Global Artificial Intelligence (AI) in Drug Discovery Market, By Application (Novel Drug Candidates, Drug Optimization and Repurposing Preclinical Testing and Approval, Drug Monitoring, Finding New Diseases Associated Targets and Pathways, Understanding Disease Mechanisms, Aggregating and Synthesizing Information, Formation and Qualification of Hypotheses, De Novo Drug Design, Finding Drug Targets of an Old Drug and Others), Technology (Machine Learning, Deep Learning, Natural Language Processing and Others), Drug Type (Small Molecule and Large Molecule), Offering (Software and Services), Indication (Immuno-Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases and Others), End Use (Contract Research Organizations (CROs), Pharmaceutical and Biotechnology Companies, Research Centers and Academic Institutes and Others) – Industry Trends and Forecast to 2031.
Artificial Intelligence (AI) in Drug Discovery Market Analysis and Size
Artificial intelligence (AI) in drug discovery market continues its exponential growth, leveraging the latest methods and technologies to revolutionize pharmaceutical research. Through advanced algorithms and data analytics, AI expedites drug identification and optimization processes, significantly reducing time and costs. Its application in predictive modeling, virtual screening, and target identification enhances drug development efficiency, promising breakthroughs in combating diseases.
The global artificial intelligence (AI) in drug discovery market size was valued at USD 932.24 million in 2023, is projected to reach USD 1,409.14 million by 2031, with a CAGR of 5.30% during the forecast period 2024 to 2031. This indicates that the market value. In addition to the insights on market scenarios such as market value, growth rate, segmentation, geographical coverage, and major players, the market reports curated by the Data Bridge Market Research also include depth expert analysis, patient epidemiology, pipeline analysis, pricing analysis, and regulatory framework.
Report Scope and Market Segmentation
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Report Metric
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Details
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Forecast Period
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2024 to 2031
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Base Year
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2023
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Historic Years
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2022 (Customizable to 2016-2021)
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Quantitative Units
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Revenue in USD Million, Volumes in Units, Pricing in USD
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Segments Covered
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Application (Novel Drug Candidates, Drug Optimization and Repurposing Preclinical Testing and Approval, Drug Monitoring, Finding New Diseases Associated Targets and Pathways, Understanding Disease Mechanisms, Aggregating and Synthesizing Information, Formation and Qualification of Hypotheses, De Novo Drug Design, Finding Drug Targets of an Old Drug and Others), Technology (Machine Learning, Deep Learning, Natural Language Processing and Others), Drug Type (Small Molecule and Large Molecule), Offering (Software and Services), Indication (Immuno-Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases and Others), End Use (Contract Research Organizations (CROs), Pharmaceutical and Biotechnology Companies, Research Centers and Academic Institutes and Others)
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Countries Covered
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U.S., Canada and Mexico in North America, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, Rest of Europe in Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, South Africa, Egypt, Israel, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), Brazil, Argentina and Rest of South America as part of South America.
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Market Players Covered
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NVIDIA Corporation (U.S.), IBM Corp. (U.S.), Atomwise Inc. (U.S.), Microsoft (U.S.), Benevolent AI (U.K.), Aria Pharmaceuticals, Inc. (U.S.), DEEP GENOMICS (Canada), Exscientia (U.K.), Insilico Medicine (Hong Kong), Cyclica (Canada), NuMedii, Inc. (U.S.), Envisagenics (U.S.), Owkin Inc. (U.S.), BERG LLC (U.S.), Schrödinger, Inc. (U.S.), XtalPi Inc. (China), and BIOAGE Inc. (U.S.)
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Market Opportunities
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Market Definition
Artificial Intelligence (AI) in drug discovery leverages advanced algorithms to analyze vast datasets, predict molecular interactions, and design novel compounds with therapeutic potential. Through machine learning and data mining techniques, AI accelerates the drug development process, optimizing molecule selection and reducing costs. It enhances target identification, lead optimization, and toxicity prediction, revolutionizing pharmaceutical research and expediting the delivery of life-saving medications.
