Artificial Intelligence / AI in Drug Discovery Market

Artificial Intelligence / AI in Drug Discovery Market by Offering, Process (Target selection, Validation, Lead generation, optimization), Drug Design (Small molecule, Vaccine, Antibody, PK/PD), Dry Lab, Wet Lab (Single Cell analysis) & Region - Global Forecast to 2028

Report Code: HIT 7445 Nov, 2023, by marketsandmarkets.com

The global AI in drug discovery market in terms of revenue was estimated to be worth $0.9 billion in 2023 and is poised to reach $4.9 billion by 2028, growing at a CAGR of 40.2% from 2023 to 2028. The new research study consists of an industry trend analysis of the market. The new research study consists of industry trends, pricing analysis, patent analysis, conference and webinar materials, key stakeholders, and buying behaviour in the market. The integration of Artificial Intelligence (AI) into the domain of drug discovery is poised to significantly fortify the market landscape. AI accelerates research by optimizing experiments, emphasizing impactful targets, and enabling virtual screening, leading to faster failure and diversified testing. AI can transform drug discovery workflows, consolidating steps, automating processes, reducing in-process decision-making, and accelerating property optimization in parallel. Development of epitope selection, prediction and binding tools, resulting in significant acceleration of the discovery of new vaccines and other therapeutics. However, AI algorithms may lack the nuanced understanding and creative insight that experienced researchers possess. The depth, dimensionality, and scale are often too limited for the application of AI to better characterize diseases. There may be challenges such as missing metadata on cell culture conditions or assay conditions beyond experimental outcomes and others. The use of AI raises ethical questions, particularly around data privacy, bias, and transparency in decision-making, are some of the factors expected to restrain the growth of this market in the coming years.

Attractive Opportunities in AI in Drug Discovery Market

AI in Drug Discovery Market

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AI in Drug Discovery Market

AI in Drug Discovery Market Dynamics

Driver: Growing need to control drug discovery & development costs and reduce time involved in drug development

Drug discovery is a very costly and lengthy process, owing to which there is a need for alternative tools for discovering new drugs. Drug discovery and development are commonly conducted through in vivo and in vitro methods, which are very costly and time-consuming. It typically takes a staggering 10–15 years and costs up to USD 2.8 billion on average, to develop a new drug, while an astonishing proportion (80–90%) of them fail in the clinic, with Phase II proof-of-concept (PoC) trials accounting for the most significant number of clinical failures. Although the number of new molecular entities (NMEs) approved by regulatory agencies, such as the US Food and Drug Administration (FDA), has increased over the past decade (2010–2019) compared with the prior decade, the cost of bringing a new drug to market has risen precipitously. The key drivers contributing to the increased cost of pharmaceutical innovation include investment lost from late-stage clinical attrition, an increasingly stringent regulatory system that sets a high bar for approval, and higher clinical trial costs, especially for pivotal trials. Given these realities, pharmaceutical and biotech companies are incentivized to innovate and adopt new technologies to improve productivity, cut costs, and ensure sustainability.

In the drug discovery process, only one out of 5,000–10,000 compounds are approved as a potential drug for a particular condition. AI in drug discovery has the potential to significantly reduce the time and costs associated with bringing new drugs to market. It can also help identify novel treatments for diseases that were previously difficult to target.

Several players operating in this market are developing platforms that can help in the rapid discovery of drugs. For instance, in May 2023 Google Cloud launched two new AI-powered solutions, the Target and Lead Identification Suite, and the Multiomics Suite, to accelerate drug discovery and precision medicine for biotech companies, pharmaceutical firms, and public sector organizations. The Target and Lead Identification Suite enables more efficient in silico drug design, predicting protein structures and accelerating lead optimization for drug discovery. The two new Google Cloud suites help address a long-standing issue in the biopharma industry: the lengthy and costly process of bringing a new medicine to the US market. Several businesses, including Big Pharma’s Pfizer have already started using the products. Simarly, in March 2023, Insilico Medicine integrated a specialized AI chat feature, ChatPandaGPT, into its PandaOmics platform. This integration enables researchers to have natural language conversations with the platform, facilitating the discovery of potential therapeutic targets and biomarkers in a more efficient manner. The new feature allows researchers to have natural language conversations with the platform and analyze large datasets to discover potential therapeutic targets and biomarkers more efficiently.

