AI-based Drug Repurposing Market Size, Share & Trends Analysis Report by Component (Software, Hardware, Services), Deployment Mode, Technology, Drug Type, Workflow, Therapeutic Stage, Application, End User and Geography (North America, Europe, Asia Pacific, Middle East, Africa and South America) – Global Industry Data, Trends and Forecasts, 2026–2035
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Segmental Data Insights |
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Demand Trends |
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Competitive Landscape |
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Strategic Development |
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Future Outlook & Opportunities |
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AI-based Drug Repurposing Market Size, Share, and Growth
The global AI-based drug repurposing market is exhibiting strong growth, with an estimated value of USD 0.3 billion in 2025 and USD 2.2 billion by 2035, achieving a CAGR of 23.1%, during the forecast period. Asia Pacific is the fastest-growing AI-based drug repurposing market due to rising government AI healthcare investments, expanding biotech ecosystems, increasing adoption of precision medicine, and growing availability of large-scale clinical and genomic datasets enabling AI-driven drug repurposing.
"I am excited to partner with one of the top leaders in the biopharmaceutical industry with massive competence in generative AI," said Alex Zhavoronkov, Ph.D., founder, CEO and CBO of Insilico Medicine. "As we deepen the integration of generative AI into every stage of the pharma value chain, I believe the future of pharmaceutical superintelligence has the potential to deliver the highest quality and differentiated drugs. This is a fundamental step on our journey toward extension of healthy productive life."
The AI-based drug repurposing market is primarily driven by the increasing adoption of AI platforms to accelerate the identification of new therapeutic indications for existing drugs, reducing development timelines and costs. For instance, in July 2026, Insilico Medicine announced a strategic partnership with Takeda in AI drug discovery with the Pharma segment. An AI platform that identifies new therapeutics, underscoring the trend of pharmaceutical companies investing in AI-driven drug discovery.
Moreover, the growing strategic partnerships between AI technology firms and pharmaceutical firms to broaden the scope of AI supported R&D fuels the market growth. For instance, in March 2026, Insilico Medicine expanded its AI partnership with Eli Lilly through a deal worth up to US$2.75 billion, granting Lilly access to Insilico's Pharma. Next-generation AI platform to identify and develop multiple therapeutic candidates. This is speeding up drug repurposing and pharmaceutical innovation based on AI.
Adjacent market opportunities for the global AI-based drug repurposing market include AI-driven drug discovery, computational biology, bioinformatics, clinical trial optimization, and precision medicine. The increased integration of multiomics data, generative AI, and real-world evidence is enhancing cross-market innovation and fueling increased commercialization opportunities in pharmaceutical R&D. The adjacent markets are expanding the use of AI and presenting fresh revenue avenues throughout the drug development landscape.
AI-based Drug Repurposing Market Dynamics and Trends
Driver: Increasing Commercial Success of AI-Enabled Repurposed Drug Development is Strengthening Market Confidence
- Commercial validation of AI-powered drug repurposing is building confidence in AI-driven drug development. Pharma firms are finding new uses for existing drug candidates through the use of AI platforms, which also help cut development time, costs and the likelihood of commercial failure.
- The increasing regulatory acceptance of AI-driven discoveries further fuels investments in computational drug development technologies. For instance, in June 2026, Anivive LifeSciences announced that LAVERDIA-CA1 (verdinexor) has been approved by the FDA, with its AI platform identifying and prioritizing the drug for canine lymphoma. This confirms the commercial viability of AI Drug Repurposing.
- Regulatory successes are driving increased investments in AI-powered repurposing platforms, which facilitate a quicker expansion of portfolios, higher R&D productivity, and better opportunities for commercialization of existing drug assets.
- The commercialization of AI-powered repurposed treatments is driving the industry to adopt and invest in AI-driven drug development.
Restraint: Limited Translational Validation and Biological Reproducibility Continue to Constrain Market Expansion
- Biological reproducibility and limited translational validation continue to be challenges in the AI-based drug repurposing market. Although AI algorithms can quickly find promising drug candidates, computational predictions still need significant biological confirmation before moving forward into clinical trials.
- The restrictions hinder AI drug repurposing candidate validation efficiency and raise costs and timelines. For instance, in November 2025, Syngene International noted that complex biological systems, low reproducibility, scalability and the lack of clinical predictability are ongoing challenges with advanced models of translational research such as tumor organoids and organ-on-a-chips.
- The widespread commercialization of AI-driven drug repurposing platforms remains limited by validation challenges.
Opportunity: Expansion of AI-Driven Precision Medicine Platforms is Creating New Drug Repurposing Opportunities
- AI drug repurposing market is poised to witness significant growth owing to the fast-paced expansion of AI-powered precision medicine platforms. AI platforms can leverage genomic, molecular and clinical data to uncover patient-specific therapeutic opportunities and new indications for existing drugs, leading to more targeted and efficient drug development.
- For instance, in March 2026, BostonGene announced the development of an advanced AI foundation model that can model at the disease level, predict response, understand toxicity, optimize treatment based on biomarkers, and facilitate drug repurposing across disease areas. The development marks an emerging trend in AI's role in precision medicine applications.
- Precision medicine and AI are working together to help drug companies make the most of current drug assets, while enhancing drug development efficiency and optimizing treatment approaches.
- AI based drug repurposing technologies are expanding the clinical and commercial applications.
Key Trend: Growing Adoption of Graph-Based Artificial Intelligence is Transforming Drug Repurposing Workflows
- Graph-based artificial intelligence is becoming a key technology trend in the AI-based drug repurposing market. Graph AI empowers pharmaceutical firms to build a unified analysis of biological pathways, multiomics data, scientific literature, and real-world evidence that provides a stronger basis for the discovery of therapeutic targets and indications.
- Increasing emphasis on explainable and biologically interpretable AI models. For instance, in May 2026, QIAGEN signed a deal with NVIDIA to integrate graph-oriented AI into its curated bioinformatics knowledge base to help with drug discovery, biomarker identification, and drug repurposing applications.