Artificial Intelligence (AI) in Drug Discovery Market Dynamics
Drivers
- Accelerated Drug Discovery Process
AI expedites the drug discovery process by analyzing vast datasets, predicting molecular interactions, and identifying potential drug candidates more rapidly than traditional methods. For instance, Atomwise, using AI-powered virtual screening, identified a drug candidate for Ebola in just a few days, a process that typically takes months using traditional methods. This acceleration allows for quicker identification and development of promising compounds, potentially saving lives in urgent medical situations.
- Rise in Incidence of Chronic Diseases Propels Need
The surge in chronic diseases worldwide, exemplified by CDC data showing six in 10 U.S. adults affected, underscores the urgency for effective treatments. AI in drug discovery emerges as a promising solution to mitigate this health crisis. Through analyzing vast datasets, AI platforms offer insights into developing drugs targeting conditions such as heart disease and diabetes, addressing the pressing need for innovative therapies to reduce mortality rates.
Opportunities
- Rising Collaboration and Data Sharing among Researchers
AI fosters collaboration among researchers and facilitates data sharing across institutions and companies, enabling access to diverse datasets and enhancing the collective knowledge base for drug discovery. For instance, platforms such as OpenAI's Drug Discovery, which harness AI to analyze molecular structures and predict drug properties, encourage collaborative efforts by providing a shared space for researchers to access and contribute to a vast pool of data, accelerating the pace of discovery and innovation in the pharmaceutical industry.
- Growing Demand for Personalized Medicine
AI facilitates personalized medicine by analyzing patient data, including genomics, proteomics, and clinical records, to identify biomarkers indicative of disease susceptibility and treatment response. For instance, AI-driven analysis of tumor genomic profiles can predict patient responses to specific cancer therapies, enabling tailored treatment strategies that maximize efficacy and minimize adverse effects, ultimately improving patient outcomes in oncology and beyond.
Restraints/Challenges
- Integration with Traditional Methods Hinder Workflow
Integrating AI with traditional drug discovery methods faces hurdles in standardization, compatibility, and workflow optimization. Harmonizing AI algorithms with established experimental and computational techniques necessitates meticulous planning to ensure seamless integration, minimizing disruptions to existing workflows.
- Data Privacy and Accessibility Limit Development
Access to proprietary data in drug discovery is restricted due to privacy, intellectual property, and regulatory constraints. This limits the availability of data for AI models, hindering their development and validation. Privacy concerns, especially regarding patient data, necessitate careful handling and compliance with regulations, further complicating data accessibility for AI-driven drug discovery initiatives.
This market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on the market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.
Recent Development
- In July 2021, Chief.AI introduced a pay-as-you-go AI platform for drug discovery, democratizing access to advanced AI technologies. This empowers small and medium enterprises to pinpoint breakthrough therapeutics swiftly and precisely, addressing the unpredictability of traditional drug discovery
- In January 2021, Nucleai and Debiopharm Pharma formed a collaborative agreement, permitting the latter to utilize Nucleai's AI platform for oncology drug candidates. This underscores AI's growing significance in refining drug development processes, particularly in biomarker-based therapies
- In September 2020 witnessed Atomwise securing USD 123 million in Series B financing, led by Sanabil and B Capital Group Investments. This substantial investment aims to expand Atomwise's market presence, initiate its drug discovery pipeline, and forge new partnerships with pharmaceutical firms, emphasizing AI's pivotal role in advancing artificial intelligence in drug discovery and development
- In July 2020, IBM strategically acquired WDG Automation, enriching its AI-infused automation capabilities for enterprises. This strategic move enhances IBM's capacity to deliver comprehensive AI solutions, spanning from business processes to IT operations, thereby fortifying its overall portfolio
Artificial Intelligence (AI) in Drug Discovery Market Scope
The market is segmented on the basis of application, technology, drug type, offering, indication, and end use. The growth amongst these segments will help you analyze meagre growth segments in the industries and provide the users with a valuable market overview and market insights to help them make strategic decisions for identifying core market applications.
