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Home » Healthcare » AI in Drug Discovery Market Size Share, Future Forecast [Latest]

AI in Drug Discovery Market By Offering (Hardware, Services, Software); By Therapeutic Area (Infectious Diseases, Cardiovascular Diseases, Metabolic Diseases, Oncology, Neurodegenerative Diseases, Others); By Application (Preclinical Testing, Drug Optimization & Repurposing, Others); By Geography, Segment revenue estimation, Forecast, 2023-2030.

Published On: Feb-2024   |   Base Year: 2021   |   No Of Pages: 150   |   Historical Data: 2017-2020   |   Formats: PDF   |   Report ID: 76500723

The AI in drug discovery Market is poised for significant growth, with a market size of USD 1.8 billion in 2022. At a CAGR) of 30.2%, the market is expected to reach USD 2.34 billion by 2023 and further balloon to USD 14.86 billion by 2030. Imagine a world where cures come quicker. AI in drug discovery is making that a reality. By analyzing mountains of data, AI helps identify potential new medications, paving the way for faster development.

 

Technology is essential to the pharmaceutical business, although its uses and priorities differ depending on the industry. AI is predicted to have a revolutionary impact on the pharmaceutical sector in the future, revolutionizing a number of areas, including medication development, discovery, and healthcare delivery.

 

Medicine development is a time- and money-consuming process; Taconic Biosciences estimates that bringing a medicine to market costs around $2.8 billion over more than 12 years. The drug development process can benefit from applying AI and machine learning at every stage. Compared to firms utilizing the technology in other healthcare sectors, those employing AI to expedite the drug-making process received some of the largest funding rounds, with healthcare AI startups raising over $2 billion in Q3 2020.

 

 The use of AI drug discovery platforms by pharmaceutical companies to expedite R&D procedures, save costs and timeframes for discovery, and improve overall productivity is becoming more prevalent. Promising advances in AI and machine learning offer a revolutionary opportunity for drug discovery, formulation, and dosage testing.

 

It is anticipated that investments, which currently have a value of about 100 billion dollars, will increase by 2000% by 2030 to reach approximately two trillion dollars. By 2025, about half of all healthcare organizations worldwide will adopt artificial intelligence tactics. AI and machine learning will continue to support medication development and production, and as these technologies become more widely available over time, they will inevitably find their way into pharmaceutical and industrial processes.

 

Currently, pharmaceutical companies are leveraging AI technology to develop larger molecules such as antibodies, proteins, gene therapies, and RNA-based treatments. These compounds accounted for 40% of new drug approvals in 2022 and are expected to become the mainstay of the biopharmaceutical industry's research and development pipeline in the future. As a result, AI is now being utilized to tackle even more complex challenges in drug discovery and development. A report published by BCG and the research funding organization Wellcome in June states that AI might result in "time and cost savings of at least 25–50%" in drug discovery up to the preclinical stage.

ai-in-drug-discovery-market-size.

Market Drivers (Precision Push: Personalized Medicine and the Rise of AI in Drug Discovery)

AI in the drug discovery market is growing significantly through machine learning algorithms to examine large amounts of data and the use of advanced personalized medicine.

  • With the introduction of AI, the process of identifying targets can be sped up by using machine learning (ML) algorithms to examine massive amounts of data. For instance, a machine learning system can assist in the analysis of extensive genomic data related to a disease, suggest possible therapeutic targets, and forecast the efficacy of the medication. In addition to finding possible therapeutic targets, machine learning algorithms can identify genetic biomarkers for illness diagnosis and prognosis by analyzing scientific literature. Artificial Intelligence can forecast the binding affinity of possible molecules to the target protein, which minimizes the number of compounds that require experimental screening. With a focus on tiny compounds, AI has started to impact the pharmaceutical industry in recent years. Since up to 90% of pharmaceutical revenues worldwide in 2021 came from small compounds, these little powerhouses are incredibly significant. AI has been utilized to forecast their safety, maximize their effectiveness, and predict how they will interact with their targets. As of now, AI is being used by companies to develop larger molecules such as antibodies, proteins, gene therapies, and RNA-based treatments. These molecules made up 40% of the new drug approvals in 2022 and are expected to be the future of the biopharma industry. AI is making significant strides in the field by applying the technology to even more challenging problems.

