USD 1.80 billion
AI In Drug Discovery Market Size, Share, Growth Analysis, By Component (Software, Services), By Technology (Machine Learning, Deep Learning), By Application (Target Identification, Molecule Screening), By Region - Industry Forecast 2025-2032
Report ID:
SQMIG35J2061 |
Region:
Global |
Published Date: February, 2024
Pages:
157
|Tables:
59
|Figures:
75
AI in Drug Discovery Market Insights
AI in Drug Discovery Market size was valued at USD 1,427.67 Million in 2023 and is poised to grow from USD 1850.26 Million in 2024 to USD 14725.63 Million by 2032, growing at a CAGR of 29.6% during the forecast period (2025-2032).
The need for new medical cures, increased manufacturing capabilities of drugs in the life sciences sector, and breakthroughs in technology create a rising demand for AI-powered drug development solutions. Artificial intelligence technologies, including machine learning and deep learning, are being applied to the following stages of drug discovery, including initial compound screening and success rate for clinical trials. In addition, it is expected that increasing funding, investments, and startups in developing AI-based applications will drive AI in drug discovery market growth further. In addition, through addressing potential issues, increasing accuracy and efficiency, and reducing cycle times, the introduction of AI in the drug development process through clinical trials has revolutionized the entire sector. As such, this high-tech approach is getting more and more in favor with stakeholders in the life sciences industry as its benefits are increasingly being recognized. Clinical Trials Arena data for 2021 reported a sharp rise in the number of strategic alliances and collaborations between pharmaceutical corporations and AI-driven drug development organizations; this number increased from 4 in 2015 to 27 in 2020. This trend reflects the trend whereby AI is becoming increasingly useful as it accelerates the process of discovering and researching drugs. The growth momentum of AI in drug discovery industry is being facilitated by the availability of several alternatives, such as data mining and customization capabilities, for implementing AI technologies in drug discovery processes. The accuracy of identifying drug molecule binding characteristics improves significantly with the incorporation of machine learning and deep learning algorithms into AI systems.
US AI in Drug Discovery Market is poised to grow at a sustainable CAGR for the next forecast year.
Market snapshot - 2024-2031
Global Market Size
Largest Segment
Pharmaceutical and Biotechnology Companies
Fastest Growth
Pharmaceutical and Biotechnology Companies
Growth Rate
30.2% CAGR
Global AI in Drug Discovery Market ($ Bn)
Country Share for North America Region (%)
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AI in Drug Discovery Market Segmental Analysis
Global AI in Drug Discovery Market is segmented by component, technology, application, therapeutic area, end use and region. Based on component, the market is segmented into software and services. Based on technology, the market is segmented into machine learning, deep learning, natural language processing (NLP) and others. Based on application, the market is segmented into target identification, molecule screening, lead optimization, preclinical testing, clinical trials and others. Based on therapeutic area, the market is segmented into oncology, neurodegenerative diseases, cardiovascular diseases, metabolic diseases, infectious diseases and others. Based on end use, the market is segmented into pharmaceutical & biotechnology companies, contract research organizations (CROs), academic & research institutes and others. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.
Analysis by Drug Type
As per the 2023 AI in drug discovery market analysis, the small molecules category dominated the market in most therapeutic areas. These have abundant clinical data and thus represent a sound application for AI-based analysis and are key to the growth of the segment. Artificial intelligence significantly expedites the drug approval process and accelerates the development of new drugs through the effective evaluation of large amounts of information, trends identification, and prediction of molecular interactions. Due to the well-established safety profiles and predictable features, small molecules are an affordable option for medicinal chemistry. Moreover, more companies are focusing on AI-driven solutions for faster small molecule drug discovery, as there is a growing demand to speed up medicinal development.
In contrast, the large molecules segment is expected to grow during the forecast period. Since the process is also highly complex, there are only a limited number of labs that carry out research and production on large molecules. The most significant reason for the smaller share of the market today is that this limits the data available for effective execution of solutions using artificial intelligence. The demand for AI solutions is expected to grow throughout the forecast period, however, as market players continue to further investment in large molecules research and development of drugs to offer more complex therapeutic values with more affordable prices.
Analysis By Technology
Based on the AI in drug discovery market forecast, the machine learning category led the market for the sheer reason that its popularity is increasing. Predictive models produced by machine learning have become much more relevant in the stages preceding preclinical research. A collection of tools known as machine learning (ML) techniques enhances the process of finding answers to well-defined queries using a wealth of high-quality data. According to a study in February 2023 conducted by Cell Reports Methods, the uses of machine learning include predicting FDA clearance, designing clinical trials, repurposing drugs, and even novel therapeutic targets.