- As the use of graph-based AI becomes more widespread, it offers significant benefits for research productivity, decision making, and the scalability and reliability of AI-driven drug repurposing platforms.
- AI-powered drug repurposing solutions are being improved by graph-based AI, which increases the accuracy, transparency, and scalability of the technology.
AI-based Drug Repurposing Market Analysis and Segmental Data
Oncology Dominate Global AI-based Drug Repurposing Market
- The oncology segment dominates the global AI-based drug repurposing market due to the growing cancer burden worldwide, abundance of genomic and clinical data, and the demand for quick identification of new therapeutic indications for existing oncology drugs. AI powered repurposing platforms allow for fast analysis of molecular pathways, biomarkers and real-world clinical data, thus shortening development times and enhancing oncology drug development efficiency.
- Increasing adoption of AI in the therapeutic development and precision medicine of oncology. For instance, in January 2026, BostonGene announced a strategic partnership with AstraZeneca to support the use of its AI-powered multimodal platform to help predict patient safety and efficacy profiles and advance oncology drug development.
- Influential investments in cancer research, the prevalent use of biomarker therapies, and ongoing advancements in AI technology further drive the dominance of oncology in the global AI-based drug repurposing market.
North America Leads Global AI-based Drug Repurposing Market Demand
- North America leads the AI-based drug repurposing market is owing to the presence of AI-driven biotechnology firms, the highly developed infrastructure and the investments made in the computational drug discovery process. AI technology developers and pharmaceutical companies in the region are working closely on drug repurposing, helping to speed the commercialization of these platforms.
- Moreover, the rising number of strategic AI partnerships formed between biotechnology companies and global giants in the pharmaceutical industry is further solidifying the regional market leadership. For instance, in June 2026, Sanofi announced the progress of its partnership to advance several AI-powered drug discovery initiatives and development achievements by integrating Recursion's AI-driven discovery platform with Sanofi's R&D expertise.
- This demonstrates North America's leadership in integrating AI into pharmaceutical innovation and expanding drug repurposing capabilities.
AI-based Drug Repurposing Market Ecosystem
The global AI-based drug repurposing market is highly consolidated, with leading companies including BenevolentAI Limited, Recursion Pharmaceuticals, Insilico Medicine, Healx Limited, and BioXcel Therapeutics maintaining strong market positions through continuous investments in artificial intelligence (AI), machine learning (ML), deep learning, knowledge graphs, and multiomics data analytics. These firms use state-of-the-art calculation systems to speed up the discovery of therapeutic targets, prioritize already existing drug candidates for new therapeutic areas, and shorten drug development timelines while simultaneously cutting the cost of the research.
Specialized AI-powered discovery platforms are a focus to speed up drug repurposing efforts for market leaders. Milan, BenevolentAI uses knowledge graphs for target identification, while Recursion Pharmaceuticals is utilizing AI-driven phenomics and Insilico Medicine is applying its Pharma. AI platform, Healx specializes in rare disease drug repurposing, and BioXcel Therapeutics applies AI to advance neuroscience and immuno-oncology drug development.
The investments are driving AI-based drug repurposing at an unprecedented rate, enhancing drug research and development efficiency, and supporting the commercialization of innovative drugs in the healthcare sector.
Recent Development and Strategic Overview:
- In March 2026, BioXcel Therapeutics submitted a supplemental New Drug Application (sNDA) seeking label expansion for IGALMI to support at-home treatment of acute agitation associated with bipolar disorder or schizophrenia, further advancing the commercialization of its AI-enabled neuroscience portfolio.
- In October 2025, BenevolentAI Limited entered into a research collaboration with Sidra Medicine to leverage AI for the investigation of the ZFP57 gene in diabetes and metabolic disease research, thereby extending the application of its knowledge graph platform into broader therapeutic areas.
Report Scope
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Detail |
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Market Size in 2025 |
USD 0.3 Bn |
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Market Forecast Value in 2035 |
USD 2.2 Bn |
