The global artificial intelligence in drug discovery market was valued at USD 2.55 Billion in 2025, driven by the increasing demand for faster and cost-effective drug discovery processes and rising adoption of AI technologies by pharmaceutical companies across the globe. The market is anticipated to grow at a CAGR of 28.70% during the forecast period of 2026-2035, with the values likely to reach USD 31.79 Billion by 2035. The growing integration of machine learning and big data in drug development pipelines drives the market. Expanding collaborations between tech firms and biopharma companies is expected to boost growth during the forecast period.
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According to Dongning Su et al., global Parkinson’s disease cases are projected to rise by 112% from 2021 to 2050, reaching around 25.2 million. This sharp increase is accelerating the adoption of AI in drug discovery to meet therapeutic demand.
In June 2024, MIT researchers introduced the SPARROW algorithm to optimize molecule selection based on cost and efficacy, streamlining drug discovery. Such AI innovations are expected to significantly accelerate market growth by reducing development time and cost.
Artificial Intelligence in drug discovery is accelerating market growth by enhancing target identification, reducing development time, and improving success rates. Key players are leveraging AI-driven platforms to streamline R&D and gain competitive advantages.
Compound Annual Growth Rate
28.7%
Value in USD Billion
2026-2035
*this image is indicative*
Artificial Intelligence is transforming drug discovery by revolutionizing how researchers approach complex problems in medicine. It is driving a paradigm shift from traditional trial-and-error methods to data-driven, predictive approaches that enhance accuracy and speed. The global Artificial Intelligence in Drug Discovery market has witnessed robust growth due to rising R&D investments, technological advancements, and the increasing demand for precision medicine. The market was valued at USD 2.55 Billion in 2025 and is expected to expand significantly over the coming years, driven by growing adoption across the pharmaceutical and biotechnology industries for enhancing productivity and reducing time-to-market.
Strategic AI Tool Launches to Accelerate Market Growth
The increasing deployment of AI technologies by regulatory authorities to accelerate drug development and approval processes is a significant factor driving growth in the market. In June 2025, the U.S. Food and Drug Administration (FDA) launched Elsa, a generative AI tool designed to enhance clinical protocol reviews, support safety assessments, and streamline regulatory operations. This milestone launch signifies a broader institutional shift toward AI-driven innovation, reinforcing global confidence in AI-enabled drug discovery solutions and driving sustained market expansion.
The market is experiencing notable trends such as the transformation of drug discovery through multi-agent AI systems and the rapid adoption of AI technologies in oncology drug development.
Multi-Agent AI Systems Transforming Drug Discovery and Driving Market Expansion
The integration of multi-agent artificial intelligence systems into drug discovery is emerging as a transformative trend, enabling faster and more sophisticated research outputs. These AI models emulate scientific reasoning, facilitating hypothesis generation, experimental design, and iterative refinement of research strategies. For instance, in February 2025, a leading technology company introduced an AI co-scientist capable of autonomously generating high-quality, novel biomedical hypotheses. This advancement highlights how AI-driven collaboration tools are revolutionizing the drug discovery landscape, significantly propelling market growth.
Accelerated AI Adoption in Oncology Drug Discovery to Enhance Artificial Intelligence in Drug Discovery Market Demand
The integration of artificial intelligence (AI) into oncology drug discovery is reshaping the pharmaceutical research landscape by enabling faster, more precise, and cost-effective development processes. This trend is driving a shift away from traditional trial-and-error methods toward data-driven innovation. For instance, in December 2024, the ACCC report highlighted AI’s role in improving early-phase trial success and optimizing clinical strategies. This growing application is anticipated to significantly boost the market in the coming years.
Oncology to Lead the Market Share by Application
In the race to revolutionize drug discovery, artificial intelligence is emerging as a game-changer, particularly in applications where speed and precision are critical. The market is segmented into oncology, infectious disease, neurology, metabolic diseases, cardiovascular diseases, immunology, mental health disorders, and others. Among these, oncology is poised to take the lead. For instance, in March 2025, researchers at the Institute of Cancer Research, London, unveiled a groundbreaking AI ‘fingerprint’ technology. This tool uses 3D cell imaging and geometric deep learning to predict drug responses with up to 99.3% accuracy, significantly reducing time and cost in cancer drug development. According to the ICR, the innovation could cut preclinical drug development time from three years to three months, accelerating the delivery of life-saving therapies. With cancer remaining a major global health burden, the oncology segment continues to benefit from such innovations, solidifying its leadership position in the AI-driven drug discovery space.
The market is divided into regions such as North America, Europe, Asia-Pacific, Latin America, and the Middle East and Africa. Among these, North America holds the leading position, driven by substantial research and development funding, a strong technological foundation, and proactive regulatory initiatives. In January 2025, the U.S. FDA issued draft guidance supporting the use of Artificial Intelligence in regulatory decision-making, further highlighting the region’s dedication to advancing innovation. This leadership is anticipated to play a critical role in accelerating global progress in AI-driven drug discovery and therapeutic development.
The artificial intelligence in drug discovery market research report by Expert Market Research provides an in-depth analysis of the competitive landscape, offering key insights into patent filings, grants analysis, funding trends, investments, and strategic initiatives by major players. It tracks recent investments, mergers, acquisitions, and partnerships that showcase the market's growth trajectory. Additionally, the report details strategic activities by leading companies, including regional expansions, adoption of new technologies, and efforts to enhance capacity, helping stakeholders better understand the market dynamics and positions of key industry players. Some of the leading players are as follows:
IBM Corporation is a leading player in the market, leveraging its advanced AI platform, IBM Watson, to accelerate drug development. The company focuses on enhancing clinical trial efficiency, identifying novel drug candidates, and optimizing treatment pathways. IBM's AI tools, such as predictive models and machine learning algorithms, support data-driven research and decision-making, significantly reducing time and costs in drug discovery processes.
Deep Genomics is a biotechnology company leveraging proprietary artificial intelligence to accelerate RNA-based drug discovery. Its flagship platform, BigRNA, is the world’s first RNA foundation model, capable of identifying novel biological mechanisms and therapeutic candidates beyond the scope of traditional methods. Deep Genomics is at the forefront of the Global Artificial Intelligence in Drug Discovery Market, transforming RNA therapeutics development through advanced machine learning, including large language models and cutting-edge genomic prediction tools.
Cloud Pharmaceuticals, Inc. is a prominent player in the artificial intelligence in drug discovery market, specializing in the use of generative AI to accelerate pharmaceutical development. The company supports drug discovery from target evaluation to clinical research planning, offering molecule design and optimization services. Cloud Pharmaceuticals is actively developing a Generative AI-focused data center to enhance efficiency, reduce costs, and increase success rates in novel drug development.
Microsoft Corporation plays a significant role in the market growth by offering advanced AI-driven solutions that enhance pharmaceutical research and development. Through its Azure platform and AI capabilities, Microsoft supports key drug discovery stages, from target identification to compound optimization and clinical trial analysis. The company actively partners with pharmaceutical firms to accelerate drug development timelines, reduce costs, and improve success rates by leveraging machine learning, predictive analytics, and intelligent data processing tools.
*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 include Exscientia, NVIDIA Corporation, Insilico Medicine, Atomwise, Inc., Biosymetrics, and Euretos.
The market report offers a detailed analysis of the market based on the following segments:
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
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*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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