The global Aartificial Intelligence (AI) in drug discovery market size is expected to reach nearly USD 16.52 billion by 2034, increasing from USD 6.93 billion in 2025. The market is accelerating a healthy CAGR of 10.10% between 2025 and 2034. The increasing investment in technologies in the healthcare and pharmaceutical sectors for improving treatment outcomes and disease management boosts the growth of the market.
In terms of revenue, the AI in Drug Discovery market is projected to exceed USD 11,32o million by the end of 2030, driven by the rising adoption of advanced algorithms that accelerate target identification, molecule design, and clinical decision-making. As pharmaceutical R&D seeks faster, cost-efficient development pathways, AI is becoming a core technology transforming how new therapies are discovered and optimized. North America held the largest share at 56.18% in 2024, while APAC is set to grow at a strong CAGR of 21.1% from 2025 to 2034.
Note: This report is readily
available for immediate delivery. We can review it with you in a meeting to
ensure data reliability and quality for decision-making. AI in Drug
Discovery Market Overview and Industry Potential The
association of artificial intelligence with the different healthcare streams
or applications revolutionizes the efficiency and productivity of the industry.
The integration of AI into the drug discovery and development process
significantly impacts pharmaceutical research. The implementation of AI
into several drug discovery applications helps the identification of several
disease mechanisms and offers useful insights for the development of the drug
for that disease, for better outcomes and results. The emergence
of smart technologies such as AI, automation, wearable technology, robotics, telehealth, mobile healthcare solutions, and
several others in the wide range of healthcare applications drives the growth
of artificial intelligence (AI) in drug discovery market. Major
Trends in the AI in Drug Discovery Market 🔹Increasing Prevalence of Chronic
Diseases The growing
cases of chronic diseases such as cancer, cardiovascular disease, infectious
diseases, respiratory illness, and others boost the demand for efficient
treatment and accelerate the demand for drug discovery for medication, and the
technological adaptation in
biotechnology is
contributing to the growth of artificial intelligence (AI) in drug discovery
market. 🔹Increasing Pharmaceutical and
Biotechnology Sectors The rising
government participation in the expansion of pharmaceutical and biotechnology
drives the adaptation of AI, automation, robotics, and other technologies into
its working operations for improving efficiency and productivity, while
reducing manual errors, and drives the expansion of the market. 🔹Awareness of Integrating AI into Drug
Discovery The increasing
awareness regarding integrating AI into drug discovery by the leading
biotechnology and pharmaceutical firms owing to its benefits in different drug
discovery applications such as evaluation of drug-target interactions,
identification of novel targets, analysis of disease mechanisms, enhancing
molecule compounds, optimization and design with the reduce manufacturing costs
and addressing several challenges associated with the drug development boosts
the growth of the market.
Artificial
Intelligence in Drug Discovery Market Report Coverage Report Attributes Key Details Market Size in 2025 USD 6.93 billion Market Size in 2026 USD 7.62 billion Market Size by 2034 USD 16.52 billion Growth Rate (2025–2034) CAGR of 10.10% Base Year 2024 Forecast Period 2025 to 2034 Segments Covered Type, Application, Drug
Type, Offering, Technology, End User, and Region Regions Covered North America, Europe,
Asia-Pacific, Latin America, Middle East & Africa Largest Regional Share
(2024) North America held 56.18%
share Fastest-Growing Region Asia Pacific with strong
double-digit CAGR Leading Application
Segment Oncology Fastest-Growing
Application Infectious Diseases Dominant Type Segment Preclinical and Clinical
Testing Leading Drug Type Small Molecules Fastest-Growing Drug Type Large Molecules
(Biologics) Dominant Technology Machine Learning
(including deep learning) Leading End User Pharmaceutical and
Biotechnology Companies Key Market Drivers Rising chronic diseases,
rapid adoption of AI tools, expanding biotech R&D, growing investment in
precision medicine Key Market Opportunities Generative AI for
molecule design, AI-integrated lab automation, personalized drug development Key Industry Challenges Data quality barriers, lack
of interoperability, regulatory alignment for AI-driven models Strategic Focus Areas Faster target
identification, improved clinical trial design, reduced R&D cost and
cycle time
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Study: How One Biopharma Company Accelerated Drug Discovery Using AI Background A
mid-sized biopharmaceutical company specializing in oncology therapeutics was
struggling with long development timelines and high early-stage R&D costs.