 

  • By evaluating unique patient data, such as genetic information and biomarkers, AI advances personalized treatment. This makes it possible to identify patient subgroups that might react differently to particular treatments, which could result in the development of more specialized and potent treatments. Artificial Intelligence examines genomic and molecular data from tumors in cancer treatment. This makes it possible to identify particular genetic changes that can direct the choice of targeted treatments. For instance, clinicians can choose individualized cancer treatment options with the help of IBM's Watson for Oncology, which uses genetic information. Furthermore, Artificial Intelligence is employed to evaluate empirical data, such as patient outcomes and electronic health records. By providing insight into how various patient groups react to therapies in practical contexts, this data helps in the development of more individualized treatment plans. A machine learning method trained to identify trends in data associated with CYP450 inhibition was implemented by Bristol-Myers Squibb. When CYP450 predictions were made using the algorithm, the failure rate was lowered by 6 times to 95%, as opposed to traditional approaches. These findings enable researchers to promptly exclude potentially harmful medications and concentrate on those with a higher chance of passing numerous human trials and receiving FDA approval.

 

Restraints (Key Restraints in AI-powered Drug Discovery)

  • There are a number of obstacles and restrictions that need to be considered, even with the potential advantages of AI in drug development. The availability of appropriate data is one of the main obstacles. Large amounts of data are usually needed for AI-based techniques to train them. Many times, there may be a limit to the amount of available data, or the data may need to be more consistent or of better quality, which may impact the precision and dependability of the findings.

  • Additionally, lack of standardization is another factor hampering the market growth rate. The data formats, data collection techniques, and data analysis processes used in drug discovery must be more standardized. This can limit the efficacy of AI in producing precise predictions and models by making it challenging to compare outcomes across various studies and datasets.

  • Understanding the workings of AI models and their predictions can be difficult due to their complex nature. This lack of transparency may hinder the use of AI in drug discovery, leading to doubts and mistrust.

 

Opportunity (A Golden Age of Discovery: Unveiling Opportunities in the AI-powered Drug Discovery Market)

With the use of current data, AI has the enormous potential to find and even create new treatment possibilities. AI can predict structure-function relationships for small-molecule medicines, find novel targets, and use molecular dynamics to test candidates. Similarly, it can anticipate the structure and function of proteins to find novel therapeutic targets. According to recent research, there could be a $50 billion opportunity if even small advances in drug development driven by AI could result in 50 more medicines over the course of ten years. In certain cases, AI may potentially save preclinical expenses by 20–40%. Businesses are spending a lot of money to seize this chance. In 2021, third-party funding for drug discovery facilitated by AI exceeded $5.2 billion. In the meantime, businesses like Alphabet and Nvidia have entered the drug research space, and biotechnology and pharmaceutical corporations are spending billions building their internal AI capabilities. Thus, cost reduction and rising investment will open up new growth opportunities in the near future.

ways-in-which-al-transforms-drug-discovery

Navigating the Segmented Landscape: A Look at AI in Drug Discovery Market Segmentation

The market for AI in drug discovery is segmented on the basis of offering, therapeutic area, application, and region. 

By Offering 

  • Hardware

  • Services

  • Software

 

By Therapeutic Area

  • Infectious Diseases

  • Cardiovascular Diseases

  • Metabolic Diseases

  • Oncology

  • Neurodegenerative Diseases

  • Others

 

By Application 

  • Preclinical Testing

  • Drug Optimization & Repurposing

  • Others

 

Exploring the AI in Drug Discovery Market by Region

North America

  • Canada 

  • United States

 

Asia Pacific

  • South Korea

  • China

  • Japan

  • India

  • Australia

  • Rest of APAC

 

Europe   

  • France

  • Germany

  • Spain

  • Italy

  • UK

  • Rest of Europe

 

Latin America 

  • Mexico

  • Brazil

  • Rest of Latin America

 

On the basis of offering, the software segment majorly ruled the market in 2022. Software driven by artificial Intelligence (AI) has completely changed the drug discovery process by speeding up the research and development phase. Artificial Intelligence (AI) evaluates large datasets, finds promising medication candidates, forecasts their effectiveness, and even creates new compounds using sophisticated algorithms and machine learning. This helps scientists to cut expenses and time by optimizing the drug discovery process. For instance, leading science and technology company Merck today announced the release of its AIDDISONTM drug discovery software, the first software-as-a-service platform that integrates the SynthiaTM retrosynthesis software application programming interface (API) to bridge the gap between virtual molecule design and real-world manufacturability.