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Growth Rate (CAGR) |
23.1% |
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Forecast Period |
2026 – 2035 |
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Historical Data Available for |
2021 – 2024 |
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Market Size Units |
US$ Billion for Value |
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Report Format |
Electronic (PDF) + Excel |
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North America |
Europe |
Asia Pacific |
Middle East |
Africa |
South America |
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Companies Covered |
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AI-based Drug Repurposing Market Segmentation and Highlights
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Segment |
Sub-segment |
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AI-based Drug Repurposing Market, By Component |
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AI-based Drug Repurposing Market, By Deployment Mode |
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AI-based Drug Repurposing Market, By Technology |
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AI-based Drug Repurposing Market, By Drug Type |
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AI-based Drug Repurposing Market, By Workflow |
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AI-based Drug Repurposing Market, By Therapeutic Stage |
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AI-based Drug Repurposing Market, By Application |
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AI-based Drug Repurposing Market, By End User |
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Frequently Asked Questions
Table of Contents
- 1. Research Methodology and Assumptions
- 1.1. Definitions
- 1.2. Research Design and Approach
- 1.3. Data Collection Methods
- 1.4. Base Estimates and Calculations
- 1.5. Forecasting Models
- 1.5.1. Key Forecast Factors & Impact Analysis
- 1.6. Secondary Research
- 1.6.1. Open Sources
- 1.6.2. Paid Databases
- 1.6.3. Associations
- 1.7. Primary Research
- 1.7.1. Primary Sources
- 1.7.2. Primary Interviews with Stakeholders across Ecosystem
- 2. Executive Summary
- 2.1. Global AI-based Drug Repurposing Market Outlook
- 2.1.1. AI-based Drug Repurposing Market Size (Value - US$ Bn), and Forecasts, 2021-2035
- 2.1.2. Compounded Annual Growth Rate Analysis
- 2.1.3. Growth Opportunity Analysis
- 2.1.4. Segmental Share Analysis
- 2.1.5. Geographical Share Analysis
- 2.2. Market Analysis and Facts
- 2.3. Supply-Demand Analysis
- 2.4. Competitive Benchmarking
- 2.5. Go-to- Market Strategy
- 2.5.1. Customer/ End-use Industry Assessment
- 2.5.2. Growth Opportunity Data, 2026-2035
- 2.5.2.1. Regional Data
- 2.5.2.2. Country Data
- 2.5.2.3. Segmental Data
- 2.5.3. Identification of Potential Market Spaces
- 2.5.4. GAP Analysis
- 2.5.5. Potential Attractive Price Points
- 2.5.6. Prevailing Market Risks & Challenges
- 2.5.7. Preferred Sales & Marketing Strategies
- 2.5.8. Key Recommendations and Analysis
- 2.5.9. A Way Forward
- 2.1. Global AI-based Drug Repurposing Market Outlook
- 3. Industry Data and Premium Insights
- 3.1. Global Healthcare & Pharmaceutical Industry Overview, 2025
- 3.1.1. Healthcare & Pharmaceutical Ecosystem Analysis
- 3.1.2. Key Trends for Healthcare & Pharmaceutical Industry
- 3.1.3. Regional Distribution for Healthcare & Pharmaceutical Industry
- 3.2. Supplier Customer Data
- 3.3. Technology Roadmap and Developments
- 3.4. Trump Tariff Impact Analysis
- 3.1. Global Healthcare & Pharmaceutical Industry Overview, 2025
- 4. Market Overview
- 4.1. Market Dynamics
- 4.1.1. Drivers
- 4.1.1.1. Increasing adoption of AI-powered drug discovery and computational biology platforms
- 4.1.1.2. Growing availability of genomic, multiomics, and real-world healthcare datasets
- 4.1.1.3. Expansion of AI-powered precision medicine and biomarker-driven drug repurposing
- 4.1.2. Restraints
- 4.1.2.1. Intellectual property and limited market exclusivity for repurposed drugs
- 4.1.2.2. Limited availability of standardized, high-quality biomedical data for AI model training
- 4.1.1. Drivers
- 4.2. Key Trend Analysis
- 4.3. Regulatory Framework
- 4.3.1. Key Regulations, Norms, and Subsidies, by Key Countries
- 4.3.2. Tariffs and Standards
- 4.3.3. Impact Analysis of Regulations on the Market
- 4.4. Eco-system Analysis
- 4.5. Porter’s Five Forces Analysis
- 4.6. PESTEL Analysis
- 4.7. Global AI-based Drug Repurposing Market Demand
- 4.7.1. Historical Market Size – in Value (US$ Bn), 2020-2024
- 4.7.2. Current and Future Market Size – in Value (US$ Bn), 2026–2035
- 4.7.2.1. Y-o-Y Growth Trends
- 4.7.2.2. Absolute $ Opportunity Assessment
- 4.1. Market Dynamics
- 5. Competition Landscape
- 5.1. Competition structure
- 5.1.1. Fragmented v/s consolidated