Despite strong scientific capabilities, the organization faced repeated
setbacks during target identification and lead optimization. Each new candidate
required years of laboratory work, and several potential molecules failed due
to unforeseen toxicity or poor binding affinity. Leadership
recognized the need for a more efficient approach and began exploring
artificial intelligence technologies that could support faster, more reliable
decision-making. Challenge The
company identified three persistent obstacles: ➢ Slow, traditional screening processes
that required thousands of experimental iterations before narrowing down viable
candidates. ➢ Limited predictive accuracy in
identifying off-target effects and toxicity risks early in the development
cycle. ➢ Rising R&D expenditures that
exceeded USD 100 million per candidate before entering preclinical testing. These
challenges highlighted a clear need for tools capable of enhancing scientific
insight, reducing uncertainty, and streamlining discovery workflows. AI-Driven
Transformation To
address these issues, the firm implemented an AI-enabled discovery platform
that integrated machine learning, generative modeling, and
automation. The solution brought new capabilities into their pipeline: 1.
AI-Based Target Identification Machine
learning models analyzed multi-omic datasets to uncover novel biological
targets linked to tumor progression. This replaced manual hypothesis-driven
research with data-validated insights. 2.
Generative AI for Molecule Design Generative
models produced entirely new small-molecule structures tailored for specific
drug-like properties such as potency, selectivity, solubility, and synthetic
feasibility. 3.
Predictive Toxicity and Safety Modeling Deep-learning
models evaluated each proposed molecule for toxicity risks, enabling the team
to eliminate high-risk compounds before synthesis. 4.
Automation-Enabled Lab Validation Robotic
systems synthesized and tested the most promising candidates, dramatically
reducing hands-on effort and experimental turnaround time. Results The
implementation of AI produced measurable changes across the company’s discovery
pipeline. Cycle
Time Reduction The
early screening and molecule-design phases, which previously required 18–24
months, were completed in just three months using AI-generated libraries and
predictive filtering. Two optimized candidates progressed to preclinical
readiness within 13 months, cutting development time by more than 60 percent. Cost
Efficiency With
fewer failed experiments and more precise molecular design, the company reduced
early-stage R&D costs by approximately USD 50–60 million per candidate. Higher
Success Probability Predictive
models helped remove over 70 percent of high-risk molecules early in the
process. This significantly improved the quality of the remaining candidates
and increased confidence going into preclinical testing. Improved
Clinical Planning The
organization extended the use of AI into clinical strategy. Machine learning
models were used to predict patient-response patterns and optimize Phase I
trial design. This helped refine cohort selection and reduce the likelihood of
protocol amendments. Impact
on the Organization The
experience reshaped the company’s drug discovery philosophy. Instead of relying
solely on trial-and-error experimentation, teams now began every project with
AI-generated insights. Scientists could focus on higher-value work, and
decision-making became more data-driven and agile. The
transformation aligned closely with global trends highlighted in the press
release, underscoring how AI is reshaping the future of drug
discovery—improving accuracy, accelerating development cycles, and supporting
better therapeutic outcomes. Don’t Miss
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Drug Discovery Market Fuels the Growth of AI in Drug Discovery The
global drug discovery
market,
valued at USD 65.84 billion in 2024 and projected to reach USD 158.74
billion by 2034 at a CAGR of 9.2%, is expanding rapidly due to
rising chronic diseases, increasing demand for novel therapeutics, and
continuous innovation in biologics and precision medicine. As development
pipelines grow more complex and costly, pharma companies face challenges in
speed, accuracy, and R&D efficiency. These structural pressures are
directly accelerating the need for AI-driven tools that can reduce early-stage
failures, improve target identification, and compress development timelines.
