AI In Drug Repurposing Market Size, Share & Trends Analysis Report By Component (Software & Platform, Services), By Technology (Machine Learning Algorithms, Generative AI & Large Language Models), By Application (Oncology, Rare & Orphan Diseases), By End
Description
AI In Drug Repurposing Market Summary
The global AI in drug repurposing market size was estimated at USD 1.02 billion in 2024 and is projected to reach USD 5.48 billion by 2033, growing at a CAGR of 20.39% from 2025 to 2033. Rising demand for cost-effective drug development, advancements in AI algorithms, and the growing prevalence of rare and complex diseases are significant factors contributing to market growth.
In addition, increasing collaborations between pharmaceutical companies, academic institutions, and AI technology providers, and improvements in computing power and cloud infrastructure are some other factors fueling the growth.
The rising demand for cost-effective drug development strategies substantially drives the growth of the AI in drug repurposing industry. Traditional drug discovery involves lengthy timelines, often exceeding a decade, and costs frequently exceed USD 2 billion per drug. Drug repurposing offers a strategy to bypass early-stage safety testing by focusing on approved or investigational drugs for new indications. AI accelerates this process by rapidly analyzing extensive biological, chemical, and clinical datasets to identify novel drug-disease associations. This reduces development timelines and costs, offering pharmaceutical companies and healthcare providers an economically viable alternative to de novo drug development. Integrating artificial intelligence with drug repurposing effectively addresses key industry challenges by enhancing productivity while reducing associated risks and investments.
AI systems integrate multi-omics data, including genomics, proteomics, and metabolomics, with biomedical literature and real-world patient records to identify subtle and previously unrecognized drug-target interactions. These methods enable the identification of polypharmacology candidates and synergistic drug combinations, overcoming limitations of traditional hypothesis-driven discovery. For instance, in April 2025, Plex Research partnered with Ginkgo Bioworks to use AI-powered analysis on the GDPx2 dataset, a large transcriptomics survey of compound-induced gene expression. This collaboration aims to identify novel disease mechanisms, discover new therapeutic applications, and accelerate drug repurposing, linking findings with experimental data for rigorous validation.
Furthermore, the rising prevalence of rare diseases propels market growth further. For instance, according to the data published by The Lancet Journal in March 2024, around 300 million people live with rare diseases, affecting around 3.5% - 5.9% of the global population. Moreover, around 80% of rare diseases are genetically caused, almost 70% of which are present in childhood. AI facilitates the analysis of limited datasets from rare disease cohorts, enabling the identification of therapeutic candidates from existing drugs, thus expediting treatment access.
Global AI In Drug Repurposing Market Report Segmentation
This report forecasts revenue growth at the global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2021 to 2033. For this study, Grand View Research has segmented the global AI in drug repurposing market report based on component, technology, application, end use, and region:
The global AI in drug repurposing market size was estimated at USD 1.02 billion in 2024 and is projected to reach USD 5.48 billion by 2033, growing at a CAGR of 20.39% from 2025 to 2033. Rising demand for cost-effective drug development, advancements in AI algorithms, and the growing prevalence of rare and complex diseases are significant factors contributing to market growth.
In addition, increasing collaborations between pharmaceutical companies, academic institutions, and AI technology providers, and improvements in computing power and cloud infrastructure are some other factors fueling the growth.
The rising demand for cost-effective drug development strategies substantially drives the growth of the AI in drug repurposing industry. Traditional drug discovery involves lengthy timelines, often exceeding a decade, and costs frequently exceed USD 2 billion per drug. Drug repurposing offers a strategy to bypass early-stage safety testing by focusing on approved or investigational drugs for new indications. AI accelerates this process by rapidly analyzing extensive biological, chemical, and clinical datasets to identify novel drug-disease associations. This reduces development timelines and costs, offering pharmaceutical companies and healthcare providers an economically viable alternative to de novo drug development. Integrating artificial intelligence with drug repurposing effectively addresses key industry challenges by enhancing productivity while reducing associated risks and investments.
AI systems integrate multi-omics data, including genomics, proteomics, and metabolomics, with biomedical literature and real-world patient records to identify subtle and previously unrecognized drug-target interactions. These methods enable the identification of polypharmacology candidates and synergistic drug combinations, overcoming limitations of traditional hypothesis-driven discovery. For instance, in April 2025, Plex Research partnered with Ginkgo Bioworks to use AI-powered analysis on the GDPx2 dataset, a large transcriptomics survey of compound-induced gene expression. This collaboration aims to identify novel disease mechanisms, discover new therapeutic applications, and accelerate drug repurposing, linking findings with experimental data for rigorous validation.
