Market Size (2018)
2018
$205.90M
Healthcare
AI In Drug Discovery Market
By Segment, By Region, And Segment Forecasts, 2018 – 2030
Vertical: HealthcareBase Year: 202112 Sections
Executive Summary
AI In Drug Discovery Market — Snapshot
Projected (2030)
2030
$4.52B
CAGR (2018–2030)
29.4%
29.4%Key Players
109+
The factors such as increasing adoption of AI in drug discovery, rising strategic initiatives for AI in drug discovery, increasing number of AI-powered drug discovery start-ups, and a growing number of public-private partnerships propelling the adoption of AI-powered solutions in drug discovery and development processes is helping the growth of the market. Furthermore, the growing demand for novel drug therapies and the life science industry's increasing manufacturing capacities are driving the demand for AI enabled solutions in drug discovery processes.
Key Insight
The AI In Drug Discovery Market market is projected to grow at a CAGR of 29.4% from 2018 to 2030.
Market Performance Trend
Historical performance and future projections (2020–2030, USD Billion)
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What this report covers
- Geographic Coverage: This analysis covers 4 regions: North America, Europe, Asia Pacific, Rest of the World.
- Market Segmentation: The market is analyzed across 2 segments: By Product And Service_Services, By Product And Service_Software. Forecasts are provided for each segment from 2018 to 2030.
- Competitive Landscape: 109 leading companies are profiled, covering market positioning, strategies, and recent developments.
Market Size (USD Mn)
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View Subscription PlansMarket Overview
AI In Drug Discovery Market — Growth Trajectory
AI encompasses several method domains, including reasoning, knowledge representation, solution search, and a fundamental machine learning paradigm. AI is increasingly being used in various sectors of society, particularly the pharmaceutical industry, for tasks such as drug discovery & development, drug repurposing, improving pharmaceutical productivity, and clinical trials, among others; such use reduces human workload while meeting targets in a short period of time. Furthermore, the vast chemical space, which contains more than 10^60 molecules, promotes the development of a large number of drug molecules. The lack of advanced technologies, on the other hand, limits the drug development process, making it a time-consuming and expensive task that can be addressed by using AI. AI can identify hit and lead compounds, as well as provide faster validation of the drug target and optimization of drug structure design.
AI In Drug Discovery Market — Growth Trajectory
By Product And Service_Services
By Product And Service_Software
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View Subscription PlansMarket Size Trend (USD Mn)
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View Subscription PlansMarket Dimensions
How this market is segmented
- By Product And Service By Product And Service is broken down into: By Product And Service_Software, By Product And Service_Services.
- By Molecule Type By Molecule Type is broken down into: By Molecule Type_Large Molecule, By Molecule Type_Small Molecule.
- By Technology By Technology is broken down into: Machine Learning, Deep Learning, Others.
- By Indication By Indication is broken down into: Immuno-oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases, By Indication_Others.
- By Application By Application is broken down into: Target Identification, Candidate Screening, De novo Drug Designing, Drug Optimization and Repurposing, Preclinical Testing.
Geographic Analysis
Regional market breakdown
- North America North America market size reached $87.31M in 2018 and is projected to reach $2.04B by 2030, growing at a CAGR of 30.0%.
- Europe Europe market size reached $55.18M in 2018 and is projected to reach $1.14B by 2030, growing at a CAGR of 28.7%.
- Asia Pacific Asia Pacific market size reached $37.96M in 2018 and is projected to reach $1.00B by 2030, growing at a CAGR of 31.4%.
- Rest of the World Rest of the World market size reached $25.46M in 2018 and is projected to reach $345.46M by 2030, growing at a CAGR of 24.3%.
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View Subscription PlansResearch Methodology
AI In Drug Discovery Market — How We Researched This Market
This report applies a rigorous multi-stage research process combining primary interviews, secondary data sources, and bottom-up market modelling to ensure accuracy and completeness across all segments and geographies.
Base Year
2021
Historical Period
2018 – 2021
Forecast Period
2021 – 2030
Primary Interviews
150+
Research Process
Historical data (2018–2021) and forecast period (2021–2030)
1
Problem Definition
- Market scoping
- Objective setting
- Framework design
2
Secondary Research
- Literature review
- Data mining
- Trend analysis
3
Primary Research
- Expert interviews
- Field visits
- Surveys
4
Data Analysis
- Quantitative modeling
- Statistical testing
- Validation
5
Insights & Reporting
- Synthesis
- Recommendations
- Visualization
Research Depth
Our research process spans primary interviews with industry stakeholders combined with comprehensive secondary data analysis, validated through triangulation across multiple independent sources.
