According to Precedence Research, the global AI in drug discovery market size is calculated at USD 6.93 billion in 2025 and is expected to be worth around USD 16.52 billion by 2034, growing at a CAGR of 10.10 % from 2025 to 2034.
In terms of revenue, the artificial intelligence (AI) in drug discovery market was valued at USD 6.31 billion in 2024. On the other hand, the drug discovery market size accounted for USD 65.84 billion in 2024.
In terms of CAGR, the AI in drug discovery market is poised to grow at a CAGR of 10.10% from 2025 to 2034. On the other hand, the drug discovery market is growing at a CAGR of 9.20% between 2025 and 2034.
The rising demand to accelerate the drug discovery and development process through research focuses on finding medications that are effective in treating particular diseases.
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Market Overview and Industry Potential
The integration of artificial intelligence into drug discovery has significantly stepped up its application in the pharmaceutical industry, which includes not only drug discovery but also drug development, repurposing, improving pharmaceutical productivity, clinical trials, and many more. The artificial intelligence (AI) in drug discovery market has considerably reduced the human workload and has commenced achieving targets in a short period of time.
The adequacy of advanced technologies encourages the drug development process, saving time and money through artificial intelligence. AI has the potential to recognize hit and lead compounds and provide quick validation of drug targets and optimization of drug structure design. AI has various applications in drug discovery, including drug design, polypharmacology, chemical synthesis, drug repurposing, and drug screening. The primary factor driving the market is how AI can effectively use different parts of drug discovery.
Artificial Intelligence (AI) In Drug Discovery Market Key Takeaways
• North America led the market with the largest market share of 56.18% in 2024.
• Asia Pacific market is projected to grow at a notable CAGR of 21.1% from 2025 to 2034.
• The oncology segment held a major market share of 21% in 2024.
• The drug optimization and repurposing segment contributed the highest market share of 51% in 2024.
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Major Trends in the Artificial Intelligence (AI) in Drug Discovery Market
Target Identification
The incorporation of artificial intelligence into drug discovery and development has the potential to identify drug targets with great expediency. With the help of algorithms powered by machine learning, the extensive database can swiftly analyze the potential drug candidate. Through this action, the discovery process can accelerate the streamlining, ultimately saving time and resources for research and pharmaceutical companies.
Improved Clinical Trials
AI has the capability to analyze large clinical trial datasets to identify patient populations. AI facilitates optimizing trial designs by identifying patients who are most likely to respond positively to a specific treatment.
Using AI-driven wear devices helps in monitoring real-time data, ensuring precision data collection and essential adjustment to the trial protocol for enhanced patient safety. Moreover, AI algorithms play a role in offering robust data analysis and valuable insights for future research and clinical practices.
Predict the Drug Efficacy and Toxicity
AI models can predict how a particular drug will interact with the body. Researchers use techniques such as quantitative structure-activity relationship (QSAR) modeling and molecular docking to predict the bioactivity of different compounds within a drug. This is achieved by utilizing deep learning techniques that intricately detect the patterns and relations within the vast dataset.
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Artificial Intelligence (AI) In Drug Discovery Market Scope
|
Report Attributes |
Key Statistics |
|
Market Size in 2025 |
USD 6.93 billion |
|
Market Size by 2034 |
USD 16.52 billion |
|
CAGR 2025 to 2034 |
10.10% |
|
Base Year |
2024 |
|
Forecast Period |
2025 to 2034 |
|
Segments Covered |
Type, Application, Drug Type, Offering, Technology, End User, and Regions |
|
Regions Covered |
North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
What is the Market Size for Drug Discovery?
The global drug discovery market size was valued at USD 65.84 billion in 2024 and is predicted increase from USD 71.89 billion in 2025 to approximately USD 158.74 billion by 2034, expanding at a CAGR of 9.20% between 2024 and 2034.
Drug Discovery Market Top Companies
• Pfizer Inc.
• GlaxoSmithKline PLC
• Merck & Co. Inc.
• Agilent Technologies Inc.
• Eli Lilly and Company
• F. Hoffmann-La Roche Ltd
• Bayer AG
• Abbott Laboratories Inc.
• AstraZeneca PLC
• Shimadzu Corp
Regional Analysis of Artificial Intelligence (AI) In Drug Discovery Market
What is the current size of U.S. Artificial intelligence (AI) in Drug Discovery Market?
The U.S. artificial intelligence (AI) in drug discovery market size reached USD 2.61 billion in 2024 and is projected to reach approximately USD 6.93 billion by 2034, expanding a CAGR of 10.26% from 2025 to 2034.
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North America led the market with the largest revenue share in 2024. The dominance of this region is credited to the large patient population with diverse diseases. Americans also have a robust healthcare infrastructure, as it incorporates advanced medical technology and research capabilities. The United States has the greatest medical research and development, producing groundbreaking treatments and technologies.
There are substantial investments in healthcare technology. Investment in drug research and development in the United States is increasing every year, which is made possible by both government and private companies. The U.S. has spent approximately USD 100 billion annually over the past decade on illicit drugs.
Asia Pacific is expected to witness the fastest growth in the market during the forecast period. The expansion of this region is experienced due to the rising prevalence of chronic diseases and healthcare expenditure, which is influenced by a number of factors, including population, income, and government policies.
Asia Pacific has a large and diverse patient pool, making it a prime location for clinical trials due to its vast population, diverse ethnic groups, and access to treatment-naive patients across various medical conditions.