Furthermore, the rising prevalence of rare diseases propels market growth further. For instance, according to the data published by The Lancet Journal in March 2024, around 300 million people live with rare diseases, affecting around 3.5% - 5.9% of the global population. Moreover, around 80% of rare diseases are genetically caused, almost 70% of which are present in childhood. AI facilitates the analysis of limited datasets from rare disease cohorts, enabling the identification of therapeutic candidates from existing drugs, thus expediting treatment access.
Global AI In Drug Repurposing Market Report Segmentation
This report forecasts revenue growth at the global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2021 to 2033. For this study, Grand View Research has segmented the global AI in drug repurposing market report based on component, technology, application, end use, and region:
- Component Outlook (Revenue, USD Million, 2021 - 2033)
- Software & Platforms
- Services
- Technology Outlook (Revenue, USD Million, 2021 - 2033)
- Machine Learning/Deep Learning
- Natural Language Processing (NLP)
- Knowledge Graphs & Network-Based AI
- Generative AI & Large Language Models (LLMs)
- Computer Vision
- Application Outlook (Revenue, USD Million, 2021 - 2033)
- Oncology
- Neurology
- Cardiology
- Infectious Diseases
- Rare & Orphan Diseases
- Other Therapeutic Areas
- End Use Outlook (Revenue, USD Million, 2021 - 2033)
- Pharmaceutical & Biotechnology Companies
- Contract Research Organizations (CROs)
- Academic & Research Institutes
- Others
- Regional Outlook (Revenue, USD Million, 2021 - 2033)
- North America
- U.S.
- Canada
- Mexico
- Europe
- Germany
- UK
- France
- Italy
- Spain
- Denmark
- Sweden
- Norway
- Asia Pacific
- China
- Japan
- India
- South Korea
- Australia
- Thailand
- Latin America
- Brazil
- Argentina
- MEA
- South Africa
- Saudi Arabia
- UAE
- Kuwait
Table of Contents
100 Pages
- Chapter 1. Methodology and Scope
- 1.1. Market Segmentation & Scope
- 1.2. Market Definitions
- 1.2.1. Component Segment
- 1.2.2. Technology Segment
- 1.2.3. Application Segment
- 1.2.4. End Use
- 1.3. Information analysis
- 1.3.1. Market formulation & data visualization
- 1.4. Data validation & publishing
- 1.5. Information Procurement
- 1.5.1. Primary Research
- 1.6. Information or Data Analysis
- 1.7. Market Formulation & Validation
- 1.8. Market Model
- 1.9. Total Market: CAGR Calculation
- 1.10. Objectives
- 1.10.1. Objective 1
- 1.10.2. Objective 2
- Chapter 2. Executive Summary
- 2.1. Market Outlook
- 2.2. Segment Snapshot
- 2.3. Competitive Insights Landscape
- Chapter 3. AI in Drug Repurposing Market Variables, Trends & Scope
- 3.1. Market Lineage Outlook
- 3.1.1. Parent market outlook
- 3.1.2. Related/ancillary market outlook.
- 3.2. Market Dynamics
- 3.2.1. Market driver analysis
- 3.2.1.1. Rising demand for cost-effective drug development,
- 3.2.1.2. Advancements in AI algorithms
- 3.2.1.3. Increasing collaborations between pharmaceutical companies, academic institutions, and AI technology providers,
- 3.2.2. Market restraint analysis
- 3.2.2.1. Data security and privacy concerns
- 3.2.2.2. High computational costs and infrastructure requirements
- 3.2.3. Market opportunity analysis
- 3.2.4. Market challenges analysis
- 3.3. AI in Drug Repurposing Market Analysis Tools
- 3.3.1. Industry Analysis – Porter’s
- 3.3.1.1. Supplier power
- 3.3.1.2. Buyer power
- 3.3.1.3. Substitution threat
- 3.3.1.4. Threat of new entrant
- 3.3.1.5. Competitive rivalry
- 3.3.2. PESTEL Analysis
- 3.3.2.1. Political landscape
- 3.3.2.2. Technological landscape
- 3.3.2.3. Economic landscape
- 3.3.2.4. Environmental Landscape
- 3.3.2.5. Legal Landscape
- 3.3.2.6. Social Landscape
- 3.4. Case Studies
- 3.5. Technology Analysis: Key Use Cases and Application
- 3.5.1. Machine Learning (ML)/Deep Learning
- 3.5.2. Natural Language Processing (NLP)
- 3.5.3. Generative AI & Large Language Models (LLMs)
- Chapter 4. AI in Drug Repurposing Market: Component Estimates & Trend Analysis
- 4.1. Segment Dashboard
- 4.2. Global AI in Drug Repurposing Market Component Movement Analysis
- 4.3. Global AI in Drug Repurposing Market Size & Trend Analysis, by Component, 2021 to 2033 (USD Million)
- 4.4. Software & Platforms
- 4.4.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 4.5. Services