 

On the basis of therapeutic area, the oncology segment dominated the market significantly, with a revenue share of nearly 24.5% in the year 2022. AI has a major impact on managing clinical trials and developing new drugs for cancer. Artificial Intelligence & machine learning are used to characterize tumors, identify early-stage cancers, locate specific types with precision, recommend the best course of treatment, and forecast individual patient responses to immunotherapy. Additionally, by properly predicting whether a given drug will successfully interact with a specific cancer-related protein, these techniques can help researchers expedite the drug discovery process. The ability of artificial intelligence systems to comprehend and evaluate vast amounts of imaging and non-imaging data may hasten the advancement of cancer therapies. For example, the biotech company Lantern Pharma, which specializes in oncology, has created a proprietary machine-learning platform that analyzes patient data, including genetic composition and health problems, to precisely match patients to cancer treatments. Similarly, Massive Bio introduced an AI-driven platform that helps doctors find more cancer therapy choices for their patients, such as recently authorized medications and ongoing clinical studies. The Institute of Cancer Research, in collaboration with IDIBELL and Vivan Therapeutics, is employing AI and Big Data to create new targeted cancer therapies that are resistant to medication, with a particular emphasis on KRAS, a well-known protein that drives cancer.

 

In terms of application, the drug optimization & repurposing sector led the market significantly, with a share of nearly 54.9% in the year 2022. AI is accelerating the drug discovery process, transforming drug optimization and repurposing. Machine learning algorithms analyze vast datasets containing biological, chemical, and clinical data to find and forecast the effectiveness of possible drug candidates. This facilitates the discovery of new therapeutic targets more quickly and increases the effectiveness of repurposing current medications for new uses. By considering unique patient features, AI-driven methods also support personalized medicine by enabling more accurate and efficient therapy. The use of AI in medication optimization and repurposing has enormous potential to increase the efficiency, success rates, and speed of drug development.

 

North America led the regional market, with a revenue share of nearly 59.2% in the year 2022. The market is growing significantly due to a rise in investments made by pharmaceutical and biotechnology businesses in these technologies. AI is transforming drug discovery in North America by speeding up the procedure, cutting expenses, and improving accuracy. Artificial intelligence (AI) tools, such as data analytics and machine learning, are being used to evaluate massive datasets, forecast possible therapeutic possibilities, improve lead compounds, and speed up the discovery of new targets. Innovation in the healthcare sector is promoted by incorporating AI technologies, which help researchers and pharmaceutical companies negotiate the difficulties of drug discovery with better speed and precision.

ai-in-drug-discovery-regional

Tech Titans and Pharma Giants: The Diverse Landscape of Key Players in AI Drug Discovery

  • GNS Healthcare

  • Exscientia

  • Euretos

  • Berg Health

  • Alphabet (DeepMind)

  • Atomwise

  • NVIDIA CORPORATION

  • Insitro

  • Microsoft Corporation

  • Schrödinger

  • Cloud Pharmaceuticals

  • TOMWISE INC.

  • BioSymetrics

  • IBM Watson

  • Cyclica Inc.

  • Benevolent AI

  • Other Key Players

 

parameter-impact-across-different-stages

What's New in AI Drug Discovery? Exploring Recent Advancements

  • In January 2023, Fujitsu Limited and the RIKEN Center for Computational Science's HPC- and AI-driven Drug Development Platform Division jointly developed an AI-based drug discovery technology that uses generative AI to predict 3D structural changes in proteins from electron microscope images. The technology can generate a 3D density map of proteins with high accuracy across a wide range of sizes.

 

  • In August 2023, Parexel, a clinical research organization, and Partex established a partnership to use AI-driven solutions to de-risk the assets in their portfolios and speed up drug development for biopharmaceutical clients globally. Drug developers seeking to ascertain the likelihood of clinical success for the assets in their portfolio and suggest additional disease indications for which their assets may be clinically viable are anticipated to benefit from Parexel's global experience in Phase I to IV clinical development as well as the big data and artificial intelligence capabilities of Partex, the data-to-drugs platform.

 

  • In November 2023, Accutar Biotechnology Inc. and Evommune, Inc. announced a new strategic partnership focused on discovering innovative small-molecule drug candidates for chronic inflammatory diseases. Accutar Biotechnology Inc. specializes in AI-empowered drug discovery, while Evommune, Inc. is a biotechnology company that discovers and develops new ways to treat immune-mediated inflammatory diseases. The partnership will use Accutar's in-house AI technology and Evommune's experience in creating cutting-edge oral small molecule medicines that address the underlying causes of chronic immune-mediated inflammatory illnesses.