Artificial Intelligence (AI) in Drug Discovery Market Segmentation
Type Insights
The preclinical and clinical segment has held a major revenue artificial intelligence (AI) in drug discovery market in 2024. The dominance of this segment is observed as AI in drug discovery offers to identify potential drugs, optimizes trial design, and improves patient outcomes, contributing to both preclinical and clinical trials.
Integration of AI into preclinic research includes identifying the drug from the large dataset, predicting how compounds will interact with others, and streamlining data analysis, which AI can automate the process. Now, in clinical trials, AI optimizes the trial design, improving patient recruitment and outcomes, analyzing patient data to identify biomarkers and predict treatment response, and personalizing the therapies as per the individual.
Offering Insights
The software segment will contribute more share of the artificial intelligence (AI) in drug discovery market in 2024. Integration of AI-powered drug discovery software uses machine learning to identify potential drug candidates, design new molecules, and predict drug properties.
The software facilitates speeding up the research by processing large amounts of data in a short time, minimizing errors, and providing accuracy. Additionally, it reduces cost, which helps allocate resources more effectively. For instance, Modern pharmaceutical laboratories use interconnected digital systems where laboratory information management systems (LIMS) work with specialist drug discovery tools.
The service segment is projected to have the highest growth during the forecast period. The expansion of this segment is noted as it leverages artificial intelligence technologies to analyze vast amounts of data across various stages of drug discovery and development. This allows for faster, more efficient identification of potential drug candidates by predicting their efficacy and toxicity, which ultimately accelerates the process.
Technology Insights
The machine learning segment dominated the artificial intelligence (AI) in drug discovery market in 2024. The integration of machine learning in AI in drug discovery allows for the enhancement of clinical trials through patient screening and enrollment to accelerate the drug discovery and development process.
The only and primary function of machine learning is to analyze large datasets of potential compounds and identify the most potential to treat the disease.
Application Insights
The oncology segment has held the largest market share in 2024. The dominance of this segment is noted due to the pharmacological viability offered by AI for anti-cancer drug targets. AI attends to the cancer drug design process, which increases the chances of clinical trials being successful. AI helps improve the speed, accuracy, and reliability of cancer screening and detection methods.
The neurodegenerative segment will grow rapidly in the coming years. The growth of this segment is observed as it analyses the vast dataset to design novel molecules, predict drug efficacy and toxicity, and personalized treatment to accelerate the development of new therapies for neurological diseases, including Alzheimer’s, Parkinson’s, and epilepsy, along with potentially decreasing the cost and improving the success rate in clinical trials.
End-User Insights
The pharmaceutical and biotechnology companies segment dominated the artificial intelligence (AI) in drug discovery market in 2024. The dominance of this segment is observed as it is the responsibility of pharmaceutical and biotechnology companies to provide large, detailed volumes of complex biological and chemical data, which helps in training AI models and allows for faster and more accurate identification of potential drug candidates, along with optimizing molecular structure and prediction of drug efficacy and toxicity.
Biotech companies such as Generate Biomedicines, Exscientia, Absci Corporation, and many more are working towards optimizing protein design, improving clinical trial outcomes, and discovering novel biomarkers.
The contract research organizations segment is anticipated to grow at a solid CAGR over the projected period. The CRO segment has been experiencing significant growth as AI-driver drug discoveries are transforming the pharmaceutical industry in terms of the research and development landscape.
Contract Research organization leverages AI to speed the process and efficiency, enhance accuracy, and allow for partnership and collaboration with pharmaceutical companies, biotech, and academics, fostering innovation and knowledge.
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Artificial Intelligence (AI) In Drug Discovery Market Companies
• NVIDIA CORPORATION
• Microsoft Corporation
• INSILICO MEDICINE INC.
• Schrödinger
• EXSCIENTIA
• Cloud Pharmaceuticals
• CLOUD PHARMACEUTICAL
• TOMWISE, INC
What is Going Around the Globe?
• In February 2025, Mitsubishi, NTT, NTT Com, Morgenrot, and iPark Institute collaborated on an experiment of remote provision of GPU computing power at Shonan Health Innovation Park and data centers operated by MC Digital Realty. The computing power allows multiple tenant companies to perform AI analysis securely and efficiently. This initiative aims to establish a safe infrastructure model.
• In February 2025, a Former DeepMind Scientist launched an AI drug discovery venture; Simon Kohl aims to capitalize on his experience with the Nobel-recognised AlphaFold protein prediction system. Simon Kohl raised $50 million to launch Latent Labs, a start-up to discover new drugs, providing a generative AI platform.
Segments Covered in the Report
By Type
• Preclinical and Clinical Testing
• Molecule Screening
• Target Identification
• De Novo Drug Design and Drug Optimization
By Drug Type
• Small Molecules
• Large Molecules
By Offering
• Software
• Services
By Technology
• Machine Learning
o Deep Learning
o Supervised Learning
o Reinforcement Learning
o Unsupervised Learning
o Other Machine Learning Technologies
• Other Technologies
By Application
• Neurology
• Infectious Disease
• Oncology
• Others
By End User
• Pharmaceutical & Biotechnology Companies
• Contract Research Organizations
• Academics & Research
• Others
By Regions
• Europe
• Asia Pacific
• Latin America
• Middle East & Africa (MEA)
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