Computer-Aided Drug Discovery Market - Forecasts from 2025 to 2030

The computer-aided drug discovery market is projected to grow at a CAGR of 11.59% over the forecast period, increasing from US$5.955 billion in 2025 to US$10.306 billion by 2030.
Drug discovery is a lengthy and complex process, but digital transformation is enhancing efficiency and effectiveness in the pharmaceutical industry. The integration of computer-aided drug discovery, automation, and digitization has become essential for improving quality, reducing costs, and shortening timelines. As resource constraints and changing scenarios arise, automation and digitization are key drivers of business growth.The application of quantum mechanics in computer-aided drug discovery has enabled highly accurate in-silico modeling of biological and chemical systems, facilitating the identification of novel drug candidates. The rising incidence of chronic diseases has intensified the need for rapid drug development, further boosting the growth of the computer-aided drug discovery market. According to the National Center for Health Statistics, it is projected that there will be 1,958,310 new cancer cases and 609,820 cancer deaths in the United States in 2023, underscoring the urgency of addressing these health challenges.
Drivers of the Computer-Aided Drug Discovery Market:

Expanding Use of Artificial Intelligence in Drug Discovery: The complexity and time-consuming nature of new drug discovery necessitate advanced solutions. Identifying suitable compounds that can effectively bind to specific disease-related targets requires screening vast numbers of molecules. AI is transforming this process by enabling the discovery of potential compounds through technologies such as knowledge graphs, in-silico target identification, and target ranking, which expedite treatment development with greater precision.
For instance, in December 2023, Merck launched AIDDISON, a groundbreaking drug discovery software platform that integrates generative AI, machine learning, and computer-aided drug design. This software bridges the gap between virtual molecule design and real-world manufacturability through Synthia™ retrosynthesis API integration. AIDDISON analyzes over 60 billion possibilities based on key properties essential for successful drugs—such as non-toxicity, solubility, and stability—drawing on more than two decades of validated datasets from pharmaceutical R&D.AI and machine learning models like AIDDISON significantly enhance the success rate of new patient therapies while potentially reducing costs associated with drug discovery by up to 70%.
Geographical Trends Shaping the Computer-Aided Drug Discovery Market:

Significant Growth in North America: The computer-aided drug discovery market is poised for substantial growth in the United States due to several factors, including a rising prevalence of mental health disorders, advancements in AI technologies, and increasing acceptance of telehealth solutions. The demand for effective treatment options for mental health issues such as anxiety, depression, and PTSD has surged since the COVID-19 pandemic exacerbated these challenges.
As traditional healthcare systems struggle to keep up with demand, AI technologies are emerging as viable solutions to provide scalable and accessible mental health care. AI-driven platforms can analyze large datasets to offer personalized therapy and real-time emotional support.The U.S. government has recognized AI's potential in healthcare and has initiated programs to promote its development. For example, the American AI Initiative aims to position the U.S. as a leader in artificial intelligence by establishing guidelines for its application across various sectors. Additionally, favorable funding opportunities for mental health technology have attracted investments from both public and private sectors.The combination of a robust healthcare IT infrastructure and growing public awareness about mental health issues creates an environment conducive to rapid expansion of AI solutions.In summary, the computer-aided drug discovery market is set for significant growth driven by increased adoption of AI applications in drug discovery processes, rising global demand for effective treatments for chronic diseases, supportive governmental initiatives promoting innovation in healthcare technologies, and favorable geographical trends—especially within North America—that enhance this expanding market landscape.

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Computer-Aided Drug Discovery Market has been segmented as following:

By Type

Structure-Based Drug Design
Ligand-Based Drug Design
Sequence-Based Approaches

By Therapeutic Area

Oncology
Neurology
Cardiovascular Disease
Respiratory Disease
Others

By End User

Pharmaceutical Companies
Biotechnology Companies
Research Laboratories

By Geography

North America
USA
Canada
Mexico
South America
Brazil
Argentina
Rest of South America
Europe
United Kingdom
Germany
France
Italy
Spain
Rest of Europe
Middle East and Africa
Saudi Arabia
UAE
Rest of the Middle East and Africa
Asia Pacific
China
India
Japan
South Korea
Taiwan
Thailand
Indonesia
Rest of Asia-Pacific