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    US AI Drug Discovery Market

    ID: MRFR/Pharma/12296-HCR
    100 Pages
    Garvit Vyas
    September 2025

    US AI Drug Discovery Market Research Report By Application (Target Identification, Lead Optimization, Drug Repurposing, Clinical Trials, Preclinical Testing), By Technology (Machine Learning, Natural Language Processing, Deep Learning, Knowledge Graphs, Robotic Process Automation), By End Use (Pharmaceutical Companies, Biotechnology Firms, Research Institutions, Academic Institutions) and By Workflow (Data Mining, Predictive Modeling, Clinical Data Management, Assay Development) - Forecast to 2035

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    Table of Contents

    US AI Drug Discovery Market Summary

    The US AI Drug Discovery market is projected to grow significantly from 924 million USD in 2024 to 5250 million USD by 2035.

    Key Market Trends & Highlights

    US AI Drug Discovery Key Trends and Highlights

    • The market is expected to experience a compound annual growth rate of 17.11 percent from 2025 to 2035.
    • By 2035, the market valuation is anticipated to reach 5250 million USD, indicating robust growth potential.
    • In 2024, the market is valued at 924 million USD, reflecting the current investment landscape in AI-driven drug discovery.
    • Growing adoption of AI technologies due to increasing demand for efficient drug development is a major market driver.

    Market Size & Forecast

    2024 Market Size 924 (USD Million)
    2035 Market Size 5250 (USD Million)
    CAGR (2025-2035) 17.11%

    Major Players

    Bristol Myers Squibb, Novartis, AstraZeneca, Merck, GlaxoSmithKline, Biogen, Gilead Sciences, Regeneron Pharmaceuticals, Pfizer, Amgen, Roche, AbbVie, Sanofi, Johnson and Johnson, Vertex Pharmaceuticals

    US AI Drug Discovery Market Trends

    The US AI drug discovery market is experiencing significant trends driven by technological advancements and the demand for faster drug development processes. One of the key market drivers is the increasing need for efficient and cost-effective solutions in the healthcare sector, particularly in the wake of rising pharmaceutical costs and longer approval times. The integration of AI technologies into drug discovery allows companies to process vast datasets, identify potential drug candidates, and predict outcomes more rapidly than traditional methods.

    Moreover, collaborations between tech companies and pharmaceutical firms are gaining traction, creating opportunities for innovation in drug design and personalized medicine. Opportunities in the US AI drug discovery market are being further enhanced by the supportive regulatory environment and funding from government initiatives aimed at fostering innovation in healthcare. Programs that encourage artificial intelligence research and development are providing a fertile ground for startups and established companies alike to explore new technologies and applications within drug discovery.

    As the US government continues to invest in healthcare technology, there is ample opportunity for players to leverage these advancements to improve patient outcomes. Recent trends highlight the growing use of machine learning algorithms and advanced data analytics in pharmaceutical research. The increasing availability of genomic data and electronic health records supports the application of AI in predicting drug interactions and patient responses.

    Furthermore, the COVID-19 pandemic has accelerated the adoption of AI solutions in drug discovery, emphasizing the urgent need for rapid vaccine development and therapeutic interventions. As the healthcare landscape continues to evolve, the focus on AI-driven drug discovery solutions is likely to expand, shaping the future of pharmaceutical research in the US.

    US AI Drug Discovery Market Drivers

    Market Segment Insights

    AI Drug Discovery Market Application Insights

    The Application segment of the US AI Drug Discovery Market represents a critical area where artificial intelligence is transforming various processes involved in drug development. This segment encompasses a range of functionalities, including Target Identification, Lead Optimization, Drug Repurposing, Clinical Trials, and Preclinical Testing, each contributing significantly to the advancement of pharmaceutical research.

    Target Identification plays a vital role as it helps in recognizing suitable biological molecules that could be attacked by drug therapies, thereby streamlining the early stages of drug discovery. This efficient targeting accelerates the pace of novel treatment development and lowers research costs. Lead Optimization is equally prominent, focusing on enhancing the properties of drug candidates to improve efficacy while minimizing side effects and toxicity.

