Generative AI in the Drug Discovery Market Size to Attain USD 2847.43 Million, Rising at 27.42% CAGR by 2034

The global generative AI in drug discovery market size is calculated at USD 318.55 million in 2025 and is expected to reach around USD 2847.43 million by 2034, growing at a CAGR of 27.42% for the forecasted period.

Ottawa, Oct. 10, 2025 (GLOBE NEWSWIRE) -- The global generative AI in drug discovery market size was valued at USD 250 million in 2024 and is predicted to hit around USD 2847.43 million by 2034, rising at a 27.42% CAGR, a study published by Towards Healthcare a sister firm of Precedence Research.

The growth of the market is driven by the growing demand for new and innovative drug discovery, which is effective and affordable, and this fuels the growth of the market.

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Key Takeaways

North America dominated the generative AI in drug discovery market in 2024 with a market revenue share of 43%.
Asia Pacific is expected to grow at the fastest CAGR during the forecast period.
By application, the hit generation & lead discovery segment captured the largest market revenue of 39% in 2024.
By application, the clinical trial design & optimization segment is expected to be the fastest-growing during the forecast period.
By therapeutic area, the oncology segment dominated the market in 2024 with a revenue share of 45%.
By therapeutic area, the neurological disorders segment is expected to grow at the fastest CAGR during the forecast period.
By technology, the deep learning (DL) segment captured 48% of revenue of the market revenue in 2024.
By technology, the reinforcement learning (RL) segment is expected to grow at the highest CAGR during the forecast period.
By deployment, the cloud-based segment led the market in 2024 with a revenue share of 71% and is expected to be the fastest-growing during the forecast period.
By end-user, the pharmaceutical companies segment captured a revenue share of 50% of the generative AI in drug discovery market in 2024.
By end-user, the biotechnology companies segment is expected to grow at the fastest CAGR during the forecast period.

Market Overview & Potential

Generative AI in drug discovery refers to the use of artificial intelligence models-especially generative models like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer-based architectures design, screen, and optimize novel drug candidates. These AI systems generate molecular structures, predict biological activity, synthesize compound properties, and even suggest formulation pathways with unprecedented speed and accuracy, significantly reducing the drug development cycle and costs.

Market Scope:

Metric	Details
Market Size in 2025	USD 318.55 Million
Projected Market Size in 2034	USD 2847.43 Million
CAGR (2025 - 2034)	27.42	%
Leading Region	North America share by 43%
Market Segmentation	By Application, By Therapeutic Area, By Deployment Mode, By Region
Top Key Players	Insilico Medicine, Exscientia, Atomwise, BenevolentAI, Absci, Cyclica (Recursion), XtalPi, Valo Health, Deep Genomics, Healx

What Is The Growth Potential Responsible For The Growth Of The Generative AI in the Drug Discovery Market?

The growth of the market is driven by the growing demand for cost-effective and faster recovery solutions and faster drug discovery. Key drivers for generative AI in drug discovery are the need for cost-effective drug development, the growing demand for innovative treatments for complex diseases, and the desire to accelerate the traditionally slow and expensive research process. Generative AI addresses these by speeding up discovery, reducing physical screening costs through virtual libraries, optimizing drug candidates for safety and efficacy, and improving decision-making across the pipeline, ultimately leading to faster development of new therapies.

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What Are The Growing Trends Associated With Generative AI in the Drug Discovery Market?

De Novo Drug Design:

Generative AI is used to create novel drug molecules with high therapeutic potential by simulating interactions and predicting behavior.

Target Identification and Validation:

AI helps identify and validate potential drug targets, speeding up the research process.

Clinical Trial Enhancement:

AI optimizes clinical trial designs, identifies suitable patient populations, and monitors data in real-time, improving safety and effectiveness.

Drug Repurposing and Optimization:

AI tools identify new uses for existing drugs and help optimize drug compounds for better performance.

Predictive Modeling:

Algorithms are used to predict drug interactions and toxicity, leading to safer and more effective medications.

What Are The Challenges In The Growth Of Generative AI In the Drug Discovery Market?

Challenges facing the generative AI market in drug discovery include limited access to high-quality, well-annotated data, high computational and infrastructure costs, risks of misleading or incorrect outputs, concerns about model accuracy and generalizability, data privacy and security issues, the reproducibility crisis, and the early stage of deep generative models (DGMs) in real-world applications.