- 4.5.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- Chapter 5. AI in Drug Repurposing Market: Technology Estimates & Trend Analysis
- 5.1. Segment Dashboard
- 5.2. Global AI in Drug Repurposing Market Technology Movement Analysis
- 5.3. Global AI in Drug Repurposing Market Size & Trend Analysis, by Technology, 2021 to 2033 (USD Million)
- 5.4. Machine Learning/Deep Learning
- 5.4.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 5.5. Natural Language Processing (NLP)
- 5.5.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 5.6. Knowledge Graphs & Network-Based AI
- 5.6.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 5.7. Generative AI & Large Language Models (LLMs)
- 5.7.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 5.8. Computer Vision
- 5.8.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- Chapter 6. AI in Drug Repurposing Market: Application Estimates & Trend Analysis
- 6.1. Segment Dashboard
- 6.2. Global AI in Drug Repurposing Market Application Movement Analysis
- 6.3. Global AI in Drug Repurposing Market Size & Trend Analysis, by Application, 2021 to 2033 (USD Million)
- 6.4. Oncology
- 6.4.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.5. Neurology
- 6.5.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.6. Cardiology
- 6.6.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.7. Infectious Diseases
- 6.7.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.8. Rare & Orphan Diseases
- 6.8.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.9. Other Therapeutic Areas
- 6.9.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- Chapter 7. AI in Drug Repurposing Market: End Use Estimates & Trend Analysis
- 7.1. Segment Dashboard
- 7.2. Global AI in Drug Repurposing Market End Use Movement Analysis
- 7.3. Global AI in Drug Repurposing Market Size & Trend Analysis, by End Use, 2021 to 2033 (USD Million)
- 7.4. Pharmaceutical & Biotechnology Companies
- 7.4.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 7.5. Contract Research Organizations (CROs)
- 7.5.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 7.6. Academic & Research Institutes
- 7.6.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 7.7. Others
- 7.7.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- Chapter 8. AI in Drug Repurposing Market: Regional Estimates & Trend Analysis
- 8.1. Regional Market Share Analysis, 2024 & 2033
- 8.2. Regional Market Dashboard
- 8.3. Market Size & Forecasts Trend Analysis, 2021 to 2033:
- 8.4. North America
- 8.4.1. U.S.
- 8.4.1.1. Key country dynamics
- 8.4.1.2. Regulatory framework
- 8.4.1.3. Competitive scenario
- 8.4.1.4. U.S. market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.4.2. Canada
- 8.4.2.1. Key country dynamics
- 8.4.2.2. Regulatory framework
- 8.4.2.3. Competitive scenario
- 8.4.2.4. Canada market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.4.3. Mexico
- 8.4.3.1. Key country dynamics
- 8.4.3.2. Regulatory framework
- 8.4.3.3. Competitive scenario
- 8.4.3.4. Mexico market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.5. Europe
- 8.5.1. UK
- 8.5.1.1. Key country dynamics
- 8.5.1.2. Regulatory framework
- 8.5.1.3. Competitive scenario
- 8.5.1.4. UK market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.5.2. Germany
- 8.5.2.1. Key country dynamics
- 8.5.2.2. Regulatory framework
- 8.5.2.3. Competitive scenario
- 8.5.2.4. Germany market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.5.3. France
- 8.5.3.1. Key country dynamics
- 8.5.3.2. Regulatory framework
- 8.5.3.3. Competitive scenario
- 8.5.3.4. France market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.5.4. Italy
- 8.5.4.1. Key country dynamics
- 8.5.4.2. Regulatory framework
- 8.5.4.3. Competitive scenario
- 8.5.4.4. Italy market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.5.5. Spain
- 8.5.5.1. Key country dynamics
- 8.5.5.2. Regulatory framework
- 8.5.5.3. Competitive scenario
- 8.5.5.4. Spain market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.5.6. Norway
- 8.5.6.1. Key country dynamics
- 8.5.6.2. Regulatory framework
- 8.5.6.3. Competitive scenario
- 8.5.6.4. Norway market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.5.7. Sweden
- 8.5.7.1. Key country dynamics
- 8.5.7.2. Regulatory framework
- 8.5.7.3. Competitive scenario