However, the natural language processing segment share is expected to be high. Structured information extraction from text-based documents can be performed using this technology. Facilitated by the advantages that this technology provides regarding extracting tangible insights from a large volume of data, the growth of the segment is being aided. Other technologies include robotics, automation, and machine vision. During the projection period, the category is expected to increase at a relatively lower CAGR. These technologies require the processing of significant amounts of data to achieve desired outcomes, but they still are in their very early stages of development. In natural language processing, for instance, masses of unstructured data can unearth important information from the array of medical records and clinical trial reports, not to mention scholarly literature.
Global AI in Drug Discovery Market By End User
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AI in Drug Discovery Market Regional Insights
Huge spending on healthcare technology and strategic collaborations between tech leaders and pharmaceutical firms have made North America lead the market with a 57.7% share in 2023 of AI in drug discovery. Innovation and the advance of AI-driven solutions are further facilitated by the region's best research institutes and a favorable regulatory framework. North American firms increasingly employ AI to optimize drug discovery operations and increase productivity, reduce development costs, and accelerate the launch of new therapies. Customized medicine is finally becoming a pressing need and the advancement of AI capabilities to solve challenges in drug development as well are two more factors that drive this trend to expand further.
Contrarily, the AI in drug discovery market in Europe is expected to grow significantly over the forecast period. Europe emerges as a prime player in the market for AI in drug discovery, largely attributed to significant contributions from countries such as the UK and Germany. The region has sturdy research infrastructure that supports AI integration in healthcare, with beneficial regulatory frameworks in place. European companies are leading the pack in the adoption of AI in drug discovery, focusing on advanced analytics and personalized medicine to enhance the drug development process. This is being propelled by collaboration between government organizations, businesses, and academia.
Global AI in Drug Discovery Market By Geography
- Largest
- Fastest
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AI in Drug Discovery Market Dynamics
AI in Drug Discovery Market Drivers
Higher Expenditure on Medical Technology
- In terms of market expansion, the increasing investment in healthcare technology is one of the primary drivers for AI in drug discovery industry. To fasten the drug discovery process, businesses are making huge investments in researching and developing processes, particularly in the areas of artificial intelligence and machine learning. It enhances the development of potential drug candidates and reduces the time of clinical trials, hence making drugs faster and cheaper to develop.
Advancements in Machine Learning and AI
- The rapid development of AI and machine learning technology is one of the major drivers of the market. As these technologies can better analyze complex biological data, their application to enhance drug discovery accuracy is growing rapidly. Businesses may discover medicinal compounds much faster and with greater accuracy through AI algorithms that can predict molecular behavior and identify new drug targets and optimize drug design.
AI in Drug Discovery Market Restraints
Data Security and Privacy Issues
- The leading challenge in AI-based drug research is that of data security and privacy. Healthcare data, being sensitive in nature, faces breaches; hence, there are concerns about ethical and legal issues. Businesses will have to walk through the unforgiving norms of data privacy and cybersecurity precautions, which would increase costs and slow down the use of AI-driven drug development solutions.
High Costs of Implementation
- Installation of software, hardware, and high-skilled people is required in the implementation of an AI-based solution. For many pharmaceutical businesses, especially smaller ones, it may be challenging to justify these handsome costs. While AI does promise savings in terms of long-term expenses, some firms might find it hard to embrace and include the current systems in their system due to the initial capital expenditure.
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AI in Drug Discovery Market Competitive Landscape
The competitive landscape of AI in drug development comprises tech giants, biotechnology businesses, and well-established pharmaceutical corporations. To make contributions towards research in medication, the main corporates, Microsoft, Google Health, and IBM, are investing extensively in AI. Moreover, specialist AI-based businesses, such as Insilico Medicine and Atomwise, are doing great work to adapt AI for the discovery and design of medication. Collaborations, acquisitions, and strategic alliances are crucial to market development.
AI in Drug Discovery Market Top Player’s Company Profiles
- IBM Corporation
- NVIDIA Corporation
- Microsoft Corporation
- Exscientia
- Atomwise, Inc.
- BenevolentAI
- Insilico Medicine
- Cyclica
- Schrödinger, Inc.
- Cloud Pharmaceuticals, Inc.
- BioSymetrics
- XtalPi Inc.
- Deep Genomics
- Numerate, Inc.
- Berg LLC
- OWKIN, Inc.
- TwoXAR, Inc.
- Verge Genomics
- Recursion Pharmaceuticals
- PathAI
AI in Drug Discovery Market Recent Developments
- In July 2024, Exscientia and Amazon Web technologies (AWS) announced an extended partnership with the goal to leverage AWS's AI and machine learning (ML) technologies in enhancing Exscientia's end-to-end drug discovery and automation platform.
