Report Overview

In 2023, the Global Artificial Intelligence in Drug Discovery Market was valued at USD 1.2 Billion. Between 2024 and 2033, this market is estimated to register the highest CAGR of 27.5%. It is expected to reach USD 13.6 Billion by 2033.

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Key Takeaways 

The Global Artificial Intelligence in Drug Discovery Market was valued at USD 1.2 billion in 2023 and is projected to grow at a CAGR of 27.5%, reaching USD 13.6 billion by 2033.

Software leads the market, capturing 65.4% of the AI in drug discovery market share, highlighting its integral role in advancing pharmaceutical research and development.

Machine learning dominates the technology segment with a 52.7% market share, leveraging its capabilities to enhance efficiency and accuracy in drug discovery processes.

Neurodegenerative diseases accounted for a significant 43.8% market share in 2023, driving AI application towards addressing complex health challenges.

Pharmaceutical and biotechnological companies hold a combined 68.4% market share in AI-driven drug discovery, underscoring their leadership in adopting innovative technologies.

North America emerged as the dominant region in the global AI in drug discovery market, contributing 60.1% of the total revenue share, driven by extensive research investments and technological advancements.

The pharmaceutical industry has witnessed substantial growth in AI adoption for drug discovery, facilitating tasks such as lead compound identification, target validation, and drug structure optimization.

Key applications of AI in drug discovery include polypharmacology, chemical synthesis, drug repurposing, and drug screening, supporting the development of treatments for emerging diseases and healthcare challenges.

Market Key Segments

Component

• Software
• Service

Technology

• Machine Learning
• Deep Learning
• Other Technologies

Application

• Neurodegenerative Diseases
• Cardiovascular Diseases
• Metabolic Diseases
• Immuno-Oncology
• Other Applications

End-User

• Pharmaceutical and Biotechnological Companies
• Academic and Research Institutes
• Other End-Users

Key Regions

• North America (The US, Canada, Mexico)
• Western Europe (Germany, France, The UK, Spain, Italy, Portugal, Ireland, Austria, Switzerland, Benelux, Nordic, Rest of Western Europe)
• Eastern Europe (Russia, Poland, The Czech Republic, Greece, Rest of Eastern Europe)
• APAC (China, Japan, South Korea, India, Australia & New Zealand, Indonesia, Malaysia, Philippines, Singapore, Thailand, Vietnam, Rest of APAC)
• Latin America (Brazil, Colombia, Chile, Argentina, Costa Rica, Rest of Latin America)
• Middle East & Africa (Algeria, Egypt, Israel, Kuwait, Nigeria, Saudi Arabia, South Africa, Turkey, United Arab Emirates, Rest of MEA)

Market Key Players

• NVIDIA CORPORATION
• Microsoft Corporation
• Cloud Pharmaceuticals
• TOMWISE INC.
• AI
• Schrödinger
• BioSymetrics
• Cyclica Inc.
• IBM Watson
• Benevolent AI
• Other Key Players

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Drivers:

Demand for Efficiency: The increasing need for faster and cost-effective drug discovery processes drives AI adoption.
Rise in Complex Diseases: The growing prevalence of chronic and rare diseases fuels the demand for advanced AI-driven solutions.

Opportunities:

Personalized Medicine Growth: AI facilitates personalized treatments based on genetic profiles, expanding healthcare possibilities.
Emerging Markets Expansion: Untapped potential in regions like Asia-Pacific offers growth opportunities with improving healthcare infrastructure.

Trends:

Machine Learning Advancements: Continuous improvements in machine learning algorithms enhance AI’s predictive capabilities in drug discovery.
Big Data Integration: Utilization of large datasets accelerates drug development and enhances decision-making processes.

Restraints:

Regulatory Challenges: Complex regulatory frameworks and ethical considerations pose barriers to AI adoption in drug discovery.
Implementation Costs: High initial investments in AI infrastructure and expertise limit adoption, particularly for smaller pharmaceutical firms.

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