USD 850 million
Report ID: SQMIG35J2061 | Region: Global | Published Date: October, 2023 | Pages: 157 | Tables: 59 | Figures: 75
AI in Drug Discovery Market size was valued at USD 850 million in 2021 and is poised to grow from USD 1,101.6 million in 2022 to USD 4,982.8 million by 2030, growing at a CAGR of 29.6% during the forecast period (2023-2030).
The global AI in drug discovery market is a rapidly evolving and transformative field that combines the power of artificial intelligence (AI) and machine learning (ML) with traditional pharmaceutical research and development processes. AI is revolutionizing the drug discovery process by offering innovative solutions to accelerate the discovery and development of new drugs, optimize clinical trials, and improve patient outcomes. AI in drug discovery leverages computational algorithms and advanced data analytics to analyze massive amounts of biological and chemical data. It enables researchers to identify potential drug targets, design novel molecules, predict their properties, and assess their safety and efficacy. By utilizing AI, pharmaceutical companies and research institutions can streamline the drug discovery process, reduce costs, and increase the success rate of bringing new drugs to market. The global AI in drug discovery market is witnessing significant growth and investment from pharmaceutical companies, technology firms, and venture capitalists. The market is driven by factors such as the increasing demand for innovative and effective drugs, the growing availability of big data in the life sciences industry, and advancements in AI and ML technologies. Furthermore, regulatory agencies are increasingly recognizing the potential of AI in drug discovery and are actively working to establish guidelines and frameworks for its implementation. In conclusion, the global AI in drug discovery market represents a transformative and promising approach to revolutionize the pharmaceutical industry. By harnessing the power of AI and advanced analytics, researchers can expedite the drug discovery process, leading to the development of more efficient and personalized therapies that can positively impact patient outcomes. The continued advancements and adoption of AI in drug discovery are expected to reshape the future of medicine and healthcare.
Global Market Size
USD 850 million
Pharmaceutical and Biotechnology Companies
Pharmaceutical and Biotechnology Companies
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Global AI in Drug Discovery Market is segmented type, end-user, and region. Based on Technology, the market can be segmented into small molecules and large molecules. Based on end-user, the market is segmented into Pharmaceutical and Biotechnology Companies and Academics and Research institutes. Based on region, the market is segmented into North America, Europe, Asia Pacific, Middle East and Africa, and Latin America.
AI in Drug Discovery Market Analysis by Type
By type, the market can be segmented into small molecules and large molecules. Small molecule segment dominated the market. Small molecules are typically low molecular weight compounds that can easily penetrate cell membranes and interact with specific target proteins. They are widely used in drug discovery due to their favorable pharmacokinetic properties, ease of synthesis, and established regulatory pathways for approval. The application of AI in small molecule drug discovery involves virtual screening, lead optimization, and molecular property prediction. AI algorithms can efficiently analyze large datasets to identify potential small molecule drug candidates, optimize their properties, and predict their efficacy and safety. The dominance of the small molecules segment can be attributed to the extensive research and development efforts invested in this area and the well-established infrastructure for small molecule drug discovery.
While the large molecules segment is experiencing significant growth and is the fastest-growing segment. Large molecules, also known as biologics, include therapeutic proteins, antibodies, peptides, and nucleic acids. These molecules have complex structures and are typically produced through biotechnological processes. The application of AI in large molecule drug discovery involves protein structure prediction, antibody design, and biologics optimization. AI algorithms can analyze vast biological and genomic data to identify protein targets, design novel biologics, and optimize their properties for improved therapeutic effects. The growing adoption of large molecule drugs in various therapeutic areas, such as oncology, immunology, and rare diseases, is driving the demand for AI-enabled approaches to enhance the discovery and development of large molecule therapeutics. Factors such as advancements in biotechnology, increased understanding of disease mechanisms, and regulatory support for large molecule drugs contribute to the rapid growth of this segment.
AI in Drug Discovery Market Analysis by End-User
By end-user, the market can be segmented into Pharmaceutical and Biotechnology Companies and Academics and Research institutes. These companies have significant resources and expertise to invest in AI technologies for drug discovery. They are driven by the need to improve the efficiency and success rates of their drug development processes. By leveraging AI capabilities, pharmaceutical and biotechnology companies can analyze vast amounts of data, identify potential drug targets, and design optimized molecules. AI algorithms help in predicting the properties and safety profiles of these molecules, enabling faster and more targeted drug development. These companies also have the advantage of existing infrastructure and established collaborations with research institutions and regulatory bodies, providing them with a competitive edge in implementing AI solutions for drug discovery.
