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The global artificial intelligence in drug discovery market was valued at USD 2.55 Billion in 2025. It is poised to grow at a CAGR of 28.70% during the forecast period of 2026-2035, and reach USD 31.79 Billion by 2035. The market growth is driven by the increasing research and development costs and timelines, coupled with AI’s ability to accelerate target identification, optimize compounds, and predict outcomes. This adoption significantly improves efficiency, reduces failures, and enables faster drug development.
Base Year
Historical Period
Forecast Period
In February 2026, Takeda partnered with Iambic Therapeutics for USD 1.7B, leveraging AI for small-molecule oncology and gastrointestinal drug discovery.
In March 2025, Alphabet’s Isomorphic Labs raised USD 600M to accelerate AI-driven drug discovery, utilizing protein structure prediction and de novo drug design.
In October 2024, Iambic launched “Enchant,” an AI platform improving drug behavior predictions, reducing late-stage failures, and accelerating discovery pipelines.
Compound Annual Growth Rate
28.7%
Value in USD Billion
2026-2035
*this image is indicative*
Artificial Intelligence (AI) plays a transformative role in drug discovery by accelerating target identification, optimizing lead compounds, and predicting clinical outcomes with greater accuracy. It reduces time and costs associated with traditional R&D processes while minimizing failure rates. The market is poised to grow at a CAGR of 28.70% during the forecast period of 2026-2035, due to strong pharmaceutical and biotechnology presence, well-established infrastructure, and significant R&D investments. Strategic collaborations, increasing funding, and AI-driven platforms are enhancing efficiency, supporting precision medicine, and accelerating the overall drug discovery pipeline, positioning the market for substantial expansion during the forecast period.
Rising Strategic Investment Catalyzing AI Driven Drug Discovery is Likely to Enhance the Market Landscape
The growing demand to reduce R&D timelines and rising investor confidence in AI for pharmaceutical innovation are driving significant capital inflows into drug discovery platforms. For instance, in March 2025, Alphabet’s Isomorphic Labs raised USD 600 million in its first funding round for the AI drug business, the Alphabet‑backed AI drug discovery firm secured its first external financing of USD 600 million led by Thrive Capital, with support from Alphabet and Google Ventures. The funding will accelerate development of its next‑generation AI drug design engine, including protein structure prediction, ADMET prediction, and de novo drug design capabilities, and advance therapeutic programs toward clinical trials. This investment underscores heightened confidence in AI’s ability to transform drug discovery and is expected to drive broader AI adoption and innovation throughout the forecast period.
Key trends shaping the market include growing collaborations.
Increasing Strategic Collaborations Involving the AI Adoption in Drug Discovery to Boost Market Growth
Rising R&D costs and the increasing need to shorten drug development timelines are driving the adoption of AI-driven platforms, improving efficiency and reducing failure rates. For instance, in February 2026, Takeda announced a multi-year collaboration with Iambic Therapeutics valued at over USD 1.7 billion to advance AI-based small-molecule drug discovery for oncology and gastrointestinal diseases. The partnership leverages de novo drug design, target identification, and protein structure prediction to enhance pipeline productivity and clinical trial failure reduction risks during the forecast period.
Market Breakup by Process
Market Breakup by Technology
Market Breakup by Deployment
Market Breakup by Application
Market Breakup by End User
Market Breakup by Region
Oncology Expected to Dominate the Market Segment by Application
The market is divided into oncology, infectious disease, neurology, metabolic diseases, cardiovascular diseases, immunology, mental health disorders, and others, based on the application. Among these, the oncology segment emerged as the major application, accounting for nearly 24% of the revenue share during the historical period. This growth is largely supported by the increasing prevalence of cancer and the expanding use of AI in identifying drug targets, discovering biomarkers, and streamlining clinical trials. Furthermore, sustained investments by pharmaceutical companies in oncological research continue to reinforce the segment’s dominant position in the market.
The regions included in the market are North America, Europe, Asia Pacific, Latin America, and Middle East and Africa. Among these, North America held a significantposition in the market, contributing approximately 52% of the total revenue share during the historical period. This prominence is driven by the strong presence of major technology and pharmaceutical players, well-established healthcare infrastructure, and significant R&D spending. In addition, favorable regulatory support and rapid adoption of advanced AI technologies further strengthen the region’s market position.
The key features of the market report comprise patent analysis, grants analysis, funding and investment analysis, and strategic initiatives by the leading players. The major companies in the market are as follows:
IBM Corporation is a US-based multinational technology company headquartered in Armonk, New York, founded in 1911. IBM leverages its Watson platform to accelerate data-driven research, enabling target identification, clinical trial optimization, and molecular discovery. The company collaborates with pharmaceutical firms and research institutions to enhance drug development efficiency through advanced analytics and machine learning capabilities.
Deep Genomics is a Canada-based biotechnology company headquartered in Toronto, established in 2015. The company specializes in AI-driven RNA biology to identify novel drug targets and genetic therapies. Its proprietary platform uses machine learning to predict the effects of genetic mutations, supporting precision medicine and accelerating therapeutic development, particularly for rare diseases and genetic disorders.
Cloud Pharmaceuticals, Inc. is a US-based biotechnology company headquartered in North Carolina, founded in 2013. It focuses on AI-powered drug design using its Quantum Molecular Design platform, which integrates physics-based modeling and machine learning. The company develops novel therapeutics across oncology and other disease areas, enabling faster identification of drug candidates with improved efficacy and reduced development timelines.
Microsoft Corporation is a US-based multinational technology company headquartered in Redmond, Washington, established in 1975. In the AI-driven drug discovery space, Microsoft provides cloud-based AI tools through Azure, supporting data integration, predictive modeling, and collaboration. The company partners with pharmaceutical and biotech firms to accelerate drug development processes using scalable computing, advanced analytics, and artificial intelligence technologies.
*Please note that this is only a partial list; the complete list of key players is available in the full report. Additionally, the list of key players can be customized to better suit your needs.*
Other key players in the market are Exscientia, NVIDIA Corporation, Insilico Medicine, Atomwise, Inc., Biosymetrics, and Euretos.
*While we strive to always give you current and accurate information, the numbers depicted on the website are indicative and may differ from the actual numbers in the main report. At Expert Market Research, we aim to bring you the latest insights and trends in the market. Using our analyses and forecasts, stakeholders can understand the market dynamics, navigate challenges, and capitalize on opportunities to make data-driven strategic decisions.*
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| REPORT FEATURES | DETAILS |
| Base Year | 2025 |
| Historical Period | 2019-2025 |
| Forecast Period | 2026-2035 |
| Scope of the Report |
Historical and Forecast Trends, Industry Drivers and Constraints, Historical and Forecast Market Analysis by Segment:
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| Breakup by Process |
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| Breakup by Technology |
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| Breakup by Deployment |
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| Breakup by Application |
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| Breakup by End User |
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| Breakup by Region |
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| Market Dynamics |
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| Supplier Landscape |
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| Companies Covered |
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