Regional Analysis

How Did North America Dominate The Generative AI in the Drug Discovery Market In 2024?

North America dominated the generative AI in drug discovery market in 2024 with a market revenue share of 43%. North America dominates the generative AI in drug discovery market due to robust pharmaceutical R&D ecosystems, extensive AI investments, and strong cloud infrastructure. U.S.-based firms such as Atomwise, Insilico Medicine, and Recursion Pharmaceuticals lead innovation through collaborations with academic centers and big pharma. The region benefits from mature data governance frameworks, favorable FDA guidance, and increasing adoption of AI-integrated clinical development strategies.

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What Made The Asia Pacific Significantly Grow In The Generative AI In Drug Discovery Market In 2024?

Asia Pacific is expected to grow at the fastest CAGR during the forecast period. Asia Pacific is emerging as a dynamic growth region, driven by AI-led pharmaceutical innovation across China, Japan, and India. The region’s expanding biotech sector and government-backed AI initiatives support rapid technology adoption. Asian drug developers increasingly apply generative AI for local disease modeling, cost-efficient molecule design, and accelerated drug development, positioning the region as a strategic hub for AI-driven biopharma research.

Segmental Insights

By Application,

The hit generation & lead discovery segment captured the largest market revenue of 39% in 2024. Generative AI is transforming hit generation and lead discovery by designing novel molecules with optimal drug-like properties in a fraction of the traditional time. Using deep neural networks and molecular simulations, AI models identify high-potential compounds, optimize ADMET parameters, and streamline early-stage R&D workflows, substantially lowering discovery costs and improving success rates across pharmaceutical pipelines.

The clinical trial design & optimization segment is expected to be the fastest-growing during the forecast period. AI-driven platforms enhance clinical trial design by predicting patient responses, identifying biomarkers, and optimizing cohort selection. These generative systems enable scenario modeling for dosage and safety assessments, reducing attrition rates and accelerating regulatory approval timelines. They are increasingly integrated into clinical data ecosystems to support adaptive trial designs, ensuring more efficient and cost-effective drug development.

By Therapeutic Area,

The oncology segment dominated the market in 2024 with a revenue share of 45%. In oncology, generative AI accelerates drug discovery by identifying new molecular targets and generating compounds tailored to tumor genetics. The technology enables high-precision modeling of cancer pathways, enhancing targeted therapy outcomes. Pharmaceutical firms use AI to optimize cancer drug efficacy, reduce toxicity, and personalize treatment regimens, particularly in breast, lung, and hematologic malignancies.

The neurological disorders segment is expected to grow at the fastest CAGR during the forecast period. Generative AI applications in neurological disorders focus on developing therapies for Alzheimer’s, Parkinson’s, and other CNS diseases. AI models analyze complex neurobiological data, predict blood-brain barrier permeability, and design CNS-active compounds with improved selectivity. These tools significantly reduce trial-and-error stages, promoting faster identification of disease-modifying molecules for neurodegenerative and neuropsychiatric conditions.

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By Technology,

The deep learning (DL) segment captured 48% of revenue of the market revenue in 2024. Deep learning underpins generative AI in drug discovery, leveraging multi-layered neural networks to extract patterns from massive biological and chemical datasets. These models enable de novo molecule generation, target prediction, and pharmacokinetic optimization. Their ability to learn complex relationships accelerates hit-to-lead transitions, improves candidate quality, and drives breakthroughs in precision medicine.

The reinforcement learning (RL) segment is expected to grow at the highest CAGR during the forecast period. Reinforcement learning employs feedback-driven molecular optimization, allowing AI to iteratively refine compounds based on reward functions. It supports multi-objective drug design balancing potency, safety, and selectivity while enhancing computational efficiency. The approach is increasingly adopted by AI-driven biotech companies to explore large chemical spaces dynamically and identify high-value drug candidates faster than traditional methods.

By Deployment,

The cloud-based segment led the market in 2024 with a revenue share of 71% and is expected to be the fastest-growing during the forecast period. Cloud-based generative AI platforms offer scalable computing resources, secure collaboration, and seamless data integration for drug discovery teams. These platforms enable global R&D networks to share molecular data, train large AI models, and simulate drug behavior efficiently. Cloud deployment reduces infrastructure costs, supports regulatory compliance, and enhances accessibility for both established pharmaceutical firms and startups.