- In May 2024, the third iteration of Google DeepMind's AlphaFold AI-based model was launched, which was intended to refine disease targeting and drug discovery. This latest version allows researchers at DeepMind and Isomorphic Labs to map the behavior of all molecules, including human DNA.
- In April 2024, the AI-based medicines discovery and development startup, Xaira Therapeutics, raised more than USD 1 million in a joint round of fundraising with ARCH Venture Partners and Foresite Labs. The company approaches historically challenging targets in medications using machine learning, creation algorithms, and therapeutic product development.
AI in Drug Discovery Key Market Trends
- AI Application in Preclinical and Clinical Research: This trend in drug research about the increased utilization of AI in preclinical and clinical trials is quite notable. Biomarkers for the course of disease are currently being identified through the help of AI models, while clinical trial designs are improved, and patient responses are predicted. AI reduces the risk of trial failures, accelerates testing, and helps identify the drug candidates that will lead to further development by improving the accuracy of the procedures involved in trials and enhancing patient enrollment.
- AI in Biomarker Discovery: AI is increasingly applied for the discovery of new biomarkers, which are fundamental to customized medicine. In proteomics, genomics, and clinical study sources, AI can investigate large datasets to identify molecular markers related to certain diseases or other responses to therapy. This trend holds specific importance in the creation of targeted drugs because it provides more precise diagnosis and maximizes therapeutic effectiveness for different patient groups.
AI in Drug Discovery Market SkyQuest Analysis
SkyQuest’s ABIRAW (Advanced Business Intelligence, Research & Analysis Wing) is our Business Information Services team that Collects, Collates, Correlates, and Analyses the Data collected using Primary Exploratory Research backed by robust Secondary Desk research.
As per SkyQuest analysis, the AI in the drug discovery market is growing rapidly with machine learning advancements and greater expenditure in high-tech medical research. Businesses need to expect a fast time-to-market for new treatments, cheaper research operations, and better identification of drug candidates with the help of improvements in the drug discovery process from AI. The problems are with the high up-front costs of implementation and concerns over data privacy persist. However, the struggle to personalize treatments and integrate AI with other technologies guides the advancement in drugs in the future. It is envisioned that developing drugs with AI is amongst the core underpinnings that will drive improved patient individuality and cost and time efficiency in this domain.
| Report Metric | Details |
|---|---|
| Market size value in Drug | USD 1.80 billion |
| Market size value in 2031 | USD 19.35 billion |
| Growth Rate | 30.2% |
| Base year | 2023 |
| Forecast period | 2024-2031 |
| Forecast Unit (Value) | USD Billion |
| Segments covered |
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| 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) |
| Companies covered |
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| Customization scope | Free report customization with purchase. Customization includes:-
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Table Of Content
Executive Summary
Market overview
- Exhibit: Executive Summary – Chart on Market Overview
- Exhibit: Executive Summary – Data Table on Market Overview
- Exhibit: Executive Summary – Chart on AI in Drug Discovery Market Characteristics
- Exhibit: Executive Summary – Chart on Market by Geography
- Exhibit: Executive Summary – Chart on Market Segmentation
- Exhibit: Executive Summary – Chart on Incremental Growth
- Exhibit: Executive Summary – Data Table on Incremental Growth
- Exhibit: Executive Summary – Chart on Vendor Market Positioning
Parent Market Analysis
Market overview
Market size
- Market Dynamics
- Exhibit: Impact analysis of DROC, 2021
- Drivers
- Opportunities
- Restraints
- Challenges
- Exhibit: Impact analysis of DROC, 2021
- SWOT Analysis
KEY MARKET INSIGHTS
- Technology Analysis
- (Exhibit: Data Table: Name of technology and details)
- Pricing Analysis
- (Exhibit: Data Table: Name of technology and pricing details)
- Supply Chain Analysis
- (Exhibit: Detailed Supply Chain Presentation)
- Value Chain Analysis
- (Exhibit: Detailed Value Chain Presentation)
- Ecosystem Of the Market
- Exhibit: Parent Market Ecosystem Market Analysis
- Exhibit: Market Characteristics of Parent Market
- IP Analysis
- (Exhibit: Data Table: Name of product/technology, patents filed, inventor/company name, acquiring firm)
- Trade Analysis
- (Exhibit: Data Table: Import and Export data details)
- Startup Analysis
- (Exhibit: Data Table: Emerging startups details)
- Raw Material Analysis
- (Exhibit: Data Table: Mapping of key raw materials)
- Innovation Matrix
- (Exhibit: Positioning Matrix: Mapping of new and existing technologies)
- Pipeline product Analysis
- (Exhibit: Data Table: Name of companies and pipeline products, regional mapping)
- Macroeconomic Indicators
COVID IMPACT
- Introduction
- Impact On Economy—scenario Assessment
- Exhibit: Data on GDP - Year-over-year growth 2016-2022 (%)
- Revised Market Size
- Exhibit: Data Table on AI in Drug Discovery Market size and forecast 2021-2027 ($ million)