Historical vs. Forecast Data
Historical (observed)
Forecast (modelled)
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View Subscription PlansCompetitive Landscape & Porter's Five Forces
AI In Drug Discovery Market — Competitive Analysis
Threat of New Entrants
Any manufacturing company trying to enter the market is required to accept and abide by the mandatory regulatory standards set by regulatory bodies such as the Food and Drug Administration (FDA), the European Medicines Agency (EMA), the European Centre for Disease Prevention and Control (ECDC), and others across the globe. Moreover, it may be difficult for new firms to get into this industry due to the brand image of existing large corporations as well as the shortage of an AI workforce, which puts buyers under pressure to purchase existing brand products. However, the fact that a huge number of start-ups are working on and launching products to solve problems such as protein folding, and synthetic accessibility shows that the threat of new entrants in this market is moderate.
Bargaining Power of Suppliers
There are several players at the same time, and consumers are largely at fault because of the increasing incidences of chronic diseases. AI tools reduce the time and cost of drug development, making it easier for suppliers to establish themselves in the market. Furthermore, manufacturers of AI devices and machines used in drug discovery place a premium on the uniqueness of their products in terms of qualitative and quantitative measurement. There is no replacement of the product until the process for drug discovery is finished, as the platform installation cost is also high. So, once the product is installed, there are fewer opportunities to replace the AI devices and machines until the product shows any accuracy problems.
Threat of Substitutes
Substitutes pose a moderate threat in the global AI drug discovery market due to replacing devices and machines with another brand if the existing AI tools exhibit accuracy issues. There is also a slight price difference between the AI tools of competitors. There are several manufacturers in the market, as well as a huge number of start-ups that are offering the platforms at a slightly lower cost than the large corporations. Moreover, there are moderate chances of product replacements as it is based on accuracy and precision, deals with patient life, and are used at a large scale to discover drug molecules.
Bargaining Power of Buyers
The low number of manufacturers compared to consumer demands puts buyers under pressure to purchase AI tools. This is because if buyers miss out on purchasing products, they will be delayed in carrying out their organization's processes. Furthermore, the manufacturer is unable to supply them at the time of their requirement due to a large number of consumers. There are products available in the market from competitors with the same accuracy and precision. However, there will be no brand switching because, once the devices and machines have been installed, they will be suited to the product operating person of that particular organization. Nonetheless, the market players' product costs differ slightly, but the organization continues to use a same brand of product until it discovers inaccuracies and the workforce's inability to operate the instruments. Moreover, as per the research, organizations use the same brand of products continuously because AI tools require a talented workforce. Once it is suited to the organization's workforce, there are minor chances to replace the product due to shortages of AI workforces. Therefore, the consumer keeps purchasing that same brand for several years.
Intensity of Rivalry
The demand for AI tools for drug discovery is high, owing to the huge patient population across the globe, the rising incidences of communicable and non-communicable diseases, and the rising demand for precision medicine. There are many start-ups that are introducing slightly lower-cost products than the existing brand's products. However, there is a high shortage of AI-skilled professionals, which further puts buyers under pressure to keep purchasing the same brand of product. As well, once the buyer installs the AI platform for drug discovery, it will continuously use that platform owing to the high price of installation. Hence, the high cost of installation and shortage of AI further increase the demand for the same brand, and the competition among players is overall moderate.
Quantitative Analysis
Regional Breakdown
Regional market breakdown for AI In Drug Discovery Market.
Regional Market Size (USD Mn)
Market estimates by geography (2030)
USD Mn
InsightNorth America leads with $2.04B by 2030, while Asia Pacific is projected to grow fastest at a 31.4% CAGR.
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View Subscription PlansRegional Market Data
| REGION | 2018 | 2021 | 2030 | CAGR | SHARE |
|---|---|---|---|---|---|
| North America | $87.31M | $409.00M | $2.04B | 30.0% | 45% |
| Europe | $55.18M | $242.79M | $1.14B | 28.7% | 25% |
| Asia Pacific | $37.96M | $189.84M | $1.00B | 31.4% | 22% |
| Rest of the World | $25.46M | $93.79M | $345.46M | 24.3% | 8% |
| Total | $205.91M | $935.42M | $4.52B | 29.4% | 100% |
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View Subscription PlansSegment Revenue (2030)
By Product And Service_Services
By Product And Service_Software
0767153523023069
Segment Market Share
- By Product And Service_Services62%
- By Product And Service_Software38%
Total Market Size
$4.52B
Market by Segment (2030)
| APPLICATION | REVENUE ($B) | GROWTH RATE | MARKET PENETRATION |
|---|---|---|---|
| By Product And Service_Services | $2.79B | 29.4% | 60% |
| By Product And Service_Software | $1.73B | 29.4% | 60% |
* Revenue projections based on 2025 estimates. Growth rates represent CAGR 2024–2030. Market penetration indicates current adoption rate within addressable market segments.