Restraint: Shortage of AI workforce and ambiguous regulatory guidelines for medical software

AI is a complex system, and for developing, managing, and implementing AI systems, companies require a workforce with certain skill sets. For instance, personnel dealing with AI systems should be aware of technologies such as cognitive computing, ML and machine intelligence, deep learning, and image recognition. Developing and deploying AI tools in drug discovery demands a blend of domain-specific expertise and data science skills. Both academia and industry face challenges due to a lack of subject matter expertise, difficulties in team formation, and organizational silos hindering collaboration. As AI becomes more integrated into large organizations, these issues may worsen, necessitating increased training and skill-building for both AI and drug discovery experts to bridge current capability gaps and support interdisciplinary teamwork in the future.

AI service providers are facing challenges regarding deploying/servicing their solutions at their customer sites. This is because of the lack of technology awareness and shortage of AI experts. Also, it is a perplexing task for any government or regulatory agency to keep up with these advancements and meaningfully guide the deployment of AI systems, especially in healthcare applications. The accuracy, reliability, security, and clinical use of medical AI technologies are ensured by subjecting them to a combination of standards and regulations. To receive FDA approval, AI or machine learning tools that have applications in healthcare must pass a series of tests to show that they can produce results at least as accurately as humans are currently able to produce. Similarly, in the European Union, there is no general exclusion for software, and software may be regulated as a medical device if it has a medical purpose. Generally, a case-by-case assessment is required, taking into account the product characteristics, mode of use, and claims made by the manufacturer. However, the assessment is particularly complex because, unlike the classification of general medical devices, it is not immediately apparent how these parameters apply to software, given that software does not act on the human body to restore, correct, or modify bodily functions

Opportunity: Emerging Markets

The Al in drug discovery market is poised for expansion, with emerging economies like India, China, and Middle Eastern nations presenting promising growth prospects. This is primarily attributed to the robust growth in their pharmaceutical and biopharmaceutical sectors, relaxed regulatory policies, and access to a skilled, cost-effective workforce. These countries are anticipated to witness a substantial surge in pharmaceutical demand due to the escalating prevalence of chronic and infectious diseases, rising income levels, and improvements in healthcare infrastructure. Consequently, these markets are highly appealing to companies facing profit margin challenges in mature markets, patent expirations of drugs, and escalating regulatory complexities. Additionally, the burgeoning interest of pharmaceutical firms in outsourcing drug discovery services, driven by the increasing demand for vaccines, diminishing antibiotic pipelines, and surging research and development expenses, further bolsters the growth of drug discovery services within emerging markets.

Challenge: Limited availability of data sets

For the use of AI and machine learning at their full potential, large sets of quality data are required to get the desired outcomes. Large data sets allow machine learning to capture patterns and generate novel hypotheses. However, in the drug discovery and development field, generating data is very expensive.

The majority of valuable data that holds significance for drug discovery is compartmentalized within pharmaceutical and CRO (clinical research organization) entities, particularly those that have accumulated exclusive data over many years. This data is usually regarded as precious, confidential resources that provide a competitive edge to these organizations. Consequently, startups and smaller companies are frequently compelled to rely on publicly accessible data, such as information from peer-reviewed reports, which may frequently be of poor quality. Therefore, it becomes difficult for SMEs to afford to make numerous molecules and conduct biological tests on the same. On the other hand, even though large pharmaceutical and biotechnology companies generate a large volume of data, most of it is protected. These companies adhere to a strict code of secrecy and do not pool or release their data with other parties. This is a key challenge in the market.

The depth, dimensionality, and scale are often too limited for the application of AI to better characterize diseases. There may be challenges such as missing metadata on cell culture conditions or assay conditions beyond experimental outcomes and others. Efforts like Ochre Bio's deep phenotyping approach for liver disease show promise but require patient samples and face scalability challenges across disease types. Moreover, proprietary datasets often contain high-quality data for a given use case (e.g., use cases pertaining to large-scale small molecule synthesis or safety and toxicity use cases), but lack of access to these datasets can significantly hinder the development of tools within academia. Tools developed in an academic setting, using publicly available data, are sometimes less accurate.