Frequently Asked Question About This Report

The AI in drug discovery Market is poised for significant growth, with a market size of USD 1.8 billion in 2022. At a CAGR) of 30.2%, the market is expected to reach USD 2.34 billion by 2023 and further balloon to USD 14.86 billion by 2030. 

Trends in the AI in Drug Discovery Market include accelerating drug development timelines, increasing use of machine learning for target identification and compound screening, growing partnerships between AI firms and pharmaceutical companies, and enhanced precision in predicting drug efficacy and safety.

The software segment dominates the market because it provides advanced algorithms and data analysis tools crucial for accelerating drug discovery processes, improving accuracy, and reducing research costs.

In terms of application, the drug optimization & repurposing sector led the market significantly, with a share of nearly 54.9% in the year 2022.

On the basis of therapeutic area, the oncology segment dominated the market significantly, with a revenue share of nearly 24.5% in the year 2022. The largest share is due to the high prevalence of cancer, significant investment in cancer research, and the urgent need for innovative treatments, making it a prime area for applying AI-driven drug discovery.

North America led the regional market, with a revenue share of nearly 59.2% in the year 2022. The market is growing significantly due to a rise in investments made by pharmaceutical and biotechnology businesses in these technologies. AI is transforming drug discovery in North America by speeding up the procedure, cutting expenses, and improving accuracy.

The United States is leading in the AI in Drug Discovery Market, driven by its robust healthcare infrastructure, significant R&D funding, and concentration of major pharmaceutical and technology companies.

