PUBLISHER: QYResearch | PRODUCT CODE: 1866859
PUBLISHER: QYResearch | PRODUCT CODE: 1866859
The global market for Artificial Intelligence in Drug Discovery was estimated to be worth US$ 2281 million in 2024 and is forecast to a readjusted size of US$ 14511 million by 2031 with a CAGR of 30.7% during the forecast period 2025-2031.
Artificial intelligence in medicine is the use of machine learning models to search medical data and uncover insights to help improve health outcomes and patient experiences. Thanks to recent advances in computer science and informatics, artificial intelligence (AI) is quickly becoming an integral part of modern healthcare. AI algorithms and other applications powered by AI are being used to support medical professionals in clinical settings and in ongoing research. Currently, the most common roles for AI in medical settings are clinical decision support and imaging analysis. Clinical decision support tools help providers make decisions about treatments, medications, mental health and other patient needs by providing them with quick access to information or research that's relevant to their patient. Drug discovery is often one of the longest and most costly parts of drug development. AI could help reduce the costs of developing new medicines in primarily two ways: creating better drug designs and finding promising new drug combinations. With AI, many of the big data challenges facing the life sciences industry could be overcome.
The market for artificial intelligence (AI) in drug discovery is driven by the urgent need to accelerate and reduce the cost of developing new therapeutics, as traditional drug discovery is often slow, expensive, and prone to high failure rates. AI enables rapid identification of drug candidates, predictive modeling of drug-target interactions, and optimization of clinical trial design, significantly shortening development timelines. The explosion of biomedical data, including genomics, proteomics, and real-world clinical datasets, provides a rich foundation for AI algorithms to uncover novel insights. Additionally, rising investment from pharmaceutical companies, biotech firms, and venture capital in AI-driven platforms-combined with advances in deep learning, natural language processing, and generative models-is propelling adoption. Regulatory agencies' increasing openness to AI-assisted drug development workflows also supports the growth of this transformative sector.
This report aims to provide a comprehensive presentation of the global market for Artificial Intelligence in Drug Discovery, focusing on the total sales revenue, key companies market share and ranking, together with an analysis of Artificial Intelligence in Drug Discovery by region & country, by Type, and by Application.
The Artificial Intelligence in Drug Discovery market size, estimations, and forecasts are provided in terms of sales revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. With both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Artificial Intelligence in Drug Discovery.
Market Segmentation
By Company
Segment by Type
Segment by Application
By Region
Chapter Outline
Chapter 1: Introduces the report scope of the report, global total market size. This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 2: Detailed analysis of Artificial Intelligence in Drug Discovery company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 3: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 4: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 5: Revenue of Artificial Intelligence in Drug Discovery in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.
Chapter 6: Revenue of Artificial Intelligence in Drug Discovery in country level. It provides sigmate data by Type, and by Application for each country/region.
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.
Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 9: Conclusion.