AI in Drug Discovery Market Ecosystem

The aspects present in this market are included in the ecosystem market map of the overall artificial intelligence (AI) in drug discovery, and each element is defined with a list of the organizations involved. Products and services are included. The manufacturers of various products include the organizations involved in the entire process of research, product development, optimization, and launch. Vendors provide the services to end users either directly or through a collaboration with a third party.

In-house research facilities, contract research organizations, and contract development and manufacturing companies are all part of research and product development and are essential for outsourcing product development services.

AI in Drug Discovery Market Ecosystem

Source: Secondary Literature, Interviews with Experts, and MarketsandMarkets Analysis

The global AI in drug discovery market is segmented by offering, technology, therapeutic ares, process, use case, end user, and region.

The understanding disease segment of the AI in drug discovery industry expected to grow at the highest CAGR during the forecast period

The understanding disease segment projected to be the fastest-growing market of the global AI in drug discovery market from 2023 to 2028. AI plays a crucial role in drug discovery by identifying and validating new targets for disease treatment. It automates image analysis from phenotypic screens, mines -omics data (proteomics, genomics) to understand target-disease interactions, models protein dynamics to study target-disease pathways, and identifies biomarkers to categorize patient populations for drug research. These applications enhance the understanding of diseases and facilitate the development of more effective and targeted drug therapies. The use of AI for data mining of (-omics) data to link targets to diseases and drug repurposing applications are driving the growth of this market.

Deep learning: The largest segment of the AI in drug discovery industry for machine learning, by type

The deep learning segment expected to dominate the global AI in drug discovery market for machine learning, by type, during the forecast. Deep learning, a subset of machine learning, is distinguished by its exceptional ability to extract intricate patterns and insights from vast and complex datasets, such as genomics, proteomics, and chemical structures, crucial to drug discovery. Deep learning involves using neural networks to analyze complex biological data, predict drug interactions, and identify potential candidates. It accelerates target identification, compound screening, and clinical trial optimization, leading to faster, cost-effective drug development and more precise personalized medicine.

Infectious diseases: The largest segment of the AI in drug discovery industry, by therapeutic area

The AI in drug discovery market, by therapeutic area is categorized as oncology, infectious diseases, neurology, metabolic, cardiovascular, immunology, and other therapeutic areas. The infectious diseases accounted for the second largest share of the global market during the forecast period. Majority of the focus is concentrated in diseases where significant commercial incentives exist or with easy access to philanthropic funding. Infectious disease such as COVID-19, malaria, tuberculosis, and HIV, receive majority of the focus and funding and less interest expressed on other infectious diseases including neglected tropical diseases (NTDs).

North America is expected to account for the largest share in AI in drug discovery industry in 2022

Based on region, the global market has been segmented into North America, Europe, Asia Pacific, South America, and the Middle East & Africa. In 2022, North America accounted for the largest market share followed by Europe and Asia Pacific. The large share of North America can be attributed to the increasing research funding, government initiatives for promoting precision medicine in the US, and increasing adoption of AI-based tools in R&D for drug discovery among major pharmaceutical companies in the US. The region's commitment to fostering innovation through collaborations between academia, industry, and technology providers further bolsters its position in the AI in drug discovery market.

AI in Drug Discovery Market by Region

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Some of the prominent players are NVIDIA Corporation (US), Exscientia (UK), BenevolentAI (UK), Recursion (US), Insilico Medicine (US), Schrödinger, Inc. (US), Microsoft Corporation (US), Google (US), Atomwise Inc. (US), Illumina, Inc. (US), NuMedii, Inc. (US), XtalPi Inc. (US), Iktos (France), Tempus Labs (US), Deep Genomics, Inc. (Canada), Verge Genomics (US), BenchSci (Canada), Insitro (US), Valo Health (US), BPGbio, Inc. (US), IQVIA Inc (US), Labcorp (US), Tencent Holdings Limited (China), Predictive Oncology, Inc. (US), Celsius Therapeutics (US), CytoReason (Israel), Owkin, Inc. (US), Cloud Pharmaceuticals (US), Evaxion Biotech (Denmark), Standigm (South Korea), BIOAGE (US), Envisagenics (US), and Aria Pharmaceuticals, Inc. (US). These players are increasingly focusing on as product launches and enhancements, investments, partnerships, collaborations, joint ventures, funding, acquisition, expansions, agreements, sales contracts, and alliances to strengthen their presence in the global market.

