across target identification, compound optimization, molecular design, biomarker discovery, clinical trial planning, and outcome prediction. These capabilities can improve pipeline productivity, reduce failure rates, and accelerate the progression of therapeutic candidates toward clinical development. Increased funding, strategic partnerships, cloud-based platforms, and continued investment in precision medicine are also strengthening the global artificial intelligence in drug discovery market outlook.

Key Market Insights

Investment and Collaboration Accelerate Market Growth

Strategic investment in AI-driven drug discovery companies is increasing as pharmaceutical developers seek to improve research productivity and shorten development cycles. In March 2025, Alphabet-backed Isomorphic Labs raised USD 600 million in its first external funding round. The financing, led by Thrive Capital with participation from Alphabet and Google Ventures, is intended to advance the company's AI drug design engine and support capabilities such as protein structure prediction, absorption, distribution, metabolism, excretion, and toxicity analysis, and de novo drug design. It will also help advance therapeutic programs toward clinical trials.

Partnerships between pharmaceutical companies and AI technology specialists are another prominent market trend. In February 2026, Takeda announced a multiyear collaboration with Iambic Therapeutics valued at more than USD 1.7 billion. The collaboration focuses on AI-enabled small-molecule drug discovery for oncology and gastrointestinal diseases. It combines target identification, protein structure prediction, and de novo molecular design to improve pipeline productivity and reduce clinical development risk.

Market Segmentation

The artificial intelligence in drug discovery market is segmented by process into target identification and selection, target validation, hit identification and prioritization, hit-to-lead identification, lead generation, lead optimization, and candidate selection and validation. Lead optimization held the largest historical share, reflecting demand for technologies that can evaluate molecular properties and improve candidate selection.

Key technologies include machine learning, natural language processing, context-aware processing and computing, computer vision, and image analysis. Deployment models comprise on-premise, cloud-based, and software-as-a-service platforms. Cloud and SaaS solutions are gaining relevance because they support scalable computing, data integration, and collaboration across geographically distributed research teams.

Major applications include oncology, infectious diseases, neurology, metabolic diseases, cardiovascular diseases, immunology, mental health disorders, and other therapeutic areas. Oncology is expected to retain a leading position due to the increasing global cancer burden, sustained investment in oncology research, and expanding use of AI for target discovery, biomarker identification, compound design, and clinical trial optimization.

By end user, the market covers pharmaceutical and biopharmaceutical companies, academic and research institutes, and other organizations. Pharmaceutical and biotechnology companies remain the dominant users as they deploy AI platforms to improve R&D efficiency, expand therapeutic pipelines, and support data-driven development decisions.

Regional Market Outlook

North America holds a leading position in the global artificial intelligence in drug discovery market. The region's approximately 52% historical revenue share is supported by substantial pharmaceutical R&D expenditure, advanced healthcare and technology infrastructure, favorable investment conditions, and the presence of major pharmaceutical, biotechnology, cloud computing, and AI companies.

Europe and Asia Pacific also present significant growth opportunities as research institutions and life sciences companies increase adoption of computational drug discovery tools. Latin America, the Middle East, and Africa are expected to benefit from expanding digital healthcare infrastructure, research partnerships, and wider access to cloud-based platforms.

Leading Artificial Intelligence in Drug Discovery Companies

IBM Corporation applies advanced analytics and machine learning to target identification, molecular research, and clinical trial optimization. Deep Genomics focuses on AI-driven RNA biology, genetic target discovery, and the development of therapies for rare and genetically defined diseases. Cloud Pharmaceuticals uses physics-based modeling and machine learning to support molecular design and therapeutic candidate identification.

Microsoft Corporation provides cloud computing, predictive analytics, data integration, and collaborative research capabilities through Microsoft Azure. Other prominent artificial intelligence in drug discovery market participants include Exscientia, NVIDIA Corporation, Insilico Medicine, Atomwise, Biosymetrics, and Euretos.

The competitive landscape is increasingly shaped by funding rounds, licensing agreements, research collaborations, technology partnerships, mergers, and acquisitions. Patent activity, grants, investment trends, and strategic initiatives will remain important indicators of market development as companies compete to advance differentiated AI platforms and therapeutics.