- 5.2. Company Share Analysis, 2025
- 5.2.1. Global Company Market Share
- 5.2.2. By Region
- 5.2.2.1. North America
- 5.2.2.2. Europe
- 5.2.2.3. Asia Pacific
- 5.2.2.4. Middle East
- 5.2.2.5. Africa
- 5.2.2.6. South America
- 5.3. Product Comparison Matrix
- 5.3.1. Specifications
- 5.3.2. Market Positioning
- 5.3.3. Pricing
- 5.1. Competition structure
- 6. Global AI-based Drug Repurposing Market Analysis, by Component
- 6.1. Key Segment Analysis
- 6.2. AI-based Drug Repurposing Market Size (Value - US$ Bn), Analysis, and Forecasts, by Component, 2021-2035
- 6.2.1. Software
- 6.2.1.1. AI Drug Discovery Platforms
- 6.2.1.2. Drug Repurposing Software
- 6.2.1.3. Predictive Analytics Software
- 6.2.1.4. Molecular Modeling & Simulation Software
- 6.2.1.5. Bioinformatics Software
- 6.2.1.6. Clinical Data Analytics Software
- 6.2.1.7. Workflow Management Software
- 6.2.1.8. Cloud-Based Drug Discovery Platforms
- 6.2.1.9. Others
- 6.2.2. Hardware
- 6.2.2.1. High-Performance Computing (HPC) Systems
- 6.2.2.2. AI Servers & Workstations
- 6.2.2.3. GPU Computing Infrastructure
- 6.2.2.4. Data Storage Systems
- 6.2.2.5. Networking & Connectivity Equipment
- 6.2.2.6. Security Infrastructure
- 6.2.2.7. Others
- 6.2.3. Services
- 6.2.3.1. Consulting Services
- 6.2.3.2. System Integration & Deployment Services
- 6.2.3.3. AI Model Development & Customization
- 6.2.3.4. Bioinformatics & Data Analysis Services
- 6.2.3.5. Cloud & Managed Services
- 6.2.3.6. Technical Support & Maintenance
- 6.2.3.7. Training & Education Services
- 6.2.3.8. Regulatory & Compliance Services
- 6.2.3.9. Others
- 6.2.1. Software
- 7. Global AI-based Drug Repurposing Market Analysis, by Deployment Mode
- 7.1. Key Segment Analysis
- 7.2. AI-based Drug Repurposing Market Size (Value - US$ Bn), Analysis, and Forecasts, by Deployment Mode, 2021-2035
- 7.2.1. Cloud-Based
- 7.2.2. On-Premises
- 7.2.3. Hybrid
- 8. Global AI-based Drug Repurposing Market Analysis, by Technology
- 8.1. Key Segment Analysis
- 8.2. AI-based Drug Repurposing Market Size (Value - US$ Bn), Analysis, and Forecasts, by Technology, 2021-2035
- 8.2.1. Machine Learning (ML)
- 8.2.2. Deep Learning
- 8.2.3. Natural Language Processing (NLP)
- 8.2.4. Generative AI
- 8.2.5. Knowledge Graph-Based AI
- 8.2.6. Predictive Analytics
- 8.2.7. Computer Vision
- 8.2.8. Reinforcement Learning
- 8.2.9. Others
- 9. Global AI-based Drug Repurposing Market Analysis, by Drug Type
- 9.1. Key Segment Analysis
- 9.2. AI-based Drug Repurposing Market Size (Value - US$ Bn), Analysis, and Forecasts, by Drug Type, 2021-2035
- 9.2.1. Small Molecules
- 9.2.2. Biologics
- 9.2.3. Biosimilars
- 9.2.4. Peptides
- 9.2.5. Vaccines
- 9.2.6. Cell & Gene Therapy Candidates
- 9.2.7. RNA-Based Therapeutics
- 9.2.8. Combination Therapies
- 9.2.9. Others
- 10. Global AI-based Drug Repurposing Market Analysis, by Workflow
- 10.1. Key Segment Analysis
- 10.2. AI-based Drug Repurposing Market Size (Value - US$ Bn), Analysis, and Forecasts, by Workflow, 2021-2035
- 10.2.1. Target Identification
- 10.2.2. Drug Candidate Screening
- 10.2.3. Drug Repurposing Prediction
- 10.2.4. Molecular Modeling & Simulation
- 10.2.5. Biomarker Discovery
- 10.2.6. Clinical Trial Optimization
- 10.2.7. Safety & Toxicity Assessment
- 10.2.8. Regulatory Data Analysis
- 10.2.9. Others
- 11. Global AI-based Drug Repurposing Market Analysis, by Therapeutic Stage
- 11.1. Key Segment Analysis
- 11.2. AI-based Drug Repurposing Market Size (Value - US$ Bn), Analysis, and Forecasts, by Therapeutic Stage Technology, 2021-2035
- 11.2.1. Preclinical Research
- 11.2.2. Phase I Clinical Trials
- 11.2.3. Phase II Clinical Trials
- 11.2.4. Phase III Clinical Trials
- 11.2.5. Post-Marketing Studies
- 12. Global AI-based Drug Repurposing Market Analysis, by Application
- 12.1. Key Segment Analysis
- 12.2. AI-based Drug Repurposing Market Size (Value - US$ Bn), Analysis, and Forecasts, by Application, 2021-2035
- 12.2.1. Oncology
- 12.2.2. Neurology
- 12.2.3. Infectious Diseases
- 12.2.4. Rare Diseases
- 12.2.5. Cardiovascular Diseases
- 12.2.6. Metabolic Disorders
- 12.2.7. Immunology & Autoimmune Diseases
- 12.2.8. Respiratory Diseases
- 12.2.9. Gastrointestinal Diseases
- 12.2.10. Dermatology
- 12.2.11. Others
- 13. Global AI-based Drug Repurposing Market Analysis, by End User
- 13.1. Key Segment Analysis
- 13.2. AI-based Drug Repurposing Market Size (Value - US$ Bn), Analysis, and Forecasts, by End User, 2021-2035
- 13.2.1. Pharmaceutical Companies
- 13.2.2. Biotechnology Companies
- 13.2.3. Contract Research Organizations (CROs)
- 13.2.4. Academic & Research Institutes
- 13.2.5. Hospitals
- 13.2.6. Government Research Organizations
- 13.2.7. Clinical Research Organizations
- 13.2.8. Drug Discovery Startups
- 13.2.9. Others
- 14. Global AI-based Drug Repurposing Market Analysis, by Region
- 14.1. Key Findings