Scope of the AI in Drug Discovery Industry

Report Metric

Details

Market Revenue in 2023

$0.9 billion

Projected Revenue by 2028

$4.9 billion

Revenue Rate

Poised to Grow at a CAGR of 40.2%

Market Driver

Growing need to control drug discovery & development costs and reduce time involved in drug development

Market Opportunity

Emerging Markets

The study categorizes the AI in drug discovery market to forecast revenue and analyze trends in each of the following submarkets:

By Offering

  • Software
  • Services

By Technology

  • Machine Learning
    • Deep Learning
    • Supervised Learning
    • Reinforcement Learning
    • Unsupervised Learning
    • Other Machine Learning Technologies
  • Natural Language Processing
  • Context-aware Processing
  • Other Technologies

By Therapeutic Area

  • Oncology
  • Infectious Diseases
  • Neurology
  • Metabolic Diseases
  • Cardiovascular Diseases
  • Immunology
  • Other Therapeutic Areas

By Process

  • Target Identification & Selection
  • Target Validation
  • Hit Identification & Prioritization
  • Hit-to-lead Identification/ Lead generation
  • Lead Optimization
  • Candidate Selection & Validation

By Use Cases

  • Understanding Disease
  • Small Molecule Design and Optimization
  • Vaccine Design and Optimization
  • Antibody & Other Biologics Design and Optimization
  • Safety and Toxicity

By End User

  • Pharmaceutical & Biotechnology Companies
  • Contract Research Organizations
  • Research Centers and Academic & Government Institutes

By Region

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • France
    • Italy
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Rest of Asia Pacific
  • South America
  • Middle East & Africa

Recent Developments of AI in Drug Discovery Industry

  • In October 2023, Recursion, in collaboration with Roche and Genentech, achieved its first significant milestone by identifying and validating a hit series for a specific disease, triggering Roche's Small Molecule Validation Program Option. Recursion would lead the program's advancement using its Recursion OS and digital chemistry tools. This marked progress in their joint efforts to develop therapeutic programs based on Maps of Biology and Chemistry, with plans to expand to multiple CNS cell types for novel target hypotheses and partnerships in the future.
  • In September 2023, Exscientia entered into a collaboration with Merck KGaA focused on the discovery of novel small molecule drug candidates across oncology, neuroinflammation and immunology. The multi-year collaboration will utilize Exscientia’s AI-driven precision drug design and discovery capabilities while leveraging Merck KGaA’s disease expertise in oncology and neuroinflammation, clinical development capabilities and global footprint.
  • In May 2023, Google Cloud launched two new AI-powered solutions, the Target and Lead Identification Suite, and the Multiomics Suite, to accelerate drug discovery and precision medicine for biotech companies, pharmaceutical firms, and public sector organizations. The Target and Lead Identification Suite enables more efficient in silico drug design, predicting protein structures and accelerating lead optimization for drug discovery.
  • In May 2023, 9xchange partnered with BenevolentAI. The partnership aimed to leverage BenevolentAI's AI-enabled technology to support decision-making related to indication expansion and drug repurposing for assets within the 9xchange platform. By combining BenevolentAI's proven AI-enabled engine with the 9xchange platform, the partnership aimed to uncover untapped potential in therapeutic portfolios, create new opportunities for drug discovery.
  • In March 2023, NVIDIA launched the BioNeMo Cloud service, expanding its generative AI cloud offerings to aid drug discovery and research in genomics, chemistry, biology, and molecular dynamics. The BioNeMo Cloud service allows researchers to fine-tune AI applications on their proprietary data and run AI model inference in web browsers or through cloud APIs.

