The global artificial intelligence (AI) in drug repurposing market was valued at USD 1.3 billion in 2025 and is estimated to reach USD 1.7 billion in 2026. The market is projected to expand to USD 7.7 billion by 2033, registering a 24.5% CAGR from 2026 to 2033.

North America accounted for the largest revenue share at 52.9% in 2025, supported by a strong ecosystem of AI companies, pharmaceutical and biotechnology firms, advanced research institutions, and technology infrastructure. Meanwhile, Asia Pacific is expected to record the fastest CAGR during 2026–2033.

AI is increasingly being applied to drug repurposing because it can analyze large volumes of biological, chemical, clinical, genomic, and real-world datasets to identify potential new uses for existing or investigational drugs. This approach can reduce the time, cost, and uncertainty associated with traditional drug discovery.

What Is Driving Market Expansion?

Several factors are accelerating adoption of AI-powered drug repurposing platforms:

• Lower drug development costs: Repurposing existing or investigational compounds can reduce the need for some early-stage discovery and safety-development activities.
• Shorter development timelines: AI can rapidly screen large datasets and identify potential drug-disease associations, helping researchers prioritize promising candidates.
• Growing clinical activity: Increasing clinical trials focused on new indications for existing drugs are expanding demand for computational repurposing solutions.
• Rising prevalence of complex and rare diseases: Limited treatment options are encouraging researchers to identify alternative therapeutic applications for known compounds.
• Expansion of precision medicine: AI enables researchers to identify relationships between molecular characteristics, disease biology, patient populations, and drug responses.
• Advances in cloud computing: Greater computational capacity and scalable cloud infrastructure are supporting sophisticated machine learning and data-analysis workflows.

Traditional drug discovery can take more than a decade and may require investments exceeding USD 2 billion per successful drug. AI-enabled repurposing provides an alternative by analyzing established or investigational compounds for new therapeutic indications. Machine learning can process extensive biomedical datasets at scale, helping researchers identify relationships that may be difficult to detect using conventional approaches.

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Market Structure and Key Trends

The market demonstrates strong adoption across software, technology, therapeutic applications, and end-user categories.

Segment-Level Insights

Software & platforms represented the largest component category in 2025, reflecting growing demand for computational platforms capable of integrating and interpreting complex biomedical information.

Machine learning and deep learning accounted for the largest technology share at 45.8%. These techniques are particularly valuable for identifying patterns across electronic health records (EHRs), genomic datasets, clinical information, scientific publications, and real-world evidence.

Oncology led the application landscape with a 36.7% revenue share. Cancer research generates extensive clinical and molecular datasets, while the need for targeted and precision therapies creates significant opportunities for identifying alternative drug indications.

By end use, pharmaceutical and biotechnology companies dominated with a 59.2% share. These organizations are increasingly using AI to supplement internal discovery programs, prioritize drug candidates, identify new indications, and improve R&D productivity.

Small-molecule drugs also represent a major application area because they have extensive historical clinical data, well-characterized biological activity, and established development profiles.

Regional Outlook

North America remained the leading regional market in 2025, generating 52.9% of global revenue. The U.S. held the largest country-level market share. The region benefits from concentrated AI startup activity, advanced pharmaceutical R&D capabilities, major research institutions, and established technology infrastructure.

Asia Pacific is projected to be the fastest-growing regional market from 2026 to 2033. Increasing investment in biotechnology, healthcare digitization, AI infrastructure, and drug discovery is expected to support regional expansion.

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Innovation, Competition, and Market Outlook

The AI in drug repurposing market is slightly fragmented, with established companies operating alongside emerging technology providers. New entrants are contributing to greater fragmentation as AI-driven drug discovery platforms become increasingly accessible.

Innovation remains particularly strong. Generative AI can be used to hypothesize potential drug-target interactions, while natural language processing (NLP) can extract information from biomedical literature, patents, clinical trial records, and other unstructured sources. These capabilities enable researchers to uncover relationships and therapeutic opportunities that may otherwise remain difficult to identify.

Collaboration is another defining characteristic of the market. Partnerships among AI developers, pharmaceutical companies, biotechnology firms, and academic institutions are supporting the development of specialized platforms for drug-repurposing workflows. The market also faces a high regulatory impact, as AI-generated insights must ultimately be evaluated within established drug-development and clinical-validation frameworks. Regional expansion is considered moderate.

Key Companies

Major companies profiled in the AI in drug repurposing market include:

• BostonGene Corporation
• BenevolentAI
• Innophore
• Delta4.ai
• BioXcel Therapeutics Inc.
• BullFrog AI Holdings, Inc.

Explore the full list of profiled companies operating in this market with recent strategic initiatives

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