The more the drug discovery market scales, the stronger the operational demand
becomes for AI platforms capable of handling complexity at lower cost. This
broader ecosystem—characterized by high-throughput screening, genomics data
expansion, cloud-based laboratories, and aggressive investment in
next-generation platforms—creates the ideal foundation for AI adoption. Market
Synergy Snapshot: Traditional Drug Discovery vs AI-Enabled Drug Discovery Category Drug Discovery Market
(Parent Market) AI in Drug Discovery
Market (Sub-Market) Market Size (2024/2025
baseline) USD 65.84 billion (2024) USD 6.93 billion (2025) Market Size by 2034 USD 158.74 billion USD 16.52 billion CAGR (Forecast Period) 9.2% (2024–2034) 10.10% (2025–2034) Growth Driver Rising chronic diseases,
demand for novel drugs, expansion of biologics Growing need for
efficiency, predictive modeling, automation, generative molecule design Market Pressure Points High R&D cost,
time-consuming early-stage screening, complex clinical pathways Need for high-quality
datasets, model validation, regulatory harmonization Technology Influence Increasing adoption of
robotics, high-throughput screening, genomics, digital labs Relies on ML, deep
learning, generative AI, predictive analytics Role in Pharma R&D Core driver of
therapeutic innovation Efficiency enhancer and
accelerator within the discovery process Relationship Between
Markets Creates demand for
faster, cheaper, more accurate R&D tools Absorbs that demand by
delivering algorithm-driven solutions
The
Complete Study is Immediately Accessible | Download the Sample Pages of this
Report@ https://www.precedenceresearch.com/sample/1464 The
drug discovery market is dominated by key industry leaders whose strong market
share and strategic initiatives shape the future direction of the industry. View
Detailed Insights of Drug Discovery Market 👉 https://www.precedenceresearch.com/drug-discovery-market Artificial
Intelligence (AI) In Drug Discovery Market Regional Outlook: North America
dominated the artificial intelligence (AI) in drug discovery market in 2024.
The growth of the market is attributed to the early adoption of the
technologies by regional countries like the United States and Canada, which are
the major healthcare technology leaders, with the expanding investment in the
development of novel technologies in the pharmaceutical and biotechnology
industry driving the market growth. Additionally, the ongoing research on drug
discovery for different disease treatments boosts the growth of the market in the
region. How Big is
the U.S. Artificial Intelligence (AI) In Drug Discovery Market Size? According to
Precedence Research, The U.S. artificial intelligence (AI) in drug discovery
market size is expected to be worth approximately USD 6.93 billion by 2034, up
from USD 2.86 billion in 2025. In terms of CAGR, the market is projected to
grow at a double-digit CAGR of 10.26% from 2025 to 2034. The United
States maintained its dominance in the artificial intelligence (AI) in
drug discovery market due to emerging and powerful AI startups and greater
government support for the implementation and innovation of the latest
technology. Moreover, the major pharmaceutical brands have invested heavily in
AI platforms to speed up drug production in the United States nowadays. The Complete Study is Now Available
for Immediate Access | Download the Sample Pages of this Report@ https://www.precedenceresearch.com/sample/1875 Asia Pacific
is expected to have the fastest growth in the artificial intelligence (AI) in
drug discovery market during the forecast period. The increasing healthcare
infrastructural development in the economically developing countries in the
region, like China, India, Japan, South Korea, and others, is driving the
advancements in the drug discovery process. The inclination towards smart
technologies like AI and machine learning in biotechnology and pharmaceuticals
for drug development and novel treatment procedures contributed to the growth of
the market across the region. China China is
expected to emerge as a prominent country for artificial intelligence (AI) in
the drug discovery market in the coming years, owing to the rapid acceptance of
artificial intelligence and big data. Furthermore, the major companies in China
have seen under the development of heavy medical databases while using AI to
create personalized drugs and treatment in the country in recent years. ✚ Related Topics You May Find Useful: ➡️ Generative
AI in Drug Discovery Market: How algorithm-driven molecule generation is compressing
R&D timelines and transforming early-stage discovery pipelines ➡️ AI-Driven
Drug Discovery Platforms Market: Why computational platforms are
becoming the core infrastructure for target identification and lead
optimization ➡️ Artificial
Intelligence in Biopharmaceutical Market: How AI is accelerating biologics
development, manufacturing precision, and clinical decision support ➡️ AI
in Pharmaceutical Market: The shift toward automated clinical operations,
predictive analytics, and AI-enabled drug lifecycle management ➡️ Artificial
Intelligence in Precision Medicine Market: How AI models are unlocking deeply
personalized diagnostics, therapy selection, and treatment pathways ➡️ U.S.