- 14.2. AI-based Drug Repurposing Market Size (Value - US$ Bn), Analysis, and Forecasts, by Region, 2021-2035
- 14.2.1. North America
- 14.2.2. Europe
- 14.2.3. Asia Pacific
- 14.2.4. Middle East
- 14.2.5. Africa
- 14.2.6. South America
- 15. North America AI-based Drug Repurposing Market Analysis
- 15.1. Key Segment Analysis
- 15.2. Regional Snapshot
- 15.3. North America AI-based Drug Repurposing Market Size (Value - US$ Bn), Analysis, and Forecasts, 2021-2035
- 15.3.1. Component
- 15.3.2. Deployment Mode
- 15.3.3. Technology
- 15.3.4. Drug Type
- 15.3.5. Workflow
- 15.3.6. Therapeutic Stage
- 15.3.7. Application
- 15.3.8. End User
- 15.3.9. Country
- 15.3.9.1. USA
- 15.3.9.2. Canada
- 15.3.9.3. Mexico
- 15.4. USA AI-based Drug Repurposing Market
- 15.4.1. Country Segmental Analysis
- 15.4.2. Component
- 15.4.3. Deployment Mode
- 15.4.4. Technology
- 15.4.5. Drug Type
- 15.4.6. Workflow
- 15.4.7. Therapeutic Stage
- 15.4.8. Application
- 15.4.9. End User
- 15.5. Canada AI-based Drug Repurposing Market
- 15.5.1. Country Segmental Analysis
- 15.5.2. Component
- 15.5.3. Deployment Mode
- 15.5.4. Technology
- 15.5.5. Drug Type
- 15.5.6. Workflow
- 15.5.7. Therapeutic Stage
- 15.5.8. Application
- 15.5.9. End User
- 15.6. Mexico AI-based Drug Repurposing Market
- 15.6.1. Country Segmental Analysis
- 15.6.2. Component
- 15.6.3. Deployment Mode
- 15.6.4. Technology
- 15.6.5. Drug Type
- 15.6.6. Workflow
- 15.6.7. Therapeutic Stage
- 15.6.8. Application
- 15.6.9. End User
- 16. Europe AI-based Drug Repurposing Market Analysis
- 16.1. Key Segment Analysis
- 16.2. Regional Snapshot
- 16.3. Europe AI-based Drug Repurposing Market Size (Value - US$ Bn), Analysis, and Forecasts, 2021-2035
- 16.3.1. Component
- 16.3.2. Deployment Mode
- 16.3.3. Technology
- 16.3.4. Drug Type
- 16.3.5. Workflow
- 16.3.6. Therapeutic Stage
- 16.3.7. Application
- 16.3.8. End User
- 16.3.9. Country
- 16.3.9.1. Germany
- 16.3.9.2. United Kingdom
- 16.3.9.3. France
- 16.3.9.4. Italy
- 16.3.9.5. Spain
- 16.3.9.6. Netherlands
- 16.3.9.7. Nordic Countries
- 16.3.9.8. Poland
- 16.3.9.9. Russia & CIS
- 16.3.9.10. Rest of Europe
- 16.4. Germany AI-based Drug Repurposing Market
- 16.4.1. Country Segmental Analysis
- 16.4.2. Component
- 16.4.3. Deployment Mode
- 16.4.4. Technology
- 16.4.5. Drug Type
- 16.4.6. Workflow
- 16.4.7. Therapeutic Stage
- 16.4.8. Application
- 16.4.9. End User
- 16.5. United Kingdom AI-based Drug Repurposing Market
- 16.5.1. Country Segmental Analysis
- 16.5.2. Component
- 16.5.3. Deployment Mode
- 16.5.4. Technology
- 16.5.5. Drug Type
- 16.5.6. Workflow
- 16.5.7. Therapeutic Stage
- 16.5.8. Application
- 16.5.9. End User
- 16.6. France AI-based Drug Repurposing Market
- 16.6.1. Country Segmental Analysis
- 16.6.2. Component
- 16.6.3. Deployment Mode
- 16.6.4. Technology
- 16.6.5. Drug Type
- 16.6.6. Workflow
- 16.6.7. Therapeutic Stage
- 16.6.8. Application
- 16.6.9. End User
- 16.7. Italy AI-based Drug Repurposing Market
- 16.7.1. Country Segmental Analysis
- 16.7.2. Component
- 16.7.3. Deployment Mode
- 16.7.4. Technology
- 16.7.5. Drug Type
- 16.7.6. Workflow
- 16.7.7. Therapeutic Stage
- 16.7.8. Application
- 16.7.9. End User
- 16.8. Spain AI-based Drug Repurposing Market
- 16.8.1. Country Segmental Analysis
- 16.8.2. Component
- 16.8.3. Deployment Mode
- 16.8.4. Technology
- 16.8.5. Drug Type
- 16.8.6. Workflow
- 16.8.7. Therapeutic Stage
- 16.8.8. Application
- 16.8.9. End User
- 16.9. Netherlands AI-based Drug Repurposing Market
- 16.9.1. Country Segmental Analysis
- 16.9.2. Component
- 16.9.3. Deployment Mode
- 16.9.4. Technology
- 16.9.5. Drug Type
- 16.9.6. Workflow
- 16.9.7. Therapeutic Stage
- 16.9.8. Application
- 16.9.9. End User
- 16.10. Nordic Countries AI-based Drug Repurposing Market
- 16.10.1. Country Segmental Analysis
- 16.10.2. Component
- 16.10.3. Deployment Mode
- 16.10.4. Technology
- 16.10.5. Drug Type
- 16.10.6. Workflow
- 16.10.7. Therapeutic Stage
- 16.10.8. Application
- 16.10.9. End User
- 16.11. Poland AI-based Drug Repurposing Market
- 16.11.1. Country Segmental Analysis
- 16.11.2. Component
- 16.11.3. Deployment Mode
- 16.11.4. Technology
- 16.11.5. Drug Type
- 16.11.6. Workflow
- 16.11.7. Therapeutic Stage
- 16.11.8. Application
- 16.11.9. End User
- 16.12. Russia & CIS AI-based Drug Repurposing Market
- 16.12.1. Country Segmental Analysis
- 16.12.2. Component
- 16.12.3. Deployment Mode
- 16.12.4. Technology
- 16.12.5. Drug Type
- 16.12.6. Workflow
- 16.12.7. Therapeutic Stage
- 16.12.8. Application
- 16.12.9. End User
- 16.13. Rest of Europe AI-based Drug Repurposing Market
- 16.13.1. Component
- 16.13.2. Deployment Mode
- 16.13.3. Technology
- 16.13.4. Drug Type
- 16.13.5. Workflow
- 16.13.6. Therapeutic Stage
- 16.13.7. Application
- 16.13.8. End User
- 17. Asia Pacific AI-based Drug Repurposing Market Analysis
- 17.1. Key Segment Analysis