    AI algorithms analyze vast datasets to predict the most favorable molecular modifications, which is essential for developing safe and effective medications. Drug Repurposing offers a unique advantage in this landscape, capitalizing on existing drugs that can potentially treat diseases beyond their initial indications. This approach not only shortens the time to market for new therapies but also utilizes available resources better, addressing urgent healthcare needs more quickly.

    Clinical Trials are another critical focus area in this segment, where AI contributes to patient selection, trial design, and monitoring processes. By employing sophisticated data analytics, AI enables researchers to optimize trial outcomes, ensuring that treatments are tested effectively and efficiently. Lastly, Preclinical Testing is vital for assessing new compounds' safety and biological activity before human trials.

    Through the use of AI in preclinical settings, there is an opportunity to increase the predictive value of early testing, thereby reducing the risk of clinical failures. Collectively, these applications highlight how the US AI Drug Discovery Market is leveraging cutting-edge technologies to enhance drug development processes, promote innovative treatment discovery, and ultimately improve patient outcomes. The ongoing evolution within this market circumference due to advancements in AI technology reflects a robust potential for growth and transformation in the pharmaceutical industry, addressing both current and future healthcare challenges through enhanced efficiencies and insights.

    Source: Primary Research, Secondary Research, Market Research Future Database and Analyst Review

    AI Drug Discovery Market Technology Insights

    The Technology segment of the US AI Drug Discovery Market showcases a dynamic landscape that significantly enhances the efficiency and effectiveness of pharmaceutical development. Machine Learning is critical, enabling predictive analytics and improving drug design processes by uncovering complex patterns in biological data. Natural Language Processing plays a vital role in mining scientific literature and extracting relevant information, facilitating faster research insights.

    Deep Learning stands out for its ability to analyze large datasets, which is invaluable in genomics and compound screening, while Knowledge Graphs provide a structured representation of relationships and data integration, enhancing the understanding of drug interactions. Robotic Process Automation boosts operational efficiency by automating repetitive tasks, allowing researchers to focus on more complex challenges.

    As these technologies evolve, they contribute to transforming traditional R&D approaches, driving innovation within the industry and ultimately leading to breakthroughs in drug discovery. The adoption of these technologies is expected to increase, responding to the high demand for quicker and more reliable drug development processes. The interplay among these technologies creates opportunities for holistic solutions that could address existing challenges in the pharmaceutical landscape, making them indispensable in advancing drug discovery initiatives across the United States.

    AI Drug Discovery Market End Use Insights

    The US AI Drug Discovery Market, particularly under the End Use segment, showcases a diverse landscape with significant contributions from various sectors including Pharmaceutical Companies, Biotechnology Firms, Research Institutions, and Academic Institutions. Pharmaceutical Companies are increasingly leveraging AI technologies to streamline their research processes, reduce drug development time, and enhance precision in clinical trials. This reflects the shift towards data-driven approaches in drug discovery.

    Biotechnology Firms, known for their innovative methodologies, utilize AI to accelerate the discovery of biologically complex molecules, thus playing a crucial role in developing next-generation therapies. Research Institutions apply AI algorithms to analyze vast datasets, enabling breakthroughs in understanding disease mechanisms and identifying novel therapeutic targets.

    Academic Institutions, integral to the training of future researchers and professionals, often lead pioneering research initiatives utilizing AI in drug discovery, contributing to a strong pipeline of new discoveries. Overall, the factors driving the growth of these segments include advancements in computational power, the availability of biological data, and the increasing demand for personalized medicine, positioning the US at the forefront of innovation within the AI Drug Discovery Market.

    AI Drug Discovery Market Workflow Insights

    The Workflow segment of the US AI Drug Discovery Market is crucial as it encompasses various processes essential for streamlining drug development. This segment significantly contributes to the efficient handling of data and enhances decision-making across multiple phases of research. Data Mining plays a vital role in uncovering hidden patterns and insights from extensive datasets, making it fundamental for identifying potential drug candidates.

    Predictive Modeling is essential for forecasting therapeutic outcomes, enabling researchers to make informed decisions early in the drug discovery process. Clinical Data Management ensures the integrity and security of clinical trial data, which is critical for regulatory compliance and trust in research findings.