Application
- Novel Drug Candidates
- Drug Optimization and Repurposing Preclinical Testing and Approval
- Drug Monitoring
- Finding New Diseases Associated Targets and Pathways
- Understanding Disease Mechanisms
- Aggregating and Synthesizing Information
- Formation and Qualification of Hypotheses
- De Novo Drug Design
- Finding Drug Targets of an Old Drug
- Others
Technology
- Machine Learning
- Supervised Learning
- Reinforcement Learning
- Unsupervised Learning
- Other Machine Learning Technologies
- Deep Learning
- Natural Language Processing
- Others
Drug Type
- Small Molecule
- Large Molecule
Offering
- Software
- Services
Indication
- Immuno-Oncology
- Neurodegenerative Diseases
- Cardiovascular Diseases
- Metabolic Diseases
- Others
End Use
- Contract Research Organizations (CROs)
- Pharmaceutical and Biotechnology Companies
- Research Centers and Academic Institutes
- Others
Artificial Intelligence (AI) in Drug Discovery Market Regional Analysis/Insights
The market is analysed and market size insights and trends are provided by country, application, technology, drug type, offering, indication, and end use as referenced above.
The countries covered in the market report are U.S., Canada and Mexico in North America, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, Rest of Europe in Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, South Africa, Egypt, Israel, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), Brazil, Argentina and Rest of South America as part of South America.
North America is expected to dominate the artificial intelligence (AI) in drug discovery market, driven by substantial research investments and widespread AI adoption in medicine development. Key players such as IBM, Google, and Microsoft strengthen the region's influence and technological advancement, catalyzing market growth significantly.
Asia-Pacific is expected to witness rapid growth in the artificial intelligence (AI) in drug discovery market due to heightened investments in research and development initiatives. The region's evolving healthcare infrastructure further accelerates market expansion, underscoring its growing influence in shaping AI applications for drug discovery.
The country section of the report also provides individual market impacting factors and changes in regulation in the market domestically that impacts the current and future trends of the market. Data points like down-stream and upstream value chain analysis, technical trends and porter's five forces analysis, case studies are some of the pointers used to forecast the market scenario for individual countries. Also, the presence and availability of global brands and their challenges faced due to large or scarce competition from local and domestic brands, impact of domestic tariffs and trade routes are considered while providing forecast analysis of the country data.
Healthcare Infrastructure growth Installed base and New Technology Penetration
The market also provides you with detailed market analysis for every country growth in healthcare expenditure for capital equipment, installed base of different kind of products for market, impact of technology using life line curves and changes in healthcare regulatory scenarios and their impact on the market. The data is available for historic period 2016-2021.
Competitive Landscape and Artificial Intelligence (AI) in Drug Discovery Market Share Analysis
The market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in research and development, new market initiatives, global presence, production sites and facilities, production capacities, company strengths and weaknesses, product launch, product width and breadth, application dominance. The above data points provided are only related to the companies' focus related to market.
Some of the major players operating in the market are:
- NVIDIA Corporation (U.S.)
- IBM Corp. (U.S.)
- Atomwise Inc. (U.S.)
- Microsoft (U.S.)
- Benevolent AI (U.K.)
- Aria Pharmaceuticals, Inc. (U.S.)
- DEEP GENOMICS (Canada)
- Exscientia (U.K.)
- Insilico Medicine (Hong Kong)
- Cyclica (Canada)
- NuMedii, Inc. (U.S.)
- Envisagenics (U.S.)
- Owkin Inc. (U.S.)
- BERG LLC (U.S.)
- Schrödinger, Inc. (U.S.)
- XtalPi Inc. (China)
- BIOAGE Inc. (U.S.)
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