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Table of Contents

1.    EXECUTIVE SUMMARY
1.1. Market Attractiveness
1.2. Understanding the Target Customers
1.3. CXO perspective
1.4. Global AI in drug discovery Market, Historical Market Size & Future Projections Analysis
1.5. Global AI in drug discovery Market, By Offering
1.6. Global AI in drug discovery Market, By Therapeutic Area
1.7. Global AI in drug discovery Market, By Application
1.8. Global AI in drug discovery Market, By Region
2.    MARKET SHARE ANALYSIS
2.1. Top 10 Players with Revenue and Sales Volume
2.2. Market Share, 2024
3.    SALES VOLUME (METRIC TONNES), BY REGION
3.1. Europe (UK, Germany, France, Netherlands, Italy, Spain, Belgium, Sweden, Denmark, Norway, Aland Islands, Rest of Europe)
3.2. Asia (China, Japan, South Korea, India, Indonesia, Rest of Asia)
3.3. Middle-East (Israel, Saudi Arabia, UAE, Qatar, Egypt, Kuwait, Bahrain, and Others)
4.    INVESTMENT OPPORTUNITIES IN THE MARKET
4.1. On Going Market Developments
4.2. Merger & Acquisition Trends
4.3. Key Investment Opportunities
4.4. Most Potential Product Offering Segments from Growth and Investment Perspective
5.    MARKET INTRODUCTION
5.1. Definition
5.2. Scope of the Study
5.3. Market Structure
5.4. Macro Factor Indicator Analysis
5.5. Key findings
5.5.1. Top investment pockets
6.    RESEARCH METHODOLOGY
6.1. Research Process
6.2. Primary Research
6.3. Secondary Research
6.4. Market Size Estimation
6.5. Forecast Model
7.    MARKET DYNAMICS
7.1. Introduction
7.2. Drivers
7.3. Restraints
7.4. Opportunities
7.5. Challenges 
7.6. Covid 19 Impact Analysis
8.    GLOBAL AI in drug discovery MARKET ANALYSIS BY SEGMENT (REGION LEVEL ANALYSIS)
8.1. Overview
8.2. Global AI in drug discovery Historical Market size ($MILLION), Sales Volume, (2022 – 2032)
8.3. Global AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032)
8.4. Global AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Offering
8.4.1. Hardware
8.4.2. Services
8.4.3. Software
8.5. Global AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Therapeutic Area
8.5.1. Infectious Diseases
8.5.2. Cardiovascular Diseases
8.5.3. Metabolic Diseases
8.5.4. Oncology
8.5.5. Neurodegenerative Diseases
8.5.6. Others
8.6. Global AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Application
8.6.1. Preclinical Testing
8.6.2. Drug Optimization & Repurposing
8.6.3. Others
8.7. Global AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Geography
8.7.1. Asia 
8.7.2. North America
8.7.3. Europe
8.7.4. Middle East
9.    NORTH AMERICA AI in drug discovery MARKET ANALYSIS BY SEGMENT (REGION LEVEL ANALYSIS)
9.1. Overview
9.2. North America AI in drug discovery Historical Market size ($MILLION), Sales Volume, (2022 – 2032)
9.3. North America AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032)
9.4. North America AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Offering
9.4.1. Hardware
9.4.2. Services
9.4.3. Software
9.5. North America AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Therapeutic Area
9.5.1. Infectious Diseases
9.5.2. Cardiovascular Diseases
9.5.3. Metabolic Diseases
9.5.4. Oncology
9.5.5. Neurodegenerative Diseases 
9.5.6. Others
9.6. Global AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Application
9.6.1. Preclinical Testing
9.6.2. Drug Optimization & Repurposing
9.6.3. Others
9.7. North America Metabolic Diseases AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Geography 
9.7.1. USA
9.7.2. Canada
9.7.3. Rest of North America
10.    EUROPE GLOBAL AI in drug discovery MARKET ANALYSIS 
10.1. Overview
10.2. Europe AI in drug discovery Historical Market size ($MILLION), Sales Volume, (2022 – 2032)
10.3. Europe AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032)
10.4. Europe AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Offering
10.4.1. Hardware
10.4.2. Services
10.4.3. Software
10.5. Europe AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Therapeutic Area
10.5.1. Infectious Diseases
10.5.2. Cardiovascular Diseases
10.5.3. Metabolic Diseases
10.5.4. Oncology
10.5.5. Neurodegenerative Diseases
10.5.6. Others
10.6. Global AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Application
10.6.1. Preclinical Testing
10.6.2. Drug Optimization & Repurposing
10.6.3. Others
10.7. Europe AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Region
10.7.1. Germany
10.7.2. UK
10.7.3. France
10.7.4. Spain
10.7.5. Italy
10.7.6. Benelux
10.7.7. Rest of Europe
11.    ASIA PACIFIC AI in drug discovery MARKET ANALYSIS 
11.1. Overview
11.2. Asia Pacific AI in drug discovery Historical Market size ($MILLION), Sales Volume, (2022 – 2032)
11.3. Asia Pacific AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032)
11.4. Asia Pacific AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Offering
11.4.1. Hardware
11.4.2. Services
11.4.3. Software
11.5. Asia Pacific AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Therapeutic Area