    Assay Development is significant as it aids in validating drug efficacy and safety, thereby guiding the overall research strategy. The importance of these processes cannot be overstated, as they collectively improve the efficacy of the drug discovery pipeline, ultimately expediting the delivery of new therapies to the market.

    As the US continues to invest heavily in biotechnology and pharmaceuticals, the Workflow segment of the AI Drug Discovery Market will remain a focal point for innovation and growth.

    Get more detailed insights about US AI Drug Discovery Market

    Regional Insights

    Key Players and Competitive Insights

    The US AI Drug Discovery Market has emerged as a dynamic sector where innovation and technology intersect with pharmaceutical development, offering transformative solutions to traditional drug discovery processes. As companies harness the power of artificial intelligence and machine learning, the landscape has become increasingly competitive, with key players rapidly advancing their capabilities to streamline drug development timelines, reduce costs, and enhance the accuracy of predictions regarding drug efficacy and safety.

    The competitive insights within this market shed light on how organizations are positioning themselves against rivals, developing proprietary technologies, forming strategic partnerships, and navigating regulatory challenges, all while keeping an eye on the evolving healthcare landscape and patient needs. The agility to adapt and innovate will define the leaders in this market as they leverage AI to unlock new therapeutic potentials.

    Bristol Myers Squibb has solidified its presence in the US AI Drug Discovery Market through a robust commitment to utilizing advanced technologies in its research and development processes. The company has invested significantly in AI-driven platforms that assist in target identification and drug repurposing, driving improvements in the efficiency of its pipeline development. One of the key strengths of Bristol Myers Squibb lies in its strategic collaborations with technology firms, which enhance its data analytics capabilities and expand its research footprint.

    Furthermore, the company’s established therapeutic areas, particularly in immunology and oncology, provide a rich landscape for AI applications, enabling it to capitalize on breakthroughs in these high-demand sectors while maintaining a competitive edge. Novartis, another crucial player in the US AI Drug Discovery Market, has embraced artificial intelligence to accelerate its drug development cycle and optimize clinical trial designs.

    With a focus on precision medicine, Novartis harnesses AI to identify patient populations that are most likely to benefit from new therapies, thus enhancing the likelihood of successful clinical outcomes. The company has also expanded its investment in technology platforms that utilize machine learning algorithms to analyze large datasets effectively. Its strengths include a well-established portfolio of diverse therapeutic areas, including cardiovascular, infectious diseases, and neurological disorders, which present unique opportunities for AI applications.

    Novartis has been active in mergers and acquisitions, strategically acquiring companies with advanced technologies and capabilities in AI to bolster its research pipeline. This proactive approach not only strengthens Novartis's market presence but also enhances its ability to navigate the rapidly changing landscape of drug discovery through innovative solutions.

    Key Companies in the US AI Drug Discovery Market market include

    Industry Developments

    The US AI Drug Discovery Market has seen significant advancements recently, particularly with companies like Bristol Myers Squibb, Novartis, and AstraZeneca integrating artificial intelligence into their processes. In October 2023, a collaboration was announced between Merck and a prominent AI firm to enhance drug discovery efficiencies. Additionally, the market experienced considerable growth, with valuations of major players such as Pfizer and Gilead Sciences reportedly increasing due to AI-driven innovations that expedite clinical trials and drug development timelines.

    Recent mergers include GlaxoSmithKline acquiring a biotech startup focused on AI technologies in drug candidates in August 2023, further emphasizing the trend toward leveraging AI for competitive advantage. Over the past few years, there has been a marked rise in investments in AI applications from companies like Regeneron Pharmaceuticals and Amgen, with estimates indicating a 30% boost in R&D productivity and reduced time to market for new therapeutics.

    The evolving landscape in US AI Drug Discovery is being driven not only by technological advancements but also by regulatory support from initiatives aimed at fostering innovation in drug development practices.