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Analytics
AI In Drug Discovery Market — Key Findings
Analytical insights on AI In Drug Discovery Market covering market dynamics, competitive landscape, and strategic outlook.
Key Analytical Findings
The AI In Drug Discovery Market market is projected to reach $4.52B by 2030, growing at 29.4% CAGR. The By Product And Service_Services segment holds the largest share.
Market Dynamics
The use of Artificial Intelligence in the Drug Discover space has been one of the most disruptive movements in the Pharmaceutical R&D space.
The increasing adoption of AI in drug discovery is one of the imperative factors driving the growth of the global AI in the drug discovery market. Likewise, rising strategic initiatives for AI in drug discovery and an increasing number of AI-powered drug discovery start-ups are further fueling the growth of the global market during the forecast period.
However, the shortage of AI workers is expected to hamper the growth of the global market. Nonetheless, it is anticipated that emerging markets will create lucrative opportunity pockets for the players operating in the global market.
Market Drivers
The adoption of AI in drug discovery is rising among industries, including pharmaceutical and biotechnology companies. This is primarily owing to the fact that AI offers advanced advantages to discovering the drug molecule and speeds up the drug discovery process.
The advantages of deploying the same has been immense such as AI can easily avoid human errors, improve decision-making, process data faster, and avoid repetitive tasks. Further, AI provides important insights to improve the designing, optimizing, and synthesising of drugs. There are several factors that are increasing the adoption of AI for drug discovery. Some of the most predominant ones include the rising incidences of chronic diseases and precision medicine, owing to the emerging approach to the prevention and treatment of diseases.
AI generates insights by leveraging sophisticated computation in precision medicine and inference, allowing the system to reason and learn, and empowering clinician decision-making through augmented intelligence. Furthermore, several market participants are increasing the precision of their drug portfolios, a process that has been seen to showcase increase in adoption of AI technologies.
For instance, in November 2022, AstraZeneca (UK) revealed that they are applying an 80% precision medicine approach to their biopharmaceutical portfolio. Hence, the increasing prevalence of chronic diseases, the emerging precision medicine approach based on AI technologies, and market players applying for precision medicine with the help of AI are increasing the adoption of AI for drug discovery.
Market Opportunities
Emerging economies are creating lucrative growth opportunities in the coming years for AI in drug discovery. The major market players, such as Microsoft Corporation (US), IBM Corporation (US), and Alphabet Inc. (US), are entering with advantages in developing regions. This is due to the huge population pool, a lack of awareness about health, the development of new diseases that require further research for drug development, and the rising incidences of chronic illnesses. According to the Department of Economic and Social Affairs' World Population Prospects 2022, population growth by 2100 is expected to be 10.4 billion. Moreover, in July 2022, as per the Pew Research Center, China had a greater population than Europe and the Americas, as well as a population roughly equivalent to that of Africa.
Moreover, increasing numbers of chronic diseases further increase the demand for developing effective drugs in less time. In September 2021, as per the World Health Organization, chronic diseases include cardiovascular diseases, followed by cancer, chronic respiratory diseases, and diabetes. 17.9 million people suffer from cardiovascular diseases annually. Furthermore, several start-ups in the private sector have raised significant funding for an AI-enabled drug discovery pipeline. For instance, in October 2022, Aqemia (France) raised USD 29.5 million in Series A funding in order to scale up drug discovery by combining quantum-inspired physics and machine learning. Hence, rising populations lead to a huge patient pool around the world, increasing chronic diseases further rising the demand for novel treatments, which further require AI for rapid drug discovery and rising investment in an AI-enabled drug discovery pipeline fuels market growth
Strategic Outlook and Future Directions
Impact on Supply Chain
The COVID-19 pandemic affected research activities in most parts of the world. The sectors, which include pharmaceutical and biopharmaceutical companies, clinical laboratories, and research and academic institutes, had to stop the ongoing drug discovery. This is due to the reduction in labor caused by the increasing COVID-19 infections and global restrictions on raw material export and import, which further impacted the supply chain. At the same time, the pharmaceutical and biotechnological industries were tirelessly working to discover the hit molecules for different variants of COVID-19. The urgency to develop a drug for COVID-19 increased after a few months of the COVID-19 outbreak. This further increases the demand for raw materials such as steel, plastic, or other materials to develop AI technology devices and machines used for drug discovery. This is because industries have begun to heavily rely on AI tools to identify precise targets for COVID-19 treatment. AI tools were the only hope that the pharmaceutical and biotechnological industries had to efficiently discover drug molecules for COVID-19 drugs in less time than conventional methods. This gradually recovered the AI supply chain in the drug discovery market until the end of 2020, after which the supply chain is moving at a rapid pace to discover drug molecules.