11.5.1. Infectious Diseases
11.5.2. Cardiovascular Diseases
11.5.3. Metabolic Diseases
11.5.4. Oncology
11.5.5. Neurodegenerative Diseases
11.5.6. Others
11.6. Global AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Application
11.6.1. Preclinical Testing
11.6.2. Drug Optimization & Repurposing
11.6.3. Others
11.7. Asia Pacific AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Region
11.7.1. China
11.7.2. Japan
11.7.3. Korea
11.7.4. India
11.7.5. Indonesia
11.7.6. Rest of Asia
12.    REST OF THE WORLD AI in drug discovery MARKET ANALYSIS 
12.1. Overview
12.2. Rest of the World AI in drug discovery Market Historical Market size ($MILLION), Sales Volume, (2022 – 2032)
12.3. Rest of the World AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032)
12.4. Rest of the World AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Offering
12.4.1. Hardware
12.4.2. Services
12.4.3. Software
12.5. Rest of the World AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Therapeutic Area
12.5.1. Infectious Diseases
12.5.2. Cardiovascular Diseases
12.5.3. Metabolic Diseases
12.5.4. Oncology
12.5.5. Neurodegenerative Diseases
12.5.6. Others
12.6. Global AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Application
12.6.1. Preclinical Testing
12.6.2. Drug Optimization & Repurposing
12.6.3. Others
12.7. Rest of the World AI in drug discovery Market size ($MILLION), Sales Volume, and Forecasts (2024 – 2032), By Region
12.7.1. Latin America
12.7.2. Middle East
12.7.3. Africa   
13.    COMPANY PROFILES
13.1. GNS HEALTHCARE
13.1.1. Company Overview  
13.1.2. Company Snapshot  
13.1.3. Operating business segments
13.1.4. Product Offering offered and Revenue from Global AI in drug discovery Business
13.1.5. Key business performances, strategies and developments
13.2. EXSCIENTIA
13.2.1. Company Overview  
13.2.2. Company Snapshot  
13.2.3. Operating business segments
13.2.4. Product Offering offered and Revenue from Global AI in drug discovery Business
13.2.5. Key business performances, strategies and developments
13.3. EURETOS
13.3.1. Company Overview
13.3.2. Company Snapshot
13.3.3. Operating business segments
13.3.4. Product Offering offered and Revenue from Global AI in drug discovery Business
13.3.5. Key business performances, strategies and developments
13.4.  BERG HEALTH
13.4.1. Company Overview
13.4.2. Company Snapshot
13.4.3. Operating business segments
13.4.4. Product Offering offered and Revenue from Global AI in drug discovery Business
13.4.5. Key business performances, strategies and developments
13.5. NVIDIA CORPORATION
13.5.1. Company Overview
13.5.2. Company Snapshot
13.5.3. Operating business segments
13.5.4. Product Offering offered and Revenue from Global AI in drug discovery Business
13.5.5. Key business performances, strategies and developments
13.6. INSITRO
13.6.1. Company Overview
13.6.2. Company Snapshot
13.6.3. Operating business segments
13.6.4. Product Offering offered and Revenue from Global AI in drug discovery Business
13.6.5. Key business performances, strategies and developments
13.7. CLOUD PHARMACEUTICALS
13.7.1. Company Overview
13.7.2. Company Snapshot
13.7.3. Operating business segments
13.7.4. Product Offering offered and Revenue from Global AI in drug discovery Business
13.7.5. Key business performances, strategies and developments
13.8. ATOMWISE
13.8.1. Company Overview
13.8.2. Company Snapshot
13.8.3. Operating business segments
13.8.4. Product Offering offered and Revenue from Global AI in drug discovery Business
13.8.5. Key business performances, strategies and developments
13.9. SCHRÖDINGER
13.9.1. Company Overview
13.9.2. Company Snapshot
13.9.3. Operating business segments
13.9.4. Product Offering offered and Revenue from Global AI in drug discovery Business
13.9.5. Key business performances, strategies and developments
13.10. BENEVOLENT AI
13.10.1. Company Overview
13.10.2. Company Snapshot
13.10.3. Operating business segments
13.10.4. Product Offering offered and Revenue from Global AI in drug discovery Business
13.10.5. Key business performances, strategies and developments
13.11. BIOSYMETRICS
13.11.1. Company Overview
13.11.2. Company Snapshot
13.11.3. Operating business segments
13.11.4. Product Offering offered and Revenue from Global AI in drug discovery Business
13.11.5. Key business performances, strategies and developments
13.12. OTHER MARKET PLAYERS
13.12.1. Company Overview
13.12.2. Company Snapshot
13.12.3. Operating business segments
13.12.4. Product Offering offered and Revenue from Global AI in drug discovery Business
13.12.5. Key business performances, strategies and developments
LIST OF TABLES 
1. TABLE: MARKET, BY OFFERING, 2024-2032 (USD MILLION)
2. TABLE: MARKET FOR HARDWARE, BY REGION, 2024-2032 (USD MILLION)
3. TABLE: MARKET FOR SERVICES, BY REGION, 2024-2032 (USD MILLION)
4. TABLE: MARKET FOR SOFTWARE, BY REGION, 2024-2032 (USD MILLION)


