IMARC Group, a leading market research company, has recently released a report titled “AI in Drug Discovery Market Report by Offering (Software, Services), Application (Preclinical Testing, Drug Optimization and Repurposing, Target Identification, Candidate Screening, and Others), Therapeutic Area (Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases, and Others), End User (Pharmaceutical and Biotechnology Companies, Contract Research Organizations (CROs), Research Centers and Academic Institutes), and Region 2025-2033”. The study provides a detailed analysis of the industry, including the global AI in drug discovery market share, trends, size, and industry growth forecast. The report also includes competitor and regional analysis and highlights the latest advancements in the market.
The global AI in drug discovery market size reached USD 1.8 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 14.0 Billion by 2033, exhibiting a growth rate (CAGR) of 23.17% during 2025-2033.
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Industry Trends and Drivers:
· Expanding data availability
The ongoing advancements in biotechnology and genomics are significantly shaping the landscape of data in biological and chemical research, urging researchers to delve into molecular structures, protein interactions, genetic mutations, and complex disease pathways. As the scope of available data expands, there is an increasing need for advanced analytical approaches.
Moreover, AI has emerged as an essential tool in this regard, excelling not only in processing and interpreting intricate datasets but also in identifying valuable insights that might otherwise be missed. Consequently, AI’s capability to reveal hidden patterns, relationships, and irregularities enhances precision in drug discovery, thereby expediting the identification of promising therapeutic candidates is impelling the market growth.
· Enhanced predictive capabilities
AI algorithms, particularly in machine learning (ML) and deep learning, are transforming drug discovery with their predictive capabilities. Trained on extensive datasets, these algorithms can identify promising drug candidates, estimate their effectiveness, and foresee potential side effects. By analyzing historical data from past successes and failures, AI models produce valuable hypotheses and predictive insights that help researchers focus on the most promising compounds faster. This ability reduces reliance on trial and error, increasing efficiency in drug discovery and improving the likelihood of successful outcomes.
Additionally, AI's analytical power to identify viable therapeutic candidates has significantly improved and become more precise, which is further contributing to its increasing market demand.
· Cost and time efficiency
Traditional drug discovery demands extensive time and resources, often facing high failure rates across multiple experimental stages. AI technologies, however, offer a powerful alternative by expediting timelines and reducing costs within drug development. Through virtual screening, compound optimization, and toxicity prediction, AI enables researchers to identify and focus on the most promising compounds early on. This approach reduces dependency on lengthy lab testing and minimizes resources spent on less viable options.
Additionally, with AI’s support companies can strategically reallocate resources and streamline operations, further propelling the market forward.
AI In Drug Discovery Market Report Segmentation:
Breakup By Offering:
· Software
· Services
Services dominate the market, fueled by the increasing need for AI applications to tackle the complexities of drug development and facilitate precision medicine.
Breakup By Application:
· Preclinical Testing
· Drug Optimization and Repurposing
· Target Identification
· Candidate Screening
· Others
Drug optimization and repurposing hold the largest market share, driven by AI's ability to speed up preclinical screening and candidate selection, significantly lowering costs and enhancing efficiency across drug development phases.
Breakup By Therapeutic Area:
· Oncology
· Neurodegenerative Diseases
· Cardiovascular Diseases
· Metabolic Diseases
· Others
Oncology is the dominant therapeutic area within the AI-driven drug discovery market, owing to AI’s potential to reveal intricate disease mechanisms and pinpoint specific therapeutic targets.
Breakup By End User:
· Pharmaceutical and Biotechnology Companies
· Contract Research Organizations (CROs)
· Research Centers and Academic Institutes
Pharmaceutical and biotechnology companies hold the largest market share, utilizing AI to streamline their drug development pipelines and boost innovation.
Breakup By Region:
· North America
· Asia Pacific
· Europe
· Latin America
· Middle East and Africa
North America leads the AI-driven drug discovery market, supported by a robust pharmaceutical and biotech landscape and high levels of investment in AI research.
Top AI In Drug Discovery Market Leaders:
The AI in drug discovery market research report outlines a detailed analysis of the competitive landscape, offering in-depth profiles of major companies.
Some of the key players in the market are:
· Aria Pharmaceuticals Inc.
· Atomwise Inc.
· Benevolent AI
· BioSymetrics Inc
· BPGbio Inc
· Deep Genomics
· Envisagenics
· Euretos
· Evaxion Biotech A/S
· Exscientia
· Insilico Medicine
· NVIDIA Corporation
· Okwin Inc
· XtalPi Inc
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· Market Performance (2018-2023)
· Market Outlook (2024-2032)
· Market Trends
· Market Drivers and Success Factors
· Impact of COVID-19
· Value Chain Analysis
If you need specific information that is not currently within the scope of the report, we will provide it to you as a part of the customization.
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