The report on the global AI in drug discovery market provides qualitative and quantitative analysis for the period from 2021-2030. AI in drug discovery market was valued at USD 1360.81 million in 2022 and expected to reach USD 9107.49 million in 2030, with a CAGR of 23.54% during the forecast period 2023-2030. The study on AI in drug discovery market covers the analysis of the leading geographies such as North America, Europe, Asia Pacific, and RoW for the period of 2021-2030.
Artificial Intelligence (AI) is revolutionizing the drug discovery market by significantly accelerating and enhancing the drug development process. AI in drug discovery involves the utilization of machine learning algorithms, data analysis, and computational techniques to streamline various stages of drug development, from target identification and validation to compound screening and clinical trial optimization. Additionally, the major driving factor for the adoption of AI in drug discovery is the overwhelming amount of biological and chemical data generated in the field. The explosion of biological data from genomics, proteomics, and other -omics technologies, coupled with the vast chemical compound libraries, makes it nearly impossible for researchers to manually process and analyze this data efficiently. AI systems excel at handling these large datasets, identifying meaningful patterns, and predicting potential drug candidates. This data-driven approach not only saves time and resources but also increases the likelihood of identifying novel drug candidates with higher efficacy and safety profiles, ultimately benefiting patients and the pharmaceutical industry as a whole. As AI continues to evolve and mature, it is poised to play an increasingly pivotal role in drug discovery and development.
The oncology sector stands out as the most rapidly expanding segment within the Artificial Intelligence (AI) in drug discovery market. This remarkable growth can be attributed to the pressing need for innovative and personalized treatments in cancer research and therapy. AI technologies, such as machine learning and data analytics, are being harnessed to analyze vast datasets, identify potential drug candidates, and optimize drug development processes in oncology. AI expedites the development of anti-cancer medications in the field of oncology drug discovery. Given the escalating cancer rates, this sector is poised for substantial expansion. As per the 2022 report from the American Cancer Society, cancer ranks as the second most prevalent cause of mortality in the United States. Projections indicate that by the conclusion of 2022, there will be over 609,360 fatalities and an estimated 1.9 million new cancer diagnoses. This underscores the pressing demand for AI-driven advancements in oncology to address this significant public health challenge. The ability of AI to accelerate the identification of novel cancer therapies and tailor treatments to individual patients is driving substantial interest and investment, making oncology the focal point of AI-driven drug discovery advancements.
North America is poised to lead the market due to several key factors, including the widespread adoption of AI technologies in the pharmaceutical sector, a substantial patient population, a higher incidence of chronic and infectious diseases, advanced healthcare infrastructure, and extensive ongoing clinical research and trials in AI-driven drug discovery within the region. The United States, in particular, stands out with a notable prevalence of metabolic and lifestyle-related diseases. For instance, according to the Centers for Disease Control data for 2022, over 37.3 million adults in the United States are grappling with diabetes, and as reported by the National Institutes of Health, 1 in 7 adults in the United States is affected by chronic kidney disease. Due to the rising adoption of AI in drug discovery across academic, research, and healthcare institutions, it is anticipated that companies and their significant advancements play a pivotal role in driving growth within the North American market.
1. Key Opinion Leaders
2. Internal and External subject matter experts
3. Professionals and participants from the industry
2. Product/brand/marketing managers
3. CXO level executives
4. Regional/zonal/ country managers
5. Vice President level executives.
2. Government/institutional publications
3. Trade and associations journals
4. Databases such as WTO, OECD, World Bank, and among others.
5. Websites and publications by research agencies
2. Complete coverage of all the segments in the AI in drug discovery market to analyze the trends, developments in the global market and forecast of market size up to 2030.
3. Comprehensive analysis of the companies operating in the global AI in drug discovery market. The company profile includes analysis of product portfolio, revenue, SWOT analysis and latest developments of the company.
4. Growth Matrix presents an analysis of the product segments and geographies that market players should focus to invest, consolidate, expand and/or diversify.
Artificial Intelligence (AI) is revolutionizing the drug discovery market by significantly accelerating and enhancing the drug development process. AI in drug discovery involves the utilization of machine learning algorithms, data analysis, and computational techniques to streamline various stages of drug development, from target identification and validation to compound screening and clinical trial optimization. Additionally, the major driving factor for the adoption of AI in drug discovery is the overwhelming amount of biological and chemical data generated in the field. The explosion of biological data from genomics, proteomics, and other -omics technologies, coupled with the vast chemical compound libraries, makes it nearly impossible for researchers to manually process and analyze this data efficiently. AI systems excel at handling these large datasets, identifying meaningful patterns, and predicting potential drug candidates. This data-driven approach not only saves time and resources but also increases the likelihood of identifying novel drug candidates with higher efficacy and safety profiles, ultimately benefiting patients and the pharmaceutical industry as a whole. As AI continues to evolve and mature, it is poised to play an increasingly pivotal role in drug discovery and development.
The oncology sector stands out as the most rapidly expanding segment within the Artificial Intelligence (AI) in drug discovery market. This remarkable growth can be attributed to the pressing need for innovative and personalized treatments in cancer research and therapy. AI technologies, such as machine learning and data analytics, are being harnessed to analyze vast datasets, identify potential drug candidates, and optimize drug development processes in oncology. AI expedites the development of anti-cancer medications in the field of oncology drug discovery. Given the escalating cancer rates, this sector is poised for substantial expansion. As per the 2022 report from the American Cancer Society, cancer ranks as the second most prevalent cause of mortality in the United States. Projections indicate that by the conclusion of 2022, there will be over 609,360 fatalities and an estimated 1.9 million new cancer diagnoses. This underscores the pressing demand for AI-driven advancements in oncology to address this significant public health challenge. The ability of AI to accelerate the identification of novel cancer therapies and tailor treatments to individual patients is driving substantial interest and investment, making oncology the focal point of AI-driven drug discovery advancements.