Market Outlook for 2026-2035

The artificial intelligence in drug discovery market is positioned for substantial growth through 2035. Rising R&D expenses, demand for shorter discovery timelines, expanding biomedical datasets, and advances in predictive modeling are expected to support adoption. Although data quality, regulatory requirements, platform validation, and integration with existing research workflows remain key challenges, continued investment and collaboration are likely to expand the role of AI across the global drug development pipeline.

Key Topics Covered:

1 Preface

1.1 Objectives of the Study

1.2 Key Assumptions

1.3 Report Coverage - Key Segmentation and Scope

1.4 Research Methodology

2 Executive Summary

3 Global Artificial Intelligence in Drug Discovery Market Overview

3.1 Global Artificial Intelligence in Drug Discovery Market Historical Value (2019-2025)

3.2 Global Artificial Intelligence in Drug Discovery Market Forecast Value (2026-2035)

4 Vendor Positioning Analysis

4.1 Key Vendors

4.2 Prospective Leaders

4.3 Niche Leaders

4.4 Disruptors

5 Global Artificial Intelligence in Drug Discovery Market Landscape

5.1 Global Artificial Intelligence in Drug Discovery Market: Developers Landscape

5.1.1 Analysis by Year of Establishment

5.1.2 Analysis by Company Size

5.1.3 Analysis by Region

5.2 Global Artificial Intelligence in Drug Discovery Market: Product Landscape

5.2.1 Analysis by Process

5.2.2 Analysis by Deployment

5.2.3 Analysis by Application

6 Global Artificial Intelligence in Drug Discovery Market Dynamics

6.1 Market Drivers and Constraints

6.2 SWOT Analysis

6.2.1 Strengths

6.2.2 Weaknesses

6.2.3 Opportunities

6.2.4 Threats

6.3 PESTEL Analysis

6.3.1 Political

6.3.2 Economic

6.3.3 Social

6.3.4 Technological

6.3.5 Legal

6.3.6 Environment

6.4 Porter's Five Forces Model

6.4.1 Bargaining Power of Suppliers

6.4.2 Bargaining Power of Buyers

6.4.3 Threat of New Entrants

6.4.4 Threat of Substitutes

6.4.5 Degree of Rivalry

6.5 Key Demand Indicators

6.6 Key Price Indicators

6.7 Industry Events, Initiatives, and Trends

6.8 Value Chain Analysis

7 Global Artificial Intelligence in Drug Discovery Market Segmentation (219-2035)

7.1 Global Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

7.1.1 Market Overview

7.1.2 Target Identification and Selection

7.1.3 Target Validation

7.1.4 Hit Identification & Prioritization

7.1.5 Hit-To-Lead Identification/Lead Generation

7.1.6 Lead Optimization

7.1.7 Candidate Selection and Validation

7.2 Global Artificial Intelligence in Drug Discovery Market (2019-2035) by Technology

7.2.1 Market Overview

7.2.2 Machine Learning

7.2.3 Natural Language Processing

7.2.4 Context-Aware Processing & Computing

7.2.5 Computer Vision

7.2.6 Image Analysis

7.3 Global Artificial Intelligence in Drug Discovery Market (2019-2035) by Deployment

7.3.1 Market Overview

7.3.2 On Premise Deployment

7.3.3 Cloud Based Deployment

7.3.4 SAAS Based Deployment

7.4 Global Artificial Intelligence in Drug Discovery Market (2019-2035) by Application

7.4.1 Market Overview

7.4.2 Oncology

7.4.3 Infectious Disease

7.4.4 Neurology

7.4.5 Metabolic Diseases

7.4.6 Cardiovascular Diseases

7.4.7 Immunology

7.4.8 Mental Health Disorders

7.4.9 Others

7.5 Global Artificial Intelligence in Drug Discovery Market (2019-2035) by End User

7.5.1 Market Overview

7.5.2 Pharmaceutical and Biopharmaceutical Companies

7.5.3 Academic and Research Institutes

7.5.4 Others

7.6 Global Artificial Intelligence in Drug Discovery Market (2019-2035) by Region

7.6.1 Market Overview

7.6.2 North America

7.6.3 Europe

7.6.4 Asia Pacific

7.6.5 Latin America

7.6.6 Middle East and Africa

8 North America Artificial Intelligence in Drug Discovery Market (219-2035)

8.1 North America Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

8.1.1 Market Overview

8.1.2 Target Identification and Selection

8.1.3 Target Validation

8.1.4 Hit Identification & Prioritization