- 17.2. Regional Snapshot
- 17.3. Asia Pacific AI-based Drug Repurposing Market Size (Value - US$ Bn), Analysis, and Forecasts, 2021-2035
- 17.3.1. Component
- 17.3.2. Deployment Mode
- 17.3.3. Technology
- 17.3.4. Drug Type
- 17.3.5. Workflow
- 17.3.6. Therapeutic Stage
- 17.3.7. Application
- 17.3.8. End User
- 17.3.9. Country
- 17.3.9.1. China
- 17.3.9.2. India
- 17.3.9.3. Japan
- 17.3.9.4. South Korea
- 17.3.9.5. Australia and New Zealand
- 17.3.9.6. Indonesia
- 17.3.9.7. Malaysia
- 17.3.9.8. Thailand
- 17.3.9.9. Vietnam
- 17.3.9.10. Rest of Asia Pacific
- 17.4. China AI-based Drug Repurposing Market
- 17.4.1. Country Segmental Analysis
- 17.4.2. Component
- 17.4.3. Deployment Mode
- 17.4.4. Technology
- 17.4.5. Drug Type
- 17.4.6. Workflow
- 17.4.7. Therapeutic Stage
- 17.4.8. Application
- 17.4.9. End User
- 17.5. India AI-based Drug Repurposing Market
- 17.5.1. Country Segmental Analysis
- 17.5.2. Component
- 17.5.3. Deployment Mode
- 17.5.4. Technology
- 17.5.5. Drug Type
- 17.5.6. Workflow
- 17.5.7. Therapeutic Stage
- 17.5.8. Application
- 17.5.9. End User
- 17.6. Japan AI-based Drug Repurposing Market
- 17.6.1. Country Segmental Analysis
- 17.6.2. Component
- 17.6.3. Deployment Mode
- 17.6.4. Technology
- 17.6.5. Drug Type
- 17.6.6. Workflow
- 17.6.7. Therapeutic Stage
- 17.6.8. Application
- 17.6.9. End User
- 17.7. South Korea AI-based Drug Repurposing Market
- 17.7.1. Country Segmental Analysis
- 17.7.2. Component
- 17.7.3. Deployment Mode
- 17.7.4. Technology
- 17.7.5. Drug Type
- 17.7.6. Workflow
- 17.7.7. Therapeutic Stage
- 17.7.8. Application
- 17.7.9. End User
- 17.8. Australia and New Zealand AI-based Drug Repurposing Market
- 17.8.1. Country Segmental Analysis
- 17.8.2. Component
- 17.8.3. Deployment Mode
- 17.8.4. Technology
- 17.8.5. Drug Type
- 17.8.6. Workflow
- 17.8.7. Therapeutic Stage
- 17.8.8. Application
- 17.8.9. End User
- 17.9. Indonesia AI-based Drug Repurposing Market
- 17.9.1. Country Segmental Analysis
- 17.9.2. Component
- 17.9.3. Deployment Mode
- 17.9.4. Technology
- 17.9.5. Drug Type
- 17.9.6. Workflow
- 17.9.7. Therapeutic Stage
- 17.9.8. Application
- 17.9.9. End User
- 17.10. Malaysia AI-based Drug Repurposing Market
- 17.10.1. Country Segmental Analysis
- 17.10.2. Component
- 17.10.3. Deployment Mode
- 17.10.4. Technology
- 17.10.5. Drug Type
- 17.10.6. Workflow
- 17.10.7. Therapeutic Stage
- 17.10.8. Application
- 17.10.9. End User
- 17.11. Thailand AI-based Drug Repurposing Market
- 17.11.1. Country Segmental Analysis
- 17.11.2. Component
- 17.11.3. Deployment Mode
- 17.11.4. Technology
- 17.11.5. Drug Type
- 17.11.6. Workflow
- 17.11.7. Therapeutic Stage
- 17.11.8. Application
- 17.11.9. End User
- 17.12. Vietnam AI-based Drug Repurposing Market
- 17.12.1. Country Segmental Analysis
- 17.12.2. Component
- 17.12.3. Deployment Mode
- 17.12.4. Technology
- 17.12.5. Drug Type
- 17.12.6. Workflow
- 17.12.7. Therapeutic Stage
- 17.12.8. Application
- 17.12.9. End User
- 17.13. Rest of Asia Pacific AI-based Drug Repurposing Market
- 17.13.1. Country Segmental Analysis
- 17.13.2. Component
- 17.13.3. Deployment Mode
- 17.13.4. Technology
- 17.13.5. Drug Type
- 17.13.6. Workflow
- 17.13.7. Therapeutic Stage
- 17.13.8. Application
- 17.13.9. End User
- 18. Middle East AI-based Drug Repurposing Market Analysis
- 18.1. Key Segment Analysis
- 18.2. Regional Snapshot
- 18.3. Middle East AI-based Drug Repurposing Market Size (Value - US$ Bn), Analysis, and Forecasts, 2021-2035
- 18.3.1. Component
- 18.3.2. Deployment Mode
- 18.3.3. Technology
- 18.3.4. Drug Type
- 18.3.5. Workflow
- 18.3.6. Therapeutic Stage
- 18.3.7. Application
- 18.3.8. End User
- 18.3.9. Country
- 18.3.9.1. Turkey
- 18.3.9.2. UAE
- 18.3.9.3. Saudi Arabia
- 18.3.9.4. Israel
- 18.3.9.5. Rest of Middle East
- 18.4. Turkey AI-based Drug Repurposing Market
- 18.4.1. Country Segmental Analysis
- 18.4.2. Component
- 18.4.3. Deployment Mode
- 18.4.4. Technology
- 18.4.5. Drug Type
- 18.4.6. Workflow
- 18.4.7. Therapeutic Stage
- 18.4.8. Application
- 18.4.9. End User
- 18.5. UAE AI-based Drug Repurposing Market
- 18.5.1. Country Segmental Analysis
- 18.5.2. Component
- 18.5.3. Deployment Mode
- 18.5.4. Technology
- 18.5.5. Drug Type
- 18.5.6. Workflow
- 18.5.7. Therapeutic Stage
- 18.5.8. Application
- 18.5.9. End User
- 18.6. Saudi Arabia AI-based Drug Repurposing Market
- 18.6.1. Country Segmental Analysis
- 18.6.2. Component
- 18.6.3. Deployment Mode
- 18.6.4. Technology
- 18.6.5. Drug Type
- 18.6.6. Workflow
- 18.6.7. Therapeutic Stage
- 18.6.8. Application
- 18.6.9. End User
- 18.7. Israel AI-based Drug Repurposing Market
- 18.7.1. Country Segmental Analysis
- 18.7.2. Component
- 18.7.3. Deployment Mode
- 18.7.4. Technology
- 18.7.5. Drug Type
- 18.7.6. Workflow
- 18.7.7. Therapeutic Stage
- 18.7.8. Application
- 18.7.9. End User