5. TABLE: MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)
6. TABLE: MARKET FOR INFECTIOUS DISEASES, BY REGION, 2024-2032 (USD MILLION)
7. TABLE: MARKET FOR CARDIOVASCULAR DISEASES, BY REGION, 2024-2032 (USD MILLION)
8. TABLE: MARKET FOR METABOLIC DISEASES, BY REGION, 2024-2032 (USD MILLION)
9. TABLE: MARKET FOR ONCOLOGY, BY REGION, 2024-2032 (USD MILLION)
10. TABLE: MARKET FOR NEURODEGENERATIVE DISEASES, BY REGION, 2024-2032 (USD MILLION)
11. TABLE: MARKET FOR OTHERS, BY REGION, 2024-2032 (USD MILLION)

12. TABLE: MARKET, BY APPLICATION, 2024-2032 (USD MILLION)
13. TABLE: MARKET FOR PRECLINICAL TESTING, BY REGION, 2024-2032 (USD MILLION)
14. TABLE: MARKET FOR DRUG OPTIMIZATION & REPURPOSING, BY REGION, 2024-2032 (USD MILLION)
15. TABLE: MARKET FOR OTHERS, BY REGION, 2024-2032 (USD MILLION)

16. TABLE: MARKET, BY REGION, 2024-2032 (USD MILLION)
17. TABLE: NORTH AMERICA MARKET, BY REGION, 2024-2032 (USD MILLION)
18. TABLE: NORTH AMERICA MARKET, BY OFFERING, 2024-2032 (USD MILLION)
19. TABLE: NORTH AMERICA MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)
20. TABLE: NORTH AMERICA MARKET, BY APPLICATION, 2024-2032 (USD MILLION)


21. TABLE: USA MARKET BY OFFERING, 2024-2032 (USD MILLION)
22. TABLE: USA MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION) 
23. TABLE: USA MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 

24. TABLE: CALIFORNIA MARKET, BY OFFERING, 2024-2032 (USD MILLION)
25. TABLE: CALIFORNIA MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)
26. TABLE: CALIFORNIA MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 

27. TABLE: TEXAS MARKET BY OFFERING, 2024-2032 (USD MILLION)
28. TABLE: TEXAS MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)  
29. TABLE: TEXAS MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 

30. TABLE: FLORIDA MARKET, BY OFFERING, 2024-2032 (USD MILLION)
31. TABLE: FLORIDA MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)  
32. TABLE: FLORIDA MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 

33. TABLE: CANADA MARKET, BY OFFERING, 2024-2032 (USD MILLION)
34. TABLE: CANADA MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION) 
35. TABLE: CANADA MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 

36. TABLE: MEXICO MARKET, BY OFFERING, 2024-2032 (USD MILLION) 
37. TABLE: MEXICO MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION) 
38. TABLE: MEXICO MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 


39. TABLE: REST OF NORTH AMERICA MARKET, BY OFFERING, 2024-2032 (USD MILLION)
40. TABLE: REST OF NORTH AMERICA MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)
41. TABLE: NORTH AMERICA MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 


42. TABLE: EUROPE MARKET, BY REGION, 2024-2032 (USD MILLION)
43. TABLE: EUROPE MARKET, BY OFFERING, 2024-2032 (USD MILLION)
44. TABLE: EUROPE MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)
45. TABLE: EUROPE MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 
 

46. TABLE: UK MARKET, BY OFFERING, 2024-2032 (USD MILLION)
47. TABLE: UK MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)
48. TABLE: UK MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 


49. TABLE: SPAIN MARKET, BY OFFERING, 2024-2032 (USD MILLION)
50. TABLE: SPAIN MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)  
51. TABLE: SPAIN MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 


52. TABLE: BELGIUM MARKET, BY OFFERING, 2024-2032 (USD MILLION)
53. TABLE: BELGIUM MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION) 
54. TABLE: BELGIUM MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 


55. TABLE: SCANDINAVIAN MARKET, BY OFFERING, 2024-2032 (USD MILLION)
56. TABLE: SCANDINAVIAN MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION) 
57. TABLE: SCANDINAVIAN MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 


58. TABLE: GERMANY MARKET, BY OFFERING, 2024-2032 (USD MILLION)
59. TABLE: GERMANY MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)  
60. TABLE: GERMANY MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 


61. TABLE: FRANCE MARKET, BY OFFERING, 2024-2032 (USD MILLION) 
62. TABLE: FRANCE MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)
63. TABLE: FRANCE MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 

64. TABLE: ITALY MARKET, BY OFFERING, 2024-2032 (USD MILLION)
65. TABLE: ITALY MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION) 
66. TABLE: ITALY MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 

67. TABLE: REST OF EUROPE MARKET, BY OFFERING, 2024-2032 (USD MILLION)
68. TABLE: REST OF EUROPE MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)
69. TABLE: EUROPE MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 

70. TABLE: ASIA MARKET, BY OFFERING, 2024-2032 (USD MILLION) 
71. TABLE: ASIA MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)
72. TABLE: ASIA MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 


73. TABLE: CHINA MARKET, BY OFFERING, 2024-2032 (USD MILLION)
74. TABLE: CHINA MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)   
75. TABLE: CHINA MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 


76. TABLE: INDIA MARKET, BY OFFERING, 2024-2032 (USD MILLION) 
77. TABLE: INDIA MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION) 
78. TABLE: INDIA MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 


79. TABLE: JAPAN MARKET, BY OFFERING, 2024-2032 (USD MILLION)
80. TABLE: JAPAN MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)
81. TABLE: JAPAN MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 


82. TABLE: SOUTH KOREA MARKET, BY OFFERING, 2024-2032 (USD MILLION) 
83. TABLE: SOUTH KOREA MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)   
84. TABLE: SOUTH KOREA MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 