    Market Segmentation

    AI Drug Discovery Market End Use Outlook

    • Pharmaceutical Companies
    • Biotechnology Firms
    • Research Institutions
    • Academic Institutions

    AI Drug Discovery Market Workflow Outlook

    • Data Mining
    • Predictive Modeling
    • Clinical Data Management
    • Assay Development

    AI Drug Discovery Market Technology Outlook

    • Machine Learning
    • Natural Language Processing
    • Deep Learning
    • Knowledge Graphs
    • Robotic Process Automation

    AI Drug Discovery Market Application Outlook

    • Target Identification
    • Lead Optimization
    • Drug Repurposing
    • Clinical Trials
    • Preclinical Testing

    Report Scope

    Report Attribute/Metric Source: Details
    MARKET SIZE 2018 789.6(USD Million)
    MARKET SIZE 2024 924.0(USD Million)
    MARKET SIZE 2035 5250.0(USD Million)
    COMPOUND ANNUAL GROWTH RATE (CAGR) 17.109% (2025 - 2035)
    REPORT COVERAGE Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
    BASE YEAR 2024
    MARKET FORECAST PERIOD 2025 - 2035
    HISTORICAL DATA 2019 - 2024
    MARKET FORECAST UNITS USD Million
    KEY COMPANIES PROFILED Bristol Myers Squibb, Novartis, AstraZeneca, Merck, GlaxoSmithKline, Biogen, Gilead Sciences, Regeneron Pharmaceuticals, Pfizer, Amgen, Roche, AbbVie, Sanofi, Johnson and Johnson, Vertex Pharmaceuticals
    SEGMENTS COVERED Application, Technology, End Use, Workflow
    KEY MARKET OPPORTUNITIES Increased R&D efficiency, AI-driven personalized medicine, Integration with genomics data, Enhanced predictive modeling capabilities, Cost reduction in clinical trials
    KEY MARKET DYNAMICS Growing computational power, Increased investment in biotechnology, Rising demand for personalized medicine, Regulatory advancements and support, Collaboration among tech companies and pharma
    COUNTRIES COVERED US

    Market Highlights

    Author
    Garvit Vyas
    Analyst

    Explore the profile of Garvit Vyas, one of our esteemed authors at Market Research Future, and access their expert research contributions in the field of market research and industry analysis

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    FAQs

    What is the expected market size of the US AI Drug Discovery Market in 2024?

    In 2024, the US AI Drug Discovery Market is expected to be valued at 924.0 million USD.

    What is the projected market size for the US AI Drug Discovery Market by 2035?

    By 2035, the overall market size for the US AI Drug Discovery Market is anticipated to reach 5250.0 million USD.

    What is the expected compound annual growth rate (CAGR) for the US AI Drug Discovery Market from 2025 to 2035?

    The expected CAGR for the US AI Drug Discovery Market from 2025 to 2035 is 17.109 percent.

    Which application segment will have the largest market share in the US AI Drug Discovery Market by 2035?

    By 2035, the Target Identification application segment is projected to hold the largest market share, valued at 1550.0 million USD.

    What are the key players in the US AI Drug Discovery Market?

    Some major players in the US AI Drug Discovery Market include Bristol Myers Squibb, Novartis, AstraZeneca, Merck, and GlaxoSmithKline.

    How much is the Lead Optimization application segment valued in 2024?

    The Lead Optimization application segment is valued at 210.0 million USD in the year 2024.

    What is the market size for Drug Repurposing in 2035?

    The Drug Repurposing application segment is expected to be valued at 900.0 million USD by 2035.

    What will be the market value of Clinical Trials application by 2035?

    The Clinical Trials application segment is projected to reach a market value of 750.0 million USD by 2035.

    What challenges and trends are influencing the US AI Drug Discovery Market?

    Key trends and opportunities in the market include advancements in AI technology and increasing investment in drug discovery, while challenges include regulatory hurdles.

    What is the expected market size for Preclinical Testing in 2024 and 2035?

    The Preclinical Testing application segment is expected to be valued at 114.0 million USD in 2024 and 750.0 million USD by 2035.