8.1.5 Hit-To-Lead Identification/Lead Generation

8.1.6 Lead Optimization

8.1.7 Candidate Selection and Validation

8.2 North America Artificial Intelligence in Drug Discovery Market (2019-2035) by Technology

8.2.1 Market Overview

8.2.2 Machine Learning

8.2.3 Natural Language Processing

8.2.4 Context-Aware Processing & Computing

8.2.5 Computer Vision

8.2.6 Image Analysis

8.3 North America Artificial Intelligence in Drug Discovery Market (2019-2035) by Deployment

8.3.1 Market Overview

8.3.2 On Premise Deployment

8.3.3 Cloud Based Deployment

8.3.4 SAAS Based Deployment

8.4 North America Artificial Intelligence in Drug Discovery Market (2019-2035) by Application

8.4.1 Market Overview

8.4.2 Oncology

8.4.3 Infectious Disease

8.4.4 Neurology

8.4.5 Metabolic Diseases

8.4.6 Cardiovascular Diseases

8.4.7 Immunology

8.4.8 Mental Health Disorders

8.4.9 Others

8.5 North America Artificial Intelligence in Drug Discovery Market (2019-2035) by End User

8.5.1 Market Overview

8.5.2 Pharmaceutical and Biopharmaceutical Companies

8.5.3 Academic and Research Institutes

8.5.4 Others

8.6 North America Artificial Intelligence in Drug Discovery Market (2019-2035) by Country

8.6.1 United States of America

8.6.1.1 United States of America Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

8.6.2 Canada

8.6.2.1 Canada Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

9 Europe Artificial Intelligence in Drug Discovery Market (219-2035)

9.1 Europe Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

9.1.1 Market Overview

9.1.2 Target Identification and Selection

9.1.3 Target Validation

9.1.4 Hit Identification & Prioritization

9.1.5 Hit-To-Lead Identification/Lead Generation

9.1.6 Lead Optimization

9.1.7 Candidate Selection and Validation

9.2 Europe Artificial Intelligence in Drug Discovery Market (2019-2035) by Technology

9.2.1 Market Overview

9.2.2 Machine Learning

9.2.3 Natural Language Processing

9.2.4 Context-Aware Processing & Computing

9.2.5 Computer Vision

9.2.6 Image Analysis

9.3 Europe Artificial Intelligence in Drug Discovery Market (2019-2035) by Deployment

9.3.1 Market Overview

9.3.2 On Premise Deployment

9.3.3 Cloud Based Deployment

9.3.4 SAAS Based Deployment

9.4 Europe Artificial Intelligence in Drug Discovery Market (2019-2035) by Application

9.4.1 Market Overview

9.4.2 Oncology

9.4.3 Infectious Disease

9.4.4 Neurology

9.4.5 Metabolic Diseases

9.4.6 Cardiovascular Diseases

9.4.7 Immunology

9.4.8 Mental Health Disorders

9.4.9 Others

9.5 Europe Artificial Intelligence in Drug Discovery Market (2019-2035) by End User

9.5.1 Market Overview

9.5.2 Pharmaceutical and Biopharmaceutical Companies

9.5.3 Academic and Research Institutes

9.5.4 Others

9.6 Europe Artificial Intelligence in Drug Discovery Market (2019-2035) by Country

9.6.1 United Kingdom

9.6.1.1 United Kingdom Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

9.6.2 Germany

9.6.2.1 Germany Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

9.6.3 France

9.6.3.1 France Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

9.6.4 Italy

9.6.4.1 Italy Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

9.6.5 Spain

9.6.5.1 Spain Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

9.6.6 Others

10 Asia Pacific Artificial Intelligence in Drug Discovery Market (219-2035)

10.1 Asia Pacific Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

10.1.1 Market Overview

10.1.2 Target Identification and Selection

10.1.3 Target Validation

10.1.4 Hit Identification & Prioritization

10.1.5 Hit-To-Lead Identification/Lead Generation

10.1.6 Lead Optimization

10.1.7 Candidate Selection and Validation

10.2 Asia Pacific Artificial Intelligence in Drug Discovery Market (2019-2035) by Technology

10.2.1 Market Overview

10.2.2 Machine Learning

10.2.3 Natural Language Processing

10.2.4 Context-Aware Processing & Computing

10.2.5 Computer Vision

10.2.6 Image Analysis

10.3 Asia Pacific Artificial Intelligence in Drug Discovery Market (2019-2035) by Deployment