Impact on Service Demand
COVID-19 had a positive impact on the market demand for AI for drug discovery in 2020-2021. This was due to the high demand for the AI platform after a few months of the COVID-19 outbreak. The main reason for using AI platforms for COVID-19 drug discovery as well as other chronic diseases is that they save time, eliminate human errors, and allow for rapid drug development. Furthermore, there are companies that have increased the use of AI devices and machines for drug discovery due to the rising urgency of drugs, including Deargen (South Korea), Insilico Medicine (Hong Kong), Iktos (France), Benevolent AI (UK), and IBM (US). For instance, in April 2020, IBM (US) released novel AI-powered technologies in order to identify potential targets for creating a new drug molecule for COVID-19, which further fueled the market during the pandemic.
Impact on Market Players
The initial phase of COVID-19 was complex for market firms as COVID-19 infection numbers were continuously increasing. Countries that rely heavily on providing drug discovery services to other countries face restrictions. For instance, so many countries heavily rely on China for drug discovery services, as China has well-developed contract research organizations with AI-developed tools for drug discovery. Some companies, however, began to heavily rely on AI platforms to identify drug targets during the COVID-19 outbreak. The companies, including AstraZeneca (UK), Takeda (Japan), and Bristol-Myers Squibb (US), started to form strategic alliances, which further fuel AI in the drug discovery market. Furthermore, the COVID-19 outbreak had a positive impact on market players, as they chose almost AI tools to accelerate drug discovery in order to reduce drug development time.
Market Value by Segment (2030)
Value (USD Mn)
By Product And Service_Services
By Product And Service_Software
Companies
Key companies profiled in AI In Drug Discovery Market
Profiles of 109 companies operating in the AI In Drug Discovery Market market, including revenue, employee count, and market positioning where available.
Showing 109 of 109 companies
Exscientia
Exscientia
Healthcare
Company Headquarters: UK, Europe Founded: 2012 Workforce: ~ 500 Company Working: Exscientia is a global pharma tech company using patient-first AI, drug discovery, and design enterprise. The company offers its products under the category of the precision target, precision design, precision experiment, and precision medicine. Moreover, the company platform has delivered the first three AI-system to improve clinical outcome in oncology. The company has strong business presence in Europe region.
Revenue$0.0B
Employees500
Market CapN/A
Founded2011
UK, Europe
Benevolent
BenevolentAI
Healthcare
Company Headquarters: UK, Europe Founded: 2013 Workforce: 500 Company Working: BenevolentAI is a clinical-stage AI-enabled drug discovery and development company. Through the combined capabilities of its AI platform, scientific expertise, and web-lab facilities, Benevolent AI is well-established to deliver novel drug candidates with a higher probability of clinical success. Moreover, BenevolentAI powers a growing in-house pipeline of 13 named drug programmers, and it maintains collaboration with AstraZeneca (UK), as well as research and charitable institutions. The company offers its services under the category of pipeline, COVID-19, atopic dermatitis, and ulcerative colitis as well as company has a strong market presence in Europe.
RevenueN/A
Employees500
Market CapN/A
Founded2012
UK, Europe
Cyclica
Cyclica
Healthcare
Company Headquarters: Toronto, Canada Founded: 2013 Workforce: 200 Company Working: Cyclica is a data-driven drug discovery company. The company’s calculation method for polypharmacology is unique in the industry. Cyclica used a proteome-wide lens to measure novel and off-target interaction instantaneously. The company offers its product and services under the category of drug development, network pharmacology, drug repositioning, proteomics, clinical trials, side effects, bioinformatics, systems biology, drug discovery, artificial intelligence, polypharmacology, medicines, machine learning, pharmacology, pharmaceuticals, and bioinformatics. The company has a strong business presence in Canada.
RevenueN/A
Employees200
Market CapN/A
Founded2012
Toronto, Canada
Insilico M
Insilico Medicine
Healthcare
Company Headquarters: Hong Kong, China Founded: 2014 Workforce: 200 Company Working: Insilico Medicine is a technology company specializing in drug discovery and drug development processes. It offers products under the category of pharma.AI suite, pandaomics, chemistry42, and inclinico. The company is dedicated to expanding human productive longevity and transforming every step of the drug discovery and drug development process by best practices in biomarker discovery, drug development, digital medicine, and aging research. The company has a strong business presence in the US, China, Canada, UAE, Belgium, the UK, and Taiwan.