    1. EXECUTIVE SUMMARY
    2. Market Overview
    3. Key Findings
    4. Market Segmentation
    5. Competitive Landscape
    6. Challenges and Opportunities
    7. Future Outlook
    8. MARKET INTRODUCTION
    9. Definition
    10. Scope of the study
    11. Research Objective
    12. Assumption
    13. Limitations
    14. RESEARCH METHODOLOGY
    15. Overview
    16. Data Mining
    17. Secondary Research
    18. Primary Research
    19. Primary Interviews and Information Gathering Process
    20. Breakdown of Primary Respondents
    21. Forecasting Model
    22. Market Size Estimation
    23. Bottom-Up Approach
    24. Top-Down Approach
    25. Data Triangulation
    26. Validation
    27. MARKET DYNAMICS
    28. Overview
    29. Drivers
    30. Restraints
    31. Opportunities
    32. MARKET FACTOR ANALYSIS
    33. Value chain Analysis
    34. Porter's Five Forces Analysis
    35. Bargaining Power of Suppliers
    36. Bargaining Power of Buyers
    37. Threat of New Entrants
    38. Threat of Substitutes
    39. Intensity of Rivalry
    40. COVID-19 Impact Analysis
    41. Market Impact Analysis
    42. Regional Impact
    43. Opportunity and Threat Analysis
    44. US AI Drug Discovery Market, BY Application (USD Million)
    45. Target Identification
    46. Lead Optimization
    47. Drug Repurposing
    48. Clinical Trials
    49. Preclinical Testing
    50. US AI Drug Discovery Market, BY Technology (USD Million)
    51. Machine Learning
    52. Natural Language Processing
    53. Deep Learning
    54. Knowledge Graphs
    55. Robotic Process Automation
    56. US AI Drug Discovery Market, BY End Use (USD Million)
    57. Pharmaceutical Companies
    58. Biotechnology Firms
    59. Research Institutions
    60. Academic Institutions
    61. US AI Drug Discovery Market, BY Workflow (USD Million)
    62. Data Mining
    63. Predictive Modeling
    64. Clinical Data Management
    65. Assay Development
    66. Competitive Landscape
    67. Overview
    68. Competitive Analysis
    69. Market share Analysis
    70. Major Growth Strategy in the AI Drug Discovery Market
    71. Competitive Benchmarking
    72. Leading Players in Terms of Number of Developments in the AI Drug Discovery Market
    73. Key developments and growth strategies
    74. New Product Launch/Service Deployment
    75. Merger & Acquisitions
    76. Joint Ventures
    77. Major Players Financial Matrix
    78. Sales and Operating Income
    79. Major Players R&D Expenditure. 2023
    80. Company Profiles
    81. Bristol Myers Squibb
    82. Financial Overview
    83. Products Offered
    84. Key Developments
    85. SWOT Analysis
    86. Key Strategies
    87. Novartis
    88. Financial Overview
    89. Products Offered
    90. Key Developments
    91. SWOT Analysis
    92. Key Strategies
    93. AstraZeneca
    94. Financial Overview
    95. Products Offered
    96. Key Developments
    97. SWOT Analysis
    98. Key Strategies
    99. Merck
    100. Financial Overview
    101. Products Offered
    102. Key Developments
    103. SWOT Analysis
    104. Key Strategies
    105. GlaxoSmithKline
    106. Financial Overview
    107. Products Offered
    108. Key Developments
    109. SWOT Analysis
    110. Key Strategies
    111. Biogen
    112. Financial Overview
    113. Products Offered
    114. Key Developments
    115. SWOT Analysis
    116. Key Strategies
    117. Gilead Sciences
    118. Financial Overview
    119. Products Offered
    120. Key Developments
    121. SWOT Analysis
    122. Key Strategies
    123. Regeneron Pharmaceuticals
    124. Financial Overview
    125. Products Offered
    126. Key Developments
    127. SWOT Analysis
    128. Key Strategies
    129. Pfizer