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TABLE OF CONTENTS
 
1 INTRODUCTION (Page No. - 38)
    1.1 STUDY OBJECTIVES 
    1.2 MARKET DEFINITION 
           1.2.1 INCLUSIONS AND EXCLUSIONS
    1.3 MARKET SCOPE 
           1.3.1 MARKET SEGMENTATION
                    FIGURE 1 AI IN DRUG DISCOVERY MARKET: MARKET SEGMENTATION
           1.3.2 REGIONAL SCOPE
           1.3.3 YEARS CONSIDERED
           1.3.4 CURRENCY CONSIDERED
                    TABLE 1 EXCHANGE RATES UTILIZED FOR CONVERSION TO USD
    1.4 STAKEHOLDERS 
    1.5 SUMMARY OF CHANGES 
           1.5.1 RECESSION IMPACT
 
2 RESEARCH METHODOLOGY (Page No. - 45)
    2.1 RESEARCH DATA 
          FIGURE 2 RESEARCH DESIGN
    2.2 SECONDARY SOURCES 
           2.2.1 KEY DATA FROM SECONDARY SOURCES
    2.3 PRIMARY DATA 
           2.3.1 PRIMARY SOURCES
                    2.3.1.1 Key data from primary sources
                    2.3.1.2 Key industry insights
           2.3.2 BREAKDOWN OF PRIMARY INTERVIEWS
                    FIGURE 3 BREAKDOWN OF PRIMARY INTERVIEWS: BY DEMAND SIDE, SUPPLY SIDE, DESIGNATION, AND REGION
    2.4 MARKET SIZE ESTIMATION 
          FIGURE 4 SUPPLY-SIDE MARKET ESTIMATION: REVENUE SHARE ANALYSIS
          FIGURE 5 BOTTOM-UP APPROACH: END-USER SPENDING ON AI IN DRUG DISCOVERY
          TABLE 2 FACTOR ANALYSIS
          FIGURE 6 CAGR PROJECTIONS FROM ANALYSIS OF DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES (2022–2027)
          FIGURE 7 CAGR PROJECTIONS: SUPPLY-SIDE ANALYSIS
          FIGURE 8 TOP-DOWN APPROACH
    2.5 MARKET BREAKDOWN AND DATA TRIANGULATION 
          FIGURE 9 DATA TRIANGULATION METHODOLOGY
    2.6 ASSUMPTIONS 
           2.6.1 MARKET SIZING ASSUMPTIONS
           2.6.2 OVERALL STUDY ASSUMPTIONS
    2.7 LIMITATIONS 
    2.8 RISK ASSESSMENT 
          TABLE 3 RISK ASSESSMENT: AI IN DRUG DISCOVERY MARKET
    2.9 RECESSION IMPACT ANALYSIS 
          TABLE 4 GLOBAL INFLATION RATE PROJECTIONS, 2021–2027 (% GROWTH)
          TABLE 5 US HEALTH EXPENDITURE, 2019–2022 (USD MILLION)
          TABLE 6 US HEALTH EXPENDITURE, 2023–2027 (USD MILLION)
 
3 EXECUTIVE SUMMARY (Page No. - 63)
    FIGURE 10 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2023 VS. 2028 (USD MILLION)
    FIGURE 11 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2023 VS. 2028 (USD MILLION)
    FIGURE 12 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2023 VS. 2028 (USD MILLION)
    FIGURE 13 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2023 VS. 2028 (USD MILLION)
    FIGURE 14 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2023 VS. 2028 (USD MILLION)\
    FIGURE 15 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2023 VS. 2028 (USD MILLION)
    FIGURE 16 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET: GEOGRAPHICAL SNAPSHOT
 