North America is poised to lead the market due to several key factors, including the widespread adoption of AI technologies in the pharmaceutical sector, a substantial patient population, a higher incidence of chronic and infectious diseases, advanced healthcare infrastructure, and extensive ongoing clinical research and trials in AI-driven drug discovery within the region. The United States, in particular, stands out with a notable prevalence of metabolic and lifestyle-related diseases. For instance, according to the Centers for Disease Control data for 2022, over 37.3 million adults in the United States are grappling with diabetes, and as reported by the National Institutes of Health, 1 in 7 adults in the United States is affected by chronic kidney disease. Due to the rising adoption of AI in drug discovery across academic, research, and healthcare institutions, it is anticipated that companies and their significant advancements play a pivotal role in driving growth within the North American market.
Report Findings
1) Drivers
- Artificial intelligence can rapidly analyze and optimize potential drug candidates, drastically reducing the time and cost of drug discovery.
- The abundance of biological and chemical data is driving advancements in ai for drug discovery.
2) Restraints
- Regulatory hurdles and data privacy concerns pose challenges for ai adoption in drug discovery.
3) Opportunities
- Artificial intelligence offers the potential to accelerate drug discovery by enabling data-driven insights and predictive modeling, leading to more effective and personalized treatments.
Research Methodology
A) Primary Research
The primary research involves extensive interviews and analysis of the opinions provided by the primary respondents. The primary research starts with identifying and approaching the primary respondents, the primary respondents are approached include1. Key Opinion Leaders
2. Internal and External subject matter experts
3. Professionals and participants from the industry
The primary research respondents typically include
1. Executives working with leading companies in the market under review2. Product/brand/marketing managers
3. CXO level executives
4. Regional/zonal/ country managers
5. Vice President level executives.
B) Secondary Research
Secondary research involves extensive exploring through the secondary sources of information available in both the public domain and paid sources. Each research study is based on over 500 hours of secondary research accompanied by primary research. The information obtained through the secondary sources is validated through the crosscheck on various data sources.The secondary sources of the data typically include
1. Company reports and publications2. Government/institutional publications
3. Trade and associations journals
4. Databases such as WTO, OECD, World Bank, and among others.
5. Websites and publications by research agencies
Segment Covered
The global AI in drug discovery market is segmented on the basis of offering, technology, application, therapeutic area, and end user.The Global AI in Drug Discovery Market by Offering
- Software
- Services
The Global AI in Drug Discovery Market by Technology
- Machine Learning
- Natural Language Processing (NLP)
- Computer Vision
- Others
The Global AI in Drug Discovery Market by Application
- Target Identification
- Molecule Screening
- Drug Design and Drug Optimization
- Preclinical and Clinical Testing
- Others
The Global AI in Drug Discovery Market by Therapeutic Area
- Oncology
- Neurodegenerative Diseases
- Infectious Disease
- Others
The Global AI in Drug Discovery Market by End User
- Pharmaceutical & Biotechnology Companies
- Contract Research Organizations
- Academic & Government Research Institutes
Company Profiles
The companies covered in the report include- BenevolentAI
- Atomwise Inc.
- Cyclica Inc.
- DEEP GENOMICS
- Exscientia
- IBM Corporation
- NVIDIA Corporation
- Biosymetrics
- Cloud Pharmaceuticals
- Insilico Medicine
What does this Report Deliver?
1. Comprehensive analysis of the global as well as regional markets of the AI in drug discovery market.2. Complete coverage of all the segments in the AI in drug discovery market to analyze the trends, developments in the global market and forecast of market size up to 2030.
3. Comprehensive analysis of the companies operating in the global AI in drug discovery market. The company profile includes analysis of product portfolio, revenue, SWOT analysis and latest developments of the company.
4. Growth Matrix presents an analysis of the product segments and geographies that market players should focus to invest, consolidate, expand and/or diversify.
Table of Contents
Chapter 1. Preface
Chapter 2. Executive Summary
Chapter 3. Global AI in Drug Discovery Market Overview
Chapter 5. Company Profiles and Competitive Landscape
Chapter 6. Global AI in Drug Discovery Market by Offering
Chapter 7. Global AI in Drug Discovery Market by Technology
Chapter 8. Global AI in Drug Discovery Market by Application
Chapter 9. Global AI in Drug Discovery Market by Therapeutic Area
Chapter 10. Global AI in Drug Discovery Market by End User
Chapter 11. Global AI in Drug Discovery Market by Region 2023-2030
Companies Mentioned
- BenevolentAI
- Atomwise Inc.
- Cyclica Inc.
- DEEP GENOMICS
- Exscientia
- IBM Corporation
- NVIDIA Corporation
- Biosymetrics
- Cloud Pharmaceuticals
- Insilico Medicine
Table Information
Report Attribute | Details |
---|---|
No. of Pages | 350 |
Published | May 2023 |
Forecast Period | 2022 - 2030 |
Estimated Market Value ( USD | $ 1360.81 Million |
Forecasted Market Value ( USD | $ 9107.49 Million |
Compound Annual Growth Rate | 23.5% |
Regions Covered | Global |
No. of Companies Mentioned | 10 |