    130. Financial Overview
    131. Products Offered
    132. Key Developments
    133. SWOT Analysis
    134. Key Strategies
    135. Amgen
    136. Financial Overview
    137. Products Offered
    138. Key Developments
    139. SWOT Analysis
    140. Key Strategies
    141. Roche
    142. Financial Overview
    143. Products Offered
    144. Key Developments
    145. SWOT Analysis
    146. Key Strategies
    147. AbbVie
    148. Financial Overview
    149. Products Offered
    150. Key Developments
    151. SWOT Analysis
    152. Key Strategies
    153. Sanofi
    154. Financial Overview
    155. Products Offered
    156. Key Developments
    157. SWOT Analysis
    158. Key Strategies
    159. Johnson and Johnson
    160. Financial Overview
    161. Products Offered
    162. Key Developments
    163. SWOT Analysis
    164. Key Strategies
    165. Vertex Pharmaceuticals
    166. Financial Overview
    167. Products Offered
    168. Key Developments
    169. SWOT Analysis
    170. Key Strategies
    171. References
    172. Related Reports
    173. US AI Drug Discovery Market SIZE ESTIMATES & FORECAST, BY APPLICATION, 2019-2035 (USD Billions)
    174. US AI Drug Discovery Market SIZE ESTIMATES & FORECAST, BY TECHNOLOGY, 2019-2035 (USD Billions)
    175. US AI Drug Discovery Market SIZE ESTIMATES & FORECAST, BY END USE, 2019-2035 (USD Billions)
    176. US AI Drug Discovery Market SIZE ESTIMATES & FORECAST, BY WORKFLOW, 2019-2035 (USD Billions)
    177. PRODUCT LAUNCH/PRODUCT DEVELOPMENT/APPROVAL
    178. ACQUISITION/PARTNERSHIP
    179. MARKET SYNOPSIS
    180. US AI DRUG DISCOVERY MARKET ANALYSIS BY APPLICATION
    181. US AI DRUG DISCOVERY MARKET ANALYSIS BY TECHNOLOGY
    182. US AI DRUG DISCOVERY MARKET ANALYSIS BY END USE
    183. US AI DRUG DISCOVERY MARKET ANALYSIS BY WORKFLOW
    184. KEY BUYING CRITERIA OF AI DRUG DISCOVERY MARKET
    185. RESEARCH PROCESS OF MRFR
    186. DRO ANALYSIS OF AI DRUG DISCOVERY MARKET
    187. DRIVERS IMPACT ANALYSIS: AI DRUG DISCOVERY MARKET
    188. RESTRAINTS IMPACT ANALYSIS: AI DRUG DISCOVERY MARKET
    189. SUPPLY / VALUE CHAIN: AI DRUG DISCOVERY MARKET
    190. AI DRUG DISCOVERY MARKET, BY APPLICATION, 2025 (% SHARE)
    191. AI DRUG DISCOVERY MARKET, BY APPLICATION, 2019 TO 2035 (USD Billions)
    192. AI DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2025 (% SHARE)
    193. AI DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2019 TO 2035 (USD Billions)
    194. AI DRUG DISCOVERY MARKET, BY END USE, 2025 (% SHARE)
    195. AI DRUG DISCOVERY MARKET, BY END USE, 2019 TO 2035 (USD Billions)
    196. AI DRUG DISCOVERY MARKET, BY WORKFLOW, 2025 (% SHARE)
    197. AI DRUG DISCOVERY MARKET, BY WORKFLOW, 2019 TO 2035 (USD Billions)
    198. BENCHMARKING OF MAJOR COMPETITORS

    US AI Drug Discovery Market Segmentation

    • AI Drug Discovery Market By Application (USD Million, 2019-2035)

      • Target Identification
      • Lead Optimization
      • Drug Repurposing
      • Clinical Trials
      • Preclinical Testing
    • AI Drug Discovery Market By Technology (USD Million, 2019-2035)

      • Machine Learning
      • Natural Language Processing
      • Deep Learning
      • Knowledge Graphs
      • Robotic Process Automation

     

    • AI Drug Discovery Market By End Use (USD Million, 2019-2035)

      • Pharmaceutical Companies
      • Biotechnology Firms
      • Research Institutions
      • Academic Institutions

     

    • AI Drug Discovery Market By Workflow (USD Million, 2019-2035)

      • Data Mining
      • Predictive Modeling
      • Clinical Data Management
      • Assay Development

     

     

     

     

     

     

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