Artificial Intelligence in Biotechnology Market: How U.S. biotech companies are
scaling AI to enhance gene editing, protein engineering, and cellular research ➡️ Artificial
Intelligence in Genomics Market: How machine learning is enabling
ultra-fast genome interpretation, variant detection, and disease prediction ➡️ Artificial
Intelligence in Bioinformatics Market: The role of AI in decoding complex
biological datasets and powering next-generation computational biology ➡️ Artificial
Intelligence in Biotechnology Market: Why AI-driven biological modelling
and automation are redefining lab workflows and bioprocess innovation AI in Drug
Discovery Market Segmentation
Insights: Type
Insights The
preclinical and clinical trial portion segment dominated the
artificial intelligence (AI) in drug discovery market with the largest share in
2024. The rising advancements in healthcare, pharmaceuticals, and
biotechnology, with the association of AI, enhance the accuracy and efficiency
of drug development and clinical research functions. AI enhances speed and
accuracy in the clinical trial or testing portions. It provides accuracy in the
hypothesis generation and analysis for understanding the disease and enhanced
drug discovery process, adherence, monitoring, cohort composition, and endpoint
selection. The drug
optimization segment is anticipated to grow rapidly over the forecast period.
Drug optimization is the process of evaluation and discovery of how
therapeutics or medications work on individual patients. The integration of AI
into the drug optimization method improves the efficiency of the process. Drug Type
Insights The small
molecule segment dominated the market with the largest share in 2024. Small
molecule drugs are the type of medicine that is designed to enhance and mimic
the natural substance behavior in the human body. AI can be applied to two
different types such as machines and deep learning, and generative AI. Machine
learning implements accelerated synthesis planning and predictive
retrosynthesis for novel molecular entities. Generative AI implemented for the
made for the libraries of new molecular entities depends on drug-like molecules
and synthetic accessibility scores accessibility. The large
molecule segment is expected to show the fastest growth during the forecast
period. The large molecules are also known as the biologics obtained from
living organisms. The increasing demand for large molecule drugs for the
treatment of several chronic diseases. The implementation of AI into large
molecule development aims to improve the efficiency and productivity of large
molecule drug development. Offering
Insights The software segment dominated the market with the
largest share in 2024. The increasing adaptation of artificial intelligence
software in the pharmaceutical and biotechnology industry for drug development
and cost efficiency in the drug discovery process. Furthermore, the investment
by the major market players in the R&D activities on the novel launch of
software solutions drives the growth of the segment. The service
segment is anticipated to grow rapidly over the forecast period. The increasing
demand for AI-based services by the leading pharmaceutical companies in the
drug discovery and development process is driving the growth of the
segment. Technology
Insights The machine
learning segment dominated the market with the largest share in 2024. Machine
learning technology is one of the major integral parts of artificial
intelligence. The integration of machine learning into drug discovery and
development helps in improving all aspects and applications of the process,
like target discovery, target validation, HIT discovery, HIT to lead, lead
optimization, pre-clinical studies, clinical trials, and post-development
monitoring and pharma vigilance. It improves the decision-making process in
pharmaceutical data. Application
Insights The oncology
segment accounted for the largest artificial intelligence (AI) in drug
discovery market share in 2024. The rising prevalence of cancer in the
worldwide population due to the changing environmental factors, genetics, and
lifestyle boosts the demand for effective treatment and medication processes.