10.3.1 Market Overview

10.3.2 On Premise Deployment

10.3.3 Cloud Based Deployment

10.3.4 SAAS Based Deployment

10.4 Asia Pacific Artificial Intelligence in Drug Discovery Market (2019-2035) by Application

10.4.1 Market Overview

10.4.2 Oncology

10.4.3 Infectious Disease

10.4.4 Neurology

10.4.5 Metabolic Diseases

10.4.6 Cardiovascular Diseases

10.4.7 Immunology

10.4.8 Mental Health Disorders

10.4.9 Others

10.5 Asia Pacific Artificial Intelligence in Drug Discovery Market (2019-2035) by End User

10.5.1 Market Overview

10.5.2 Pharmaceutical and Biopharmaceutical Companies

10.5.3 Academic and Research Institutes

10.5.4 Others

10.6 Asia Pacific Artificial Intelligence in Drug Discovery Market (2019-2035) by Country

10.6.1 China

10.6.1.1 China Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

10.6.2 Japan

10.6.2.1 Japan Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

10.6.3 India

10.6.3.1 India Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

10.6.4 ASEAN

10.6.4.1 ASEAN Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

10.6.5 Australia

10.6.5.1 Australia Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

10.6.6 Others

11 Latin America Artificial Intelligence in Drug Discovery Market (219-2035)

11.1 Latin America Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

11.1.1 Market Overview

11.1.2 Target Identification and Selection

11.1.3 Target Validation

11.1.4 Hit Identification & Prioritization

11.1.5 Hit-To-Lead Identification/Lead Generation

11.1.6 Lead Optimization

11.1.7 Candidate Selection and Validation

11.2 Latin America Artificial Intelligence in Drug Discovery Market (2019-2035) by Technology

11.2.1 Market Overview

11.2.2 Machine Learning

11.2.3 Natural Language Processing

11.2.4 Context-Aware Processing & Computing

11.2.5 Computer Vision

11.2.6 Image Analysis

11.3 Latin America Artificial Intelligence in Drug Discovery Market (2019-2035) by Deployment

11.3.1 Market Overview

11.3.2 On Premise Deployment

11.3.3 Cloud Based Deployment

11.3.4 SAAS Based Deployment

11.4 Latin America Artificial Intelligence in Drug Discovery Market (2019-2035) by Application

11.4.1 Market Overview

11.4.2 Oncology

11.4.3 Infectious Disease

11.4.4 Neurology

11.4.5 Metabolic Diseases

11.4.6 Cardiovascular Diseases

11.4.7 Immunology

11.4.8 Mental Health Disorders

11.4.9 Others

11.5 Latin America Artificial Intelligence in Drug Discovery Market (2019-2035) by End User

11.5.1 Market Overview

11.5.2 Pharmaceutical and Biopharmaceutical Companies

11.5.3 Academic and Research Institutes

11.5.4 Others

11.6 Latin America Artificial Intelligence in Drug Discovery Market (2019-2035) by Country

11.6.1 Brazil

11.6.1.1 Brazil Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

11.6.2 Argentina

11.6.2.1 Argentina Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

11.6.3 Mexico

11.6.3.1 Mexico Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

11.6.4 Others

12 Middle East and Africa Artificial Intelligence in Drug Discovery Market (219-2035)

12.1 Middle East and Africa Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

12.1.1 Market Overview

12.1.2 Target Identification and Selection

12.1.3 Target Validation

12.1.4 Hit Identification & Prioritization

12.1.5 Hit-To-Lead Identification/Lead Generation

12.1.6 Lead Optimization

12.1.7 Candidate Selection and Validation

12.2 Middle East and Africa Artificial Intelligence in Drug Discovery Market (2019-2035) by Technology

12.2.1 Market Overview

12.2.2 Machine Learning

12.2.3 Natural Language Processing

12.2.4 Context-Aware Processing & Computing

12.2.5 Computer Vision

12.2.6 Image Analysis

12.3 Middle East and Africa Artificial Intelligence in Drug Discovery Market (2019-2035) by Deployment

12.3.1 Market Overview

12.3.2 On Premise Deployment

12.3.3 Cloud Based Deployment

12.3.4 SAAS Based Deployment

12.4 Middle East and Africa Artificial Intelligence in Drug Discovery Market (2019-2035) by Application