- 8.5.7.4. Sweden market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.5.8. Denmark
- 8.5.8.1. Key country dynamics
- 8.5.8.2. Regulatory framework
- 8.5.8.3. Competitive scenario
- 8.5.8.4. Denmark market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.6. Asia Pacific
- 8.6.1. Japan
- 8.6.1.1. Key country dynamics
- 8.6.1.2. Regulatory framework
- 8.6.1.3. Competitive scenario
- 8.6.1.4. Japan market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.6.2. China
- 8.6.2.1. Key country dynamics
- 8.6.2.2. Regulatory framework
- 8.6.2.3. Competitive scenario
- 8.6.2.4. China market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.6.3. India
- 8.6.3.1. Key country dynamics
- 8.6.3.2. Regulatory framework
- 8.6.3.3. Competitive scenario
- 8.6.3.4. India market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.6.4. Australia
- 8.6.4.1. Key country dynamics
- 8.6.4.2. Regulatory framework
- 8.6.4.3. Competitive scenario
- 8.6.4.4. Australia market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.6.5. South Korea
- 8.6.5.1. Key country dynamics
- 8.6.5.2. Regulatory framework
- 8.6.5.3. Competitive scenario
- 8.6.5.4. South Korea market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.6.6. Thailand
- 8.6.6.1. Key country dynamics
- 8.6.6.2. Regulatory framework
- 8.6.6.3. Competitive scenario
- 8.6.6.4. Thailand market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.7. Latin America
- 8.7.1. Brazil
- 8.7.1.1. Key country dynamics
- 8.7.1.2. Regulatory framework
- 8.7.1.3. Competitive scenario
- 8.7.1.4. Brazil market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.7.2. Argentina
- 8.7.2.1. Key country dynamics
- 8.7.2.2. Regulatory framework
- 8.7.2.3. Competitive scenario
- 8.7.2.4. Argentina market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.8. MEA
- 8.8.1. South Africa
- 8.8.1.1. Key country dynamics
- 8.8.1.2. Regulatory framework
- 8.8.1.3. Competitive scenario
- 8.8.1.4. South Africa market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.8.2. Saudi Arabia
- 8.8.2.1. Key country dynamics
- 8.8.2.2. Regulatory framework
- 8.8.2.3. Competitive scenario
- 8.8.2.4. Saudi Arabia market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.8.3. UAE
- 8.8.3.1. Key country dynamics
- 8.8.3.2. Regulatory framework
- 8.8.3.3. Competitive scenario
- 8.8.3.4. UAE market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.8.4. Kuwait
- 8.8.4.1. Key country dynamics
- 8.8.4.2. Regulatory framework
- 8.8.4.3. Competitive scenario
- 8.8.4.4. Kuwait market estimates and forecasts, 2021 to 2033 (USD Million)
- Chapter 9. Competitive Landscape
- 9.1. Company/Competition Categorization
- 9.2. Strategy Mapping
- 9.3. Company Market Position Analysis, 2024
- 9.4. Company Profiles/Listing
- 9.4.1. BostonGene Corporation
- 9.4.1.1. Company overview
- 9.4.1.2. Financial performance
- 9.4.1.3. Product benchmarking
- 9.4.1.4. Strategic initiatives
- 9.4.2. Ginkgo Bioworks
- 9.4.2.1. Company overview
- 9.4.2.2. Financial performance
- 9.4.2.3. Product benchmarking
- 9.4.2.4. Strategic initiatives
- 9.4.3. IBM
- 9.4.3.1. Company overview
- 9.4.3.2. Financial performance
- 9.4.3.3. Product benchmarking
- 9.4.3.4. Strategic initiatives
- 9.4.4. TxGNN
- 9.4.4.1. Company overview
- 9.4.4.2. Financial performance
- 9.4.4.3. Product benchmarking
- 9.4.4.4. Strategic initiatives
- 9.4.5. BioXcel Therapeutics Inc.
- 9.4.5.1. Company overview
- 9.4.5.2. Financial performance
- 9.4.5.3. Product benchmarking
- 9.4.5.4. Strategic initiatives
- 9.4.6. BullFrog AI Holdings, Inc.
- 9.4.6.1. Company overview
- 9.4.6.2. Financial performance
- 9.4.6.3. Product benchmarking
- 9.4.6.4. Strategic initiatives
- 9.4.7. Ignota Labs
- 9.4.7.1. Company overview
- 9.4.7.2. Financial performance
- 9.4.7.3. Product benchmarking
- 9.4.7.4. Strategic initiatives
- 9.4.8. ISOMORPHIC LABS
- 9.4.8.1. Company overview
- 9.4.8.2. Financial performance
- 9.4.8.3. Product benchmarking
- 9.4.8.4. Strategic initiatives
- 9.4.9. Insilico Medicine
- 9.4.9.1. Company overview
- 9.4.9.2. Financial performance
- 9.4.9.3. Product benchmarking
- 9.4.9.4. Strategic initiatives
- 9.4.10. Healx
- 9.4.10.1. Company overview
- 9.4.10.2. Financial performance
- 9.4.10.3. Product benchmarking
- 9.4.10.4. Strategic initiatives
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