Academic and Research institutes have emerged as the fastest-growing segment in the AI in Drug Discovery market. Academic institutions and research organizations are increasingly recognizing the potential of AI in accelerating drug discovery and are actively exploring its applications. These entities are at the forefront of cutting-edge research and possess deep expertise in data analytics, machine learning, and computational biology. They play a crucial role in developing and refining AI algorithms and models for drug discovery. The academic and research segment is characterized by a high level of collaboration and knowledge sharing, which further fuels innovation. The increasing availability of research grants, government funding, and partnerships with pharmaceutical companies contributes to the rapid growth of this segment. Furthermore, academic institutions often have access to diverse and comprehensive datasets, making them valuable contributors to the AI in drug discovery ecosystem.
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North America dominated the global AI in Drug Discovery market. The region benefits from advanced healthcare infrastructure, strong research and development capabilities, and a high adoption rate of AI technologies in the pharmaceutical industry. The presence of key market players, technological advancements, and substantial investments contribute to the region's dominance. Additionally, favorable government initiatives and collaborations between academia, industry, and research institutions further drive the growth of AI in drug discovery in North America.
Asia Pacific is expected to be the fastest growing region in the global AI in Drug Discovery market. The Asia Pacific region is characterized by a rising population, increasing prevalence of chronic diseases, and a growing demand for innovative therapies. The region also boasts a strong base of skilled professionals and is investing heavily in AI research and development. Factors such as government support, favorable regulations, and increasing investments in healthcare infrastructure contribute to the rapid growth of AI in drug discovery in the Asia Pacific region.
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AI in Drug Discovery Market Drivers
Rise in incidence of chronic diseases propels need for AI in drug discovery
AI in Drug Discovery Market Restraints
High cost associated with technology and technical limitations
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The competitive landscape for the global artificial intelligence (AI) in drug discovery industry gives information by competitor. Included information includes a company overview, financials, revenue generated, market potential, R&D investment, new market initiatives, production sites, and facilities, as well as company strengths and weaknesses. It also includes information on product launches, product approval pipelines, product patents, product width and breath, application dominance, and the technology lifeline curve. The company's focus on the global Artificial Intelligence (AI) in drug development market is the only informational item discussed above.
AI in Drug Discovery Market Top Player’s Company Profiles
AI in Drug Discovery Market Recent Developments
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According to our global AI in drug discovery market analysis, the market is revolutionizing the pharmaceutical industry by combining artificial intelligence and machine learning with traditional research and development processes. It leverages computational algorithms and data analytics to analyze vast amounts of biological and chemical data, accelerating the discovery and development of new drugs. AI in drug discovery enables researchers to identify drug targets, design molecules, predict properties, and assess safety and efficacy. It handles complex biological data and uncovers patterns and correlations that lead to the discovery of new drug targets. The market is driven by the demand for innovative drugs, availability of big data, and advancements in AI technology. However, challenges such as ethics, data privacy, regulatory compliance, and collaboration between experts need to be addressed. Implementing AI in drug discovery has the potential to expedite the process, develop personalized therapies, and positively impact patient outcomes. The market growth and investment indicate its transformative potential in reshaping the future of medicine.
|Market size value in Drug||USD 850 million|
|Market size value in 2030||USD 4,982.8 million|
|Forecast Unit (Value)||USD Million|
|Regions covered||North America (US, Canada), Europe (Germany, France, United Kingdom, Italy, Spain, Rest of Europe), Asia Pacific (China, India, Japan, Rest of Asia-Pacific), Latin America (Brazil, Rest of Latin America), Middle East & Africa (South Africa, GCC Countries, Rest of MEA)|
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Parent Market Analysis
KEY MARKET INSIGHTS
MARKET DYNAMICS & OUTLOOK
Market Size by Region
KEY COMPANY PROFILES
For the Global AI in Drug Discovery Market, our research methodology involved a mixture of primary and secondary data sources. Key steps involved in the research process are listed below:
1. Information Procurement: This stage involved the procurement of Market data or related information via primary and secondary sources. The various secondary sources used included various company websites, annual reports, trade databases, and paid databases such as Hoover's, Bloomberg Business, Factiva, and Avention. Our team did 45 primary interactions Globally which included several stakeholders such as manufacturers, customers, key opinion leaders, etc. Overall, information procurement was one of the most extensive stages in our research process.
2. Information Analysis: This step involved triangulation of data through bottom-up and top-down approaches to estimate and validate the total size and future estimate of the Global AI in Drug Discovery Market.
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