4 PREMIUM INSIGHTS (Page No. - 68)
    4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AI IN DRUG DISCOVERY MARKET 
          FIGURE 17 GROWING NUMBER OF CROSS-INDUSTRY COLLABORATIONS & PARTNERSHIPS TO DRIVE MARKET
    4.2 AI IN DRUG DISCOVERY MARKET: REGIONAL LANDSCAPE 
          FIGURE 18 NORTH AMERICA TO DOMINATE AI IN DRUG DISCOVERY MARKET DURING FORECAST PERIOD
    4.3 AI IN DRUG DISCOVERY MARKET: GEOGRAPHIC GROWTH OPPORTUNITIES 
          FIGURE 19 US TO REGISTER HIGHEST REVENUE GROWTH FROM 2023 TO 2028
    4.4 NORTH AMERICAN AI IN DRUG DISCOVERY MARKET, BY END USER & COUNTRY, 2022 
          FIGURE 20 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES AND US HELD LARGEST SHARE IN NORTH AMERICA, 2022
    4.5 AI IN DRUG DISCOVERY MARKET, BY OFFERING 
          FIGURE 21 SERVICES TO HOLD MAJORITY MARKET SHARE IN 2028
    4.6 AI IN DRUG DISCOVERY MARKET, BY TECHNOLOGY 
          FIGURE 22 MACHINE LEARNING TO RETAIN MARKET LEADERSHIP TILL 2028
    4.7 AI IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA 
                    FIGURE 23 ONCOLOGY TO DOMINATE MARKET IN 2028
    4.8 AI IN DRUG DISCOVERY MARKET, BY PROCESS 
          FIGURE 24 HIT-TO LEAD IDENTIFICATION/LEAD GENERATION TO DOMINATE MARKET IN 2028
    4.9 AI IN DRUG DISCOVERY MARKET, BY USE CASE 
          FIGURE 25 SMALL MOLECULE DESIGN & OPTIMIZATION TO REGISTER HIGHEST GROWTH OVER FORECAST PERIOD
    4.10 AI IN DRUG DISCOVERY MARKET, BY END USER 
           FIGURE 26 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES TO ACCOUNT FOR LARGEST MARKET SHARE IN 2028
 
5 MARKET OVERVIEW (Page No. - 74)
    5.1 INTRODUCTION 
    5.2 MARKET DYNAMICS 
          FIGURE 27 AI IN DRUG DISCOVERY: MARKET DYNAMICS
          TABLE 7 AI IN DRUG DISCOVERY MARKET: IMPACT ANALYSIS
           5.2.1 DRIVERS
                    5.2.1.1 Growing cross-industry collaborations and partnerships
                                TABLE 8 INDICATIVE LIST OF COLLABORATIONS AND PARTNERSHIPS (2021−2023)
                    5.2.1.2 Growing need to reduce time and cost of drug discovery and development
                    5.2.1.3 Patent expiry of several drugs
                                TABLE 9 INDICATIVE LIST OF DRUGS LOSING PATENTS IN 2023
           5.2.2 RESTRAINTS
                    5.2.2.1 Shortage of AI workforce and ambiguous regulatory guidelines for medical software
           5.2.3 OPPORTUNITIES
                    5.2.3.1 Growing biotechnology industry
                    5.2.3.2 Emerging markets
                    5.2.3.3 Focus on developing human-aware AI systems
           5.2.4 CHALLENGES
                    5.2.4.1 Limited availability of data sets
                    5.2.4.2 Lack of required tools and usability
 