- 18.8. Rest of Middle East AI-based Drug Repurposing Market
- 18.8.1. Country Segmental Analysis
- 18.8.2. Component
- 18.8.3. Deployment Mode
- 18.8.4. Technology
- 18.8.5. Drug Type
- 18.8.6. Workflow
- 18.8.7. Therapeutic Stage
- 18.8.8. Application
- 18.8.9. End User
- 19. Africa AI-based Drug Repurposing Market Analysis
- 19.1. Key Segment Analysis
- 19.2. Regional Snapshot
- 19.3. Africa AI-based Drug Repurposing Market Size (Value - US$ Bn), Analysis, and Forecasts, 2021-2035
- 19.3.1. Component
- 19.3.2. Deployment Mode
- 19.3.3. Technology
- 19.3.4. Drug Type
- 19.3.5. Workflow
- 19.3.6. Therapeutic Stage
- 19.3.7. Application
- 19.3.8. End User
- 19.3.9. Country
- 19.3.9.1. South Africa
- 19.3.9.2. Egypt
- 19.3.9.3. Nigeria
- 19.3.9.4. Algeria
- 19.3.9.5. Rest of Africa
- 19.4. South Africa AI-based Drug Repurposing Market
- 19.4.1. Country Segmental Analysis
- 19.4.2. Component
- 19.4.3. Deployment Mode
- 19.4.4. Technology
- 19.4.5. Drug Type
- 19.4.6. Workflow
- 19.4.7. Therapeutic Stage
- 19.4.8. Application
- 19.4.9. End User
- 19.5. Egypt AI-based Drug Repurposing Market
- 19.5.1. Country Segmental Analysis
- 19.5.2. Component
- 19.5.3. Deployment Mode
- 19.5.4. Technology
- 19.5.5. Drug Type
- 19.5.6. Workflow
- 19.5.7. Therapeutic Stage
- 19.5.8. Application
- 19.5.9. End User
- 19.6. Nigeria AI-based Drug Repurposing Market
- 19.6.1. Country Segmental Analysis
- 19.6.2. Component
- 19.6.3. Deployment Mode
- 19.6.4. Technology
- 19.6.5. Drug Type
- 19.6.6. Workflow
- 19.6.7. Therapeutic Stage
- 19.6.8. Application
- 19.6.9. End User
- 19.7. Algeria AI-based Drug Repurposing Market
- 19.7.1. Country Segmental Analysis
- 19.7.2. Component
- 19.7.3. Deployment Mode
- 19.7.4. Technology
- 19.7.5. Drug Type
- 19.7.6. Workflow
- 19.7.7. Therapeutic Stage
- 19.7.8. Application
- 19.7.9. End User
- 19.8. Rest of Africa AI-based Drug Repurposing Market
- 19.8.1. Country Segmental Analysis
- 19.8.2. Component
- 19.8.3. Deployment Mode
- 19.8.4. Technology
- 19.8.5. Drug Type
- 19.8.6. Workflow
- 19.8.7. Therapeutic Stage
- 19.8.8. Application
- 19.8.9. End User
- 20. South America AI-based Drug Repurposing Market Analysis
- 20.1. Key Segment Analysis
- 20.2. Regional Snapshot
- 20.3. South America AI-based Drug Repurposing Market Size (Value - US$ Bn), Analysis, and Forecasts, 2021-2035
- 20.3.1. Component
- 20.3.2. Deployment Mode
- 20.3.3. Technology
- 20.3.4. Drug Type
- 20.3.5. Workflow
- 20.3.6. Therapeutic Stage
- 20.3.7. Application
- 20.3.8. End User
- 20.3.9. Country
- 20.3.9.1. Brazil
- 20.3.9.2. Argentina
- 20.3.9.3. Rest of South America
- 20.4. Brazil AI-based Drug Repurposing Market
- 20.4.1. Country Segmental Analysis
- 20.4.2. Component
- 20.4.3. Deployment Mode
- 20.4.4. Technology
- 20.4.5. Drug Type
- 20.4.6. Workflow
- 20.4.7. Therapeutic Stage
- 20.4.8. Application
- 20.4.9. End User
- 20.5. Argentina AI-based Drug Repurposing Market
- 20.5.1. Country Segmental Analysis
- 20.5.2. Component
- 20.5.3. Deployment Mode
- 20.5.4. Technology
- 20.5.5. Drug Type
- 20.5.6. Workflow
- 20.5.7. Therapeutic Stage
- 20.5.8. Application
- 20.5.9. End User
- 20.6. Rest of South America AI-based Drug Repurposing Market
- 20.6.1. Country Segmental Analysis
- 20.6.2. Component
- 20.6.3. Deployment Mode
- 20.6.4. Technology
- 20.6.5. Drug Type
- 20.6.6. Workflow
- 20.6.7. Therapeutic Stage
- 20.6.8. Application
- 20.6.9. End User
- 21. Key Players/ Company Profile
- 21.1. BenevolentAI Limited
- 21.1.1. Company Details/ Overview
- 21.1.2. Company Financials
- 21.1.3. Key Customers and Competitors
- 21.1.4. Business/ Industry Portfolio
- 21.1.5. Product Portfolio/ Specification Details
- 21.1.6. Pricing Data
- 21.1.7. Strategic Overview
- 21.1.8. Recent Developments
- 21.2. BioXcel Therapeutics Inc
- 21.3. BullFrog AI Holdings, Inc.
- 21.4. Healx Limited
- 21.5. Insilico Medicine, Inc.
- 21.6. Lantern Pharma Inc.
- 21.7. Recursion Pharmaceuticals, Inc.
- 21.8. Other Key Players
- 21.1. BenevolentAI Limited
Note* - This is just tentative list of players. While providing the report, we will cover more number of players based on their revenue and share for each geography
Research Design
Our research design integrates both demand-side and supply-side analysis through a balanced combination of primary and secondary research methodologies. By utilizing both bottom-up and top-down approaches alongside rigorous data triangulation methods, we deliver robust market intelligence that supports strategic decision-making.
MarketGenics' comprehensive research design framework ensures the delivery of accurate, reliable, and actionable market intelligence. Through the integration of multiple research approaches, rigorous validation processes, and expert analysis, we provide our clients with the insights needed to make informed strategic decisions and capitalize on market opportunities.