By End-User,

The pharmaceutical companies segment captured a revenue share of 50% of the generative AI in drug discovery market in 2024. Pharmaceutical companies are leveraging generative AI to enhance pipeline productivity, accelerate molecule screening, and reduce clinical trial risks. The technology aids in predicting target interactions, optimizing formulations, and repurposing existing drugs. Major global pharma players are integrating AI-first discovery platforms to strengthen innovation capacity and achieve faster go-to-market timelines.

The biotechnology companies segment is expected to grow at the fastest CAGR during the forecast period. Biotechnology firms are adopting generative AI for agile molecule discovery and design. Smaller biotechs use AI models to discover novel molecular scaffolds, simulate protein-ligand interactions, and attract partnerships with large pharma. The integration of AI accelerates experimental validation and enables data-driven innovation across niche therapeutic areas like rare diseases and immunotherapies.

Browse More Insights of Towards Healthcare:

The global antibody discovery market was valued at USD 8.31 billion in 2024 and is expected to reach USD 9.1 billion in 2025. Forecasts indicate that the market will grow at a CAGR of 9.54%, reaching approximately USD 20.71 billion by 2034.

The drug discovery SaaS platforms market is witnessing rapid global adoption, with revenues projected to rise significantly over the period from 2025 to 2034.

Meanwhile, the drug discovery as a service (DDaaS) market was valued at USD 21.3 billion in 2024 and grew to USD 24.32 billion in 2025. It is expected to expand further at a CAGR of 14.17%, reaching around USD 79.82 billion by 2034.

The machine learning in drug discovery market is also experiencing substantial growth, with projections pointing toward a considerable increase in revenue by the end of the forecast period between 2025 and 2034.

Similarly, the robotics in drug discovery market is poised for strong growth from 2024 to 2034, fueled by advancements in automation, artificial intelligence, and high-throughput screening technologies.

The oncology drug discovery market is set to expand significantly during the same period, driven by innovations in precision medicine, AI-enabled drug development, and an increasing pipeline of targeted therapies.

The multiomics in drug discovery market is also showing notable growth, with revenues expected to rise steadily over the forecast period from 2025 to 2034.

The drug discovery platforms market was valued at USD 186.24 million in 2024 and reached USD 211.26 million in 2025. It is projected to grow at a CAGR of 13.44%, reaching approximately USD 635.45 million by 2034.

Recent Developments

In March 2025, at its annual event, The Check Up, Google provided an update on some health-related R&D topics, including a new set of artificial intelligence (AI) models designed to aid in drug discovery.
In November 2024, TLV Partners is the lead investor in Converge Bio's $5.5 million initial investment round. Using large language models (LLMs), Converge Bio is a generative AI center for biotech and pharmaceutical companies that enables faster drug discovery and development.

Key Players List

Insilico Medicine 
Exscientia 
Atomwise 
BenevolentAI
Absci
Cyclica (Recursion)
XtalPi 
Valo Health 
Deep Genomics
Healx

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Segments Covered in The Report

By Application

Hit Generation & Lead Discovery
Clinical Trial Design & Optimization
Target Identification & Validation
Lead Optimization
Preclinical Testing

 By Therapeutic Area

Oncology
Neurological Disorders
Cardiovascular Diseases
Infectious Diseases
Metabolic Diseases
Others (Dermatology, Rare Diseases, etc.)
Shape, Picture By Technology
Deep Learning (DL)
Reinforcement Learning (RL)
Machine Learning (ML)
Natural Language Processing (NLP)
Others (Hybrid models, Quantum AI, etc.)

By Deployment Mode 

Cloud-Based
On-Premises
Shape, Picture

By End User 

Pharmaceutical Companies
Biotechnology Companies
Contract Research Organizations (CROs)
Academic & Research Institutions

By Region

North America
- U.S.
- Canada
Asia Pacific
- China
- Japan
- India
- South Korea
- Thailand
Europe
- Germany
- UK
- France
- Italy
- Spain
- Sweden
- Denmark
- Norway
Latin America
- Brazil
- Mexico
- Argentina
Middle East and Africa (MEA)
- South Africa
- UAE
- Saudi Arabia
- Kuwait

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Towards Healthcare is a leading global provider of technological solutions, clinical research services, and advanced analytics, with a strong emphasis on life science research. Dedicated to advancing innovation in the life sciences sector, we build strategic partnerships that generate actionable insights and transformative breakthroughs. As a global strategy consulting firm, we empower life science leaders to gain a competitive edge, drive research excellence, and accelerate sustainable growth.

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