The integration of artificial intelligence into cancer diagnostics aims to
improve the efficiency of the treatment and achieve better patient outcomes.
The AI predicts the chances of getting cancer in the future period with
predictive technology. It helps with cancer treatment, like chemotherapy and
surgeries. The infection
segment is expected to show the fastest growth during the forecast period. The
integration of AI into infectious disease control transforms the diagnostic
process. It offers rapid diagnostics, antibiotic discovery, and addresses
several other challenges associated with infectious disease. End User
Insights The
pharmaceutical and biotechnology companies segment dominated the market with
the largest share in 2024. The rising economic conditions in developing
countries and the demand for efficient healthcare and pharmaceutical
infrastructure are driving the development of effective drug discovery and
treatment procedures. There are a number of leading pharmaceutical and
biotechnology companies adopting AI into their working operations to improve
productivity by reducing the cost of operations and manual errors. The academics
and research segment is expected to show the fastest growth during the forecast
period. The increasing investment in the research and development program in
drug discovery studies in the research and academic institutions, and the
government support for the expansion of the healthcare research and academic
institutes, accelerate the growth of the segment. You can
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441 9344 AI in Drug
Discovery Market Top 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, Variational AI, an organization
behind Enki™, a leading firm in the advanced foundation model for small
molecule drug discovery, completed its oversubscribed USD 5.5 million Seed
extension round. 🔸In January 2025, Innophore and NVIDIA collaborated to
launch the AI-driven drug safety screening platform ‘CavitOmiX’ in January
2025. The platform uses NVIDIA’s computing power and specialties to increase
the silico drug design by protein binding site analysis. 🔸In February 2025, Venture capitalist and LinkedIn
co-founder Reid Hoffman entered healthcare with the launch of their startup
Manas AI. The new startup will work on drug development with the integration of
AI to enhance the drug discovery process. The development is initiated by
aggressive cancer treatment. 🔸In July 2024, Exscientia plc expanded its business
with Amazon Web Services (AWS) to implement the cloud provider’s artificial
intelligence (AI) and machine learning (ML) services in its platform for
end-to-end automation and drug discovery. 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 → Deep Learning →
Supervised Learning →
Reinforcement Learning →
Unsupervised Learning →
Other Machine Learning Technologies 🔹Other Technologies By
Application 🔹Neurology 🔹Infectious Disease 🔹Oncology 🔹Others By End
User 🔹Pharmaceutical and Biotechnology
Companies 🔹Contract Research Organizations 🔹Academics and Research 🔹Others By
Geography 🔹North America →
U.S. →
Canada 🔹Europe →
U.K. →
Germany →
France 🔹Asia Pacific →
China →
India →
Japan →
South Korea →
Rest of the World 🔹Latin America →
Brazil →
Rest of Latin America 🔹Middle East and Africa (MEA) →
GCC →
North Africa →
South Africa →
Rest of the Middle East and Africa Thanks for reading you can also get individual
chapter-wise sections or region-wise report versions such as North America,
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The AI in Drug Discovery Market, valued at USD 6.93 billion in 2025 and
expected to reach USD 16.52 billion by 2034 at a CAGR of 10.10%,
grows as companies shift toward data-rich, automation-centric R&D
processes. As the parent market generates vast biomedical datasets and requires
faster molecule design, AI becomes indispensable, improving predictive
accuracy, enabling generative compound design, and strengthening clinical
strategy. In short, the rapid growth of the drug discovery industry acts as the
core engine driving AI adoption across the entire pharmaceutical value chain.