MarketGenics leverages a dedicated industry panel of experts and a comprehensive suite of paid databases to effectively collect, consolidate, and analyze market intelligence.
Our approach has consistently proven to be reliable and effective in generating accurate market insights, identifying key industry trends, and uncovering emerging business opportunities.
Through both primary and secondary research, we capture and analyze critical company-level data such as manufacturing footprints, including technical centers, R&D facilities, sales offices, and headquarters.
Our expert panel further enhances our ability to estimate market size for specific brands based on validated field-level intelligence.
Our data mining techniques incorporate both parametric and non-parametric methods, allowing for structured data collection, sorting, processing, and cleaning.
Demand projections are derived from large-scale data sets analyzed through proprietary algorithms, culminating in robust and reliable market sizing.
Research Approach
The bottom-up approach builds market estimates by starting with the smallest addressable market units and systematically aggregating them to create comprehensive market size projections.
This method begins with specific, granular data points and builds upward to create the complete market landscape.
Customer Analysis → Segmental Analysis → Geographical Analysis
The top-down approach starts with the broadest possible market data and systematically narrows it down through a series of filters and assumptions to arrive at specific market segments or opportunities.
This method begins with the big picture and works downward to increasingly specific market slices.
TAM → SAM → SOM
Research Methods
Desk / Secondary Research
While analysing the market, we extensively study secondary sources, directories, and databases to identify and collect information useful for this technical, market-oriented, and commercial report. Secondary sources that we utilize are not only the public sources, but it is a combination of Open Source, Associations, Paid Databases, MG Repository & Knowledgebase, and others.
- Company websites, annual reports, financial reports, broker reports, and investor presentations
- National government documents, statistical databases and reports
- News articles, press releases and web-casts specific to the companies operating in the market, Magazines, reports, and others
- We gather information from commercial data sources for deriving company specific data such as segmental revenue, share for geography, product revenue, and others
- Internal and external proprietary databases (industry-specific), relevant patent, and regulatory databases
- Governing Bodies, Government Organizations
- Relevant Authorities, Country-specific Associations for Industries
We also employ the model mapping approach to estimate the product level market data through the players' product portfolio
Primary Research
Primary research/ interviews is vital in analyzing the market. Most of the cases involves paid primary interviews. Primary sources include primary interviews through e-mail interactions, telephonic interviews, surveys as well as face-to-face interviews with the different stakeholders across the value chain including several industry experts.
| Type of Respondents | Number of Primaries |
|---|---|
| Tier 2/3 Suppliers | ~20 |
| Tier 1 Suppliers | ~25 |
| End-users | ~25 |
| Industry Expert/ Panel/ Consultant | ~30 |
| Total | ~100 |
MG Knowledgebase
• Repository of industry blog, newsletter and case studies
• Online platform covering detailed market reports, and company profiles
Forecasting Factors and Models
Forecasting Factors
- Historical Trends – Past market patterns, cycles, and major events that shaped how markets behave over time. Understanding past trends helps predict future behavior.
- Industry Factors – Specific characteristics of the industry like structure, regulations, and innovation cycles that affect market dynamics.
- Macroeconomic Factors – Economic conditions like GDP growth, inflation, and employment rates that affect how much money people have to spend.
- Demographic Factors – Population characteristics like age, income, and location that determine who can buy your product.
- Technology Factors – How quickly people adopt new technology and how much technology infrastructure exists.
- Regulatory Factors – Government rules, laws, and policies that can help or restrict market growth.
- Competitive Factors – Analyzing competition structure such as degree of competition and bargaining power of buyers and suppliers.
Forecasting Models / Techniques
Multiple Regression Analysis
- Identify and quantify factors that drive market changes
- Statistical modeling to establish relationships between market drivers and outcomes
Time Series Analysis – Seasonal Patterns
- Understand regular cyclical patterns in market demand
- Advanced statistical techniques to separate trend, seasonal, and irregular components
Time Series Analysis – Trend Analysis
- Identify underlying market growth patterns and momentum
- Statistical analysis of historical data to project future trends
Expert Opinion – Expert Interviews
- Gather deep industry insights and contextual understanding
- In-depth interviews with key industry stakeholders
Multi-Scenario Development
- Prepare for uncertainty by modeling different possible futures
- Creating optimistic, pessimistic, and most likely scenarios
Time Series Analysis – Moving Averages
- Sophisticated forecasting for complex time series data
- Auto-regressive integrated moving average models with seasonal components
Econometric Models
- Apply economic theory to market forecasting
- Sophisticated economic models that account for market interactions
Expert Opinion – Delphi Method
- Harness collective wisdom of industry experts
- Structured, multi-round expert consultation process
Monte Carlo Simulation
- Quantify uncertainty and probability distributions
- Thousands of simulations with varying input parameters
Research Analysis
Our research framework is built upon the fundamental principle of validating market intelligence from both demand and supply perspectives. This dual-sided approach ensures comprehensive market understanding and reduces the risk of single-source bias.
Demand-Side Analysis: We understand end-user/application behavior, preferences, and market needs along with the penetration of the product for specific application.
Supply-Side Analysis: We estimate overall market revenue, analyze the segmental share along with industry capacity, competitive landscape, and market structure.
Validation & Evaluation
Data triangulation is a validation technique that uses multiple methods, sources, or perspectives to examine the same research question, thereby increasing the credibility and reliability of research findings. In market research, triangulation serves as a quality assurance mechanism that helps identify and minimize bias, validate assumptions, and ensure accuracy in market estimates.
- Data Source Triangulation – Using multiple data sources to examine the same phenomenon
- Methodological Triangulation – Using multiple research methods to study the same research question
- Investigator Triangulation – Using multiple researchers or analysts to examine the same data
- Theoretical Triangulation – Using multiple theoretical perspectives to interpret the same data
Custom Market Research Services
We will customise the research for you, in case the report listed above does not meet your requirements.
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