RevenueN/A
Employees200
Market CapN/A
Founded2013
Hong Kong, China
Deep Genom
Deep Genomics
Healthcare
Company Headquarters: Ontario, Canada Founded: 2015 Workforce: ~200 Company Working: Deep Genomics is a biotechnology company that builds proprietary Artificial Intelligence (AI) and uses it to discover new ways to correct the effects of genetic mutations and develop personalized therapies for individuals with rare Mendelian and complex diseases. It offers cell and molecular biology, clinical development, molecular genetics, organic chemistry, preclinical development, and other solutions. The company's AI platform generates billions of data points using throughput assays and sophisticated robotics systems and creates dozens of engineered and validated machine learning systems to support drug development. This allows researchers to categorize, rank, interpret, and link genetic variants, whether they are therapeutic or natural. Furthermore, Deep Genomics serves customers in Canada.
RevenueN/A
Employees200
Market CapN/A
Founded2014
Ontario, Canada
Atomwise I
Atomwise Inc.
Healthcare
Company Headquarters: California, US Founded: 2012 Workforce: ~ 63 Company Working: Atomwise Inc. (Atomwise) a creative pharmaceutical company, is revolutionizing the search for small-molecule drugs by utilizing AI. The platform for AI-based, structure-based drug development is offered by Atomwise. Deep learning neural networks are used by Atomwise to find new medications. The company achieved the highest outcomes in the world for toxicity detection, binding affinity prediction, and the development of novel pharmacological hits. With three lead-optimization efforts and more than 30 discovery programs, Atomwise is building a wholly owned pipeline of small-molecule pharmaceutical prospects. Additionally, the Bill and Melinda Gates Foundation (US) awarded the company a 2.3 USD million grant in 2020 to support the creation of numerous global health initiatives that will advance cutting-edge antimalarial and anti-tuberculosis small molecule therapies in conjunction with the foundation's extensive network. In addition, Atomwise predicts drug candidates for pharmaceutical companies, start-ups, and research institutions. It is currently using computational drug design to design drugs against COVID-19. The company operates in California US.
RevenueN/A
Employees63
Market CapN/A
Founded2011
California, US
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I have been reading the first document or the study, the Global HVAC and FP market report 2021 till 2026. Must say, good info! I have not gone in depth at all parts, but got a good indication of the data inside!
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Thanks for your great support. Appreciate it. Well received report. It helps us to understand market well. We're planning other area of survey in the future, let's keep in touch.
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Strategy & Business Development Director, Dogan Holding
We got the report in time, we really thank you for your support in this process. I also thank to all of your team as they did a great job.
Noah Malgeri
Co-Founder, Mojave Rail Fabrication Limited
This is really good guys. Excellent work on a tight deadline. I will continue to use you going forward and recommend you to others. Nice job.
Michael Robert
Manager, JavolVision
Thanks, I am so happy that we worked together. Maybe we still can work together in the future.
Joseph Aguayo
Sales Operations & Pricing Manager, Intel
Thanks. It's been a pleasure working with you, please use me as reference with any other Intel employees.
Bong Lau
Sales Leader, Bamberg
We bought your "2025 report" in 2020. Everything is fine and very good.
Peter Groot Koerkamp
Account and Business Manager, EFS-Holland BV
Thanks for sending the report it gives us a good global view of the Betaïne market.
Younghwan Choi
Senior Retail Manager, LG Chem
We found the report very insightful! we found your research firm very helpful. I'm sending this email to secure our future business.
Mark Irwin
Management Consultant, Level 21
I am very pleased with how market segments have been defined in a relevant way for my purposes (such as "Portable Freezers & refrigerators" and "last-mile"). In general the report is well structured. Thanks very much for your efforts.
Rob Kooiker
Group Product Manager HVAC & Fire Protection GMA, Rockwool
I have been reading the first document or the study, the Global HVAC and FP market report 2021 till 2026. Must say, good info! I have not gone in depth at all parts, but got a good indication of the data inside!
Jason Lee
R&D Director, Seojin
Thanks for your great support. Appreciate it. Well received report. It helps us to understand market well. We're planning other area of survey in the future, let's keep in touch.
Akif Moroglu
Strategy & Business Development Director, Dogan Holding
We got the report in time, we really thank you for your support in this process. I also thank to all of your team as they did a great job.
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