- Impact Of COVID On Key Segments
- Exhibit: Data Table on Segment Market size and forecast 2021-2027 ($ million)
- COVID Strategies By Company
- Exhibit: Analysis on key strategies adopted by companies
MARKET DYNAMICS & OUTLOOK
- Market Dynamics
- Exhibit: Impact analysis of DROC, 2021
- Drivers
- Opportunities
- Restraints
- Challenges
- Exhibit: Impact analysis of DROC, 2021
- Regulatory Landscape
- Exhibit: Data Table on regulation from different region
- SWOT Analysis
- Porters Analysis
- Competitive rivalry
- Exhibit: Competitive rivalry Impact of key factors, 2021
- Threat of substitute products
- Exhibit: Threat of Substitute Products Impact of key factors, 2021
- Bargaining power of buyers
- Exhibit: buyers bargaining power Impact of key factors, 2021
- Threat of new entrants
- Exhibit: Threat of new entrants Impact of key factors, 2021
- Bargaining power of suppliers
- Exhibit: Threat of suppliers bargaining power Impact of key factors, 2021
- Competitive rivalry
- Skyquest special insights on future disruptions
- Political Impact
- Economic impact
- Social Impact
- Technical Impact
- Environmental Impact
- Legal Impact
Market Size by Region
- Chart on Market share by geography 2021-2027 (%)
- Data Table on Market share by geography 2021-2027(%)
- North America
- Chart on Market share by country 2021-2027 (%)
- Data Table on Market share by country 2021-2027(%)
- USA
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Canada
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Europe
- Chart on Market share by country 2021-2027 (%)
- Data Table on Market share by country 2021-2027(%)
- Germany
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Spain
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- France
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- UK
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Rest of Europe
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Asia Pacific
- Chart on Market share by country 2021-2027 (%)
- Data Table on Market share by country 2021-2027(%)
- China
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- India
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Japan
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- South Korea
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Rest of Asia Pacific
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Latin America
- Chart on Market share by country 2021-2027 (%)
- Data Table on Market share by country 2021-2027(%)
- Brazil
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Rest of South America
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Middle East & Africa (MEA)
- Chart on Market share by country 2021-2027 (%)
- Data Table on Market share by country 2021-2027(%)
- GCC Countries
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- South Africa
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
- Rest of MEA
- Exhibit: Chart on Market share 2021-2027 (%)
- Exhibit: Market size and forecast 2021-2027 ($ million)
KEY COMPANY PROFILES
- Competitive Landscape
- Total number of companies covered
- Exhibit: companies covered in the report, 2021
- Top companies market positioning
- Exhibit: company positioning matrix, 2021
- Top companies market Share
- Exhibit: Pie chart analysis on company market share, 2021(%)
- Total number of companies covered
Methodology
For the 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 AI in Drug Discovery Market.
3. Report Formulation: The final step entailed the placement of data points in appropriate Market spaces in an attempt to deduce viable conclusions.
4. Validation & Publishing: Validation is the most important step in the process. Validation & re-validation via an intricately designed process helped us finalize data points to be used for final calculations. The final Market estimates and forecasts were then aligned and sent to our panel of industry experts for validation of data. Once the validation was done the report was sent to our Quality Assurance team to ensure adherence to style guides, consistency & design.
Analyst Support
Customization Options
With the given market data, our dedicated team of analysts can offer you the following customization options are available for the AI in Drug Discovery Market:
Product Analysis: Product matrix, which offers a detailed comparison of the product portfolio of companies.
Regional Analysis: Further analysis of the AI in Drug Discovery Market for additional countries.
Competitive Analysis: Detailed analysis and profiling of additional Market players & comparative analysis of competitive products.
Go to Market Strategy: Find the high-growth channels to invest your marketing efforts and increase your customer base.
Innovation Mapping: Identify racial solutions and innovation, connected to deep ecosystems of innovators, start-ups, academics, and strategic partners.
Category Intelligence: Customized intelligence that is relevant to their supply Markets will enable them to make smarter sourcing decisions and improve their category management.
Public Company Transcript Analysis: To improve the investment performance by generating new alpha and making better-informed decisions.
Social Media Listening: To analyze the conversations and trends happening not just around your brand, but around your industry as a whole, and use those insights to make better Marketing decisions.
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