12.4.1 Market Overview

12.4.2 Oncology

12.4.3 Infectious Disease

12.4.4 Neurology

12.4.5 Metabolic Diseases

12.4.6 Cardiovascular Diseases

12.4.7 Immunology

12.4.8 Mental Health Disorders

12.4.9 Others

12.5 Middle East and Africa Artificial Intelligence in Drug Discovery Market (2019-2035) by End User

12.5.1 Market Overview

12.5.2 Pharmaceutical and Biopharmaceutical Companies

12.5.3 Academic and Research Institutes

12.5.4 Others

12.6 Middle East and Africa Artificial Intelligence in Drug Discovery Market (2019-2035) by Country

12.6.1 Saudi Arabia

12.6.1.1 Saudi Arabia Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

12.6.2 United Arab Emirates

12.6.2.1 United Arab Emirates Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

12.6.3 Nigeria

12.6.3.1 Nigeria Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

12.6.4 South Africa

12.6.4.1 South Africa Artificial Intelligence in Drug Discovery Market (2019-2035) by Process

12.6.5 Others

13 Regulatory Framework

14 Patent Analysis

14.1 Analysis By Technology

14.2 Analysis by Publication Year

14.3 Analysis by Issuing Authority

14.4 Analysis by Patent Age

14.5 Analysis by CPC Analysis

14.6 Analysis by Patent Valuation

15 Grants Analysis

15.1 Analysis by Year

15.2 Analysis by Amount Awarded

15.3 Analysis by Issuing Authority

15.4 Analysis by Grant Application

15.5 Analysis by Funding Institute

15.6 Analysis by NIH Departments

15.7 Analysis by Recipient Organization

16 Funding and Investment Analysis

16.1 Analysis by Funding Instances

16.2 Analysis by Type of Funding

16.3 Analysis by Funding Amount

16.4 Analysis by Leading Players

16.5 Analysis by Leading Investors

16.6 Analysis by Geography

17 Strategic Initiatives

17.1 Analysis by Partnership Instances

17.2 Analysis by Type of Initiatives

17.3 Analysis by Leading Players

17.4 Analysis by Geography

18 Supplier Landscape

18.1 Market Share Analysis, By Region (Top 5 Companies)

18.2 IBM Corporation

18.2.1 Financial Analysis

18.2.2 Product Portfolio

18.2.3 Demographic Reach and Achievements

18.2.4 Company News and Development

18.2.5 Certifications

18.3 Exscientia

18.3.1 Financial Analysis

18.3.2 Product Portfolio

18.3.3 Demographic Reach and Achievements

18.3.4 Company News and Development

18.3.5 Certifications

18.4 Deep Genomics

18.4.1 Financial Analysis

18.4.2 Product Portfolio

18.4.3 Demographic Reach and Achievements

18.4.4 Company News and Development

18.4.5 Certifications

18.5 Cloud Pharmaceuticals, Inc.

18.5.1 Financial Analysis

18.5.2 Product Portfolio

18.5.3 Demographic Reach and Achievements

18.5.4 Company News and Development

18.5.5 Certifications

18.6 Microsoft Corporation

18.6.1 Financial Analysis

18.6.2 Product Portfolio

18.6.3 Demographic Reach and Achievements

18.6.4 Company News and Development

18.6.5 Certifications

18.7 NVIDIA Corporation

18.7.1 Financial Analysis

18.7.2 Product Portfolio

18.7.3 Demographic Reach and Achievements

18.7.4 Company News and Development

18.7.5 Certifications

18.8 Insilico Medicine

18.8.1 Financial Analysis

18.8.2 Product Portfolio

18.8.3 Demographic Reach and Achievements

18.8.4 Company News and Development

18.8.5 Certifications

18.9 Atomwise, Inc.

18.9.1 Financial Analysis

18.9.2 Product Portfolio

18.9.3 Demographic Reach and Achievements

18.9.4 Company News and Development

18.9.5 Certifications

18.10 Biosymetrics

18.10.1 Financial Analysis

18.10.2 Product Portfolio

18.10.3 Demographic Reach and Achievements

18.10.4 Company News and Development

18.10.5 Certifications

18.11 Euretos

18.11.1 Financial Analysis

18.11.2 Product Portfolio

18.11.3 Demographic Reach and Achievements

18.11.4 Company News and Development

18.11.5 Certifications

19 Key Opinion Leaders (KOL) Insights (Additional Insight)

Companies Featured

For more information about this report visit https://www.researchandmarkets.com/r/rrpbd2

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