85. TABLE: INDONESIA MARKET, BY OFFERING, 2024-2032 (USD MILLION) 
86. TABLE: INDONESIA MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION) 
87. TABLE: INDONESIA MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 


88. TABLE: REST OF ASIA MARKET, BY OFFERING, 2024-2032 (USD MILLION) 
89. TABLE: REST OF ASIA MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION) 
90. TABLE: REST OF ASIA MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 


91. TABLE: REST OF THE WORLD MARKET, BY OFFERING,, 2024-2032 (USD MILLION)
92. TABLE: REST OF THE WORLD MARKET, BY THERAPEUTIC AREA, 2024-2032 (USD MILLION)  
93. TABLE: REST OF THE WORLD MARKET, BY APPLICATION, 2024-2032 (USD MILLION) 


94. TABLE: EXSCIENTIA: COMPANY SNAPSHOT
95. TABLE: EXSCIENTIA: OPERATING SEGMENTS
96. TABLE: EURETOS: COMPANY SNAPSHOT
97. TABLE: EURETOS: OPERATING SEGMENTS
98. TABLE: BERG HEALTH: COMPANY SNAPSHOT 
99. TABLE: BERG HEALTH: OPERATING SEGMENTS
100. TABLE: GNS HEALTHCARE COMPANY SNAPSHOT
101. TABLE: GNS HEALTHCARE OPERATING SEGMENTS
102. TABLE: NVIDIA CORPORATION: COMPANY SNAPSHOT
103. TABLE: NVIDIA CORPORATION: OPERATING SEGMENTS
104. TABLE: INSITRO: COMPANY SNAPSHOT
105. TABLE: INSITRO: OPERATING SEGMENTS
106. TABLE: CLOUD PHARMACEUTICALS: COMPANY SNAPSHOT
107. TABLE: CLOUD PHARMACEUTICALS: OPERATING SEGMENTS
108. TABLE: ATOMWISE: COMPANY SNAPSHOT
109. TABLE: ATOMWISE: OPERATING SEGMENTS
110. TABLE: SCHRÖDINGER: COMPANY SNAPSHOT
111. TABLE: SCHRÖDINGER: OPERATING SEGMENTS
112. TABLE: BENEVOLENT AI: COMPANY SNAPSHOT
113. TABLE: BENEVOLENT AI: OPERATING SEGMENTS


LIST OF FIGURES
1. Figure: Market: Research Methodology Steps
2. Figure: Research Design
3. Figure: Breakdown of Primaries: Market
4. Figure: Research Methodology: Hypothesis Building
5. Figure: Market: Product Offering and Service-Based Estimation
6. Figure: Top 10 Companies with Highest No. Of Patent in Last 9 Years
7. Figure: Growth Strategies Adopted by the Key Players
8. Figure: No. of Patents Granted Per Year, 2024–2032
9. Figure: Data Triangulation Methodology
10. Figure: Dominating Market Share, By Offering, 2024 vs. 2032 (USD MILLION)
11. Figure: Dominating Market Share, By Therapeutic Area, 2024 vs. 2032 (USD MILLION)
12. Figure: Dominating Market Share, By Application, 2024 vs. 2032 (USD MILLION)

13. Figure: Geographical Snapshot of the Market 
14. Figure: Software to Witness Higher Share in the Market for Offering Segment during the Forecast Period.
15. Figure: North America Accounted for the Largest Share of the Market, By Regional Basis, in 2024
16. Figure: Market: Drivers, Restraints, Opportunities, and Challenges
17. Figure: Asia: Market Snapshot
18. Figure: Europe: Market Snapshot
19. Figure: Middle East: Market Snapshot
20. Figure: Vendor Dive: Evaluation Overview
21. Figure: AI in drug discovery: Competitive Benchmarking  
22. Figure: Exscientia: Financial Overview (2024-2032)  
23. Figure: Euretos: Financial Overview (2024-2032)  
24. Figure: GNS HEALTHCARE Financial Overview (2024-2032)
25. Figure: NVIDIA CORPORATION: Financial Overview (2024-2032) 
26. Figure: Insitro: Financial Overview (2024-2032)
27. Figure: Atomwise: Financial Overview (2024-2032) 
28. Figure: Schrödinger: Financial Overview (2024-2032) 
29. Figure: Benevolent AI: Financial Overview (2024-2032)