6 INDUSTRY INSIGHTS (Page No. - 82)
    6.1 OVERVIEW OF KEY INDUSTRY TRENDS 
           6.1.1 EVOLUTION OF AI IN DRUG DISCOVERY
                    FIGURE 28 EVOLUTION OF AI IN DRUG DISCOVERY MARKET
           6.1.2 COMPUTER-AIDED DRUG DESIGN AND AI
                    FIGURE 29 STRUCTURE-BASED DRUG DESIGNING: AI IN DRUG DISCOVERY MARKET
    6.2 SUPPLY CHAIN ANALYSIS 
          FIGURE 30 AI IN DRUG DISCOVERY MARKET: SUPPLY CHAIN ANALYSIS (2022)
    6.3 PORTER’S FIVE FORCES ANALYSIS 
          TABLE 10 AI IN DRUG DISCOVERY MARKET: PORTER’S FIVE FORCES ANALYSIS
           6.3.1 INTENSITY OF COMPETITIVE RIVALRY
           6.3.2 BARGAINING POWER OF BUYERS
           6.3.3 BARGAINING POWER OF SUPPLIERS
           6.3.4 THREAT OF SUBSTITUTES
           6.3.5 THREAT OF NEW ENTRANTS
    6.4 ECOSYSTEM/MARKET MAP 
          FIGURE 31 AI IN DRUG DISCOVERY MARKET ECOSYSTEM
    6.5 TECHNOLOGY ANALYSIS 
          FIGURE 32 AI IN DRUG DISCOVERY MARKET: CLASSIFICATION
           6.5.1 DRY LAB SERVICES
           6.5.2 WET LAB SERVICES
                    6.5.2.1 Chemistry services
                    6.5.2.2 BIOLOGICAL SERVICES
                               6.5.2.2.1 Single-cell analysis
    6.6 PRICING ANALYSIS 
           6.6.1 AVERAGE SELLING PRICE TRENDS, BY REGION
           6.6.2 INDICATIVE PRICING ANALYSIS, BY PROCESS
                    TABLE 11 AI IN DRUG DISCOVERY MARKET: INDICATIVE PRICING, BY PROCESS
    6.7 BUSINESS MODELS 
          FIGURE 33 AI IN LIFE SCIENCES: BUSINESS MODELS
          FIGURE 34 BENEFITS OF HYBRID BUSINESS MODELS
          FIGURE 35 SPECIALIZATION OF AI COMPANIES OVER TIME
    6.8 CASE STUDY ANALYSIS 
           6.8.1 CASE STUDY 1: BRISTOL MYERS SQUIBB AND EXSCIENTIA
           6.8.2 CASE STUDY 2: APEIRON LLC AND EXSCIENTIA
    6.9 REGULATORY ANALYSIS 
           6.9.1 AI IN DRUG DISCOVERY MARKET: REGULATORY LANDSCAPE, BY REGION
           6.9.2 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
                    TABLE 12 LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    6.10 PATENT ANALYSIS 
           FIGURE 36 TOP PATENT OWNERS AND APPLICANTS FOR AI IN DRUG DISCOVERY SOLUTIONS (JANUARY 2011–OCTOBER 2023)
           FIGURE 37 AI IN DRUG DISCOVERY MARKET: PATENT ANALYSIS (JANUARY 2011–OCTOBER 2023)
           FIGURE 38 TOP APPLICANT COUNTRIES/REGIONS FOR AI IN DRUG DISCOVERY PATENTS (JANUARY 2012–JULY 2023)
           TABLE 13 LIST OF PATENTS/PATENT APPLICATIONS IN AI IN DRUG DISCOVERY MARKET, 2021–2023
    6.11 KEY CONFERENCES & EVENTS (Q1 2023–Q2 2024) 
    6.12 TRENDS/DISRUPTIONS IMPACTING CUSTOMERS’ BUSINESSES 
           FIGURE 39 REVENUE SHIFT IN AI IN DRUG DISCOVERY MARKET
    6.13 KEY STAKEHOLDERS & BUYING CRITERIA 
           6.13.1 KEY STAKEHOLDERS IN BUYING PROCESS
                     FIGURE 40 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS OF AI IN DRUG DISCOVERY MARKET
           6.13.2 BUYING CRITERIA FOR AI IN DRUG DISCOVERY MARKET
                     FIGURE 41 KEY BUYING CRITERIA FOR END USERS
    6.14 AI-DERIVED CLINICAL ASSETS 
          TABLE 14 KEY AI-DERIVED CLINICAL ASSETS, BY COMPANY
    6.15 UNMET NEEDS 
           6.15.1 UNMET NEEDS IN AI IN DRUG DISCOVERY
           6.15.2 SINGLE-CELL ANALYSIS LANDSCAPE: KEY CHALLENGES AND PAIN POINTS IN DRUG DISCOVERY
           6.15.3 KEY UNMET NEEDS AND PAIN POINTS FOR AI APPLICATIONS IN SINGLE-CELL ANALYSIS FOR DRUG DISCOVERY
 
7 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING (Page No. - 123)
    7.1 INTRODUCTION 
          TABLE 15 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
    7.2 SERVICES 
           7.2.1 SERVICES SEGMENT TO WITNESS HIGHEST GROWTH
                    TABLE 16 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR SERVICES, BY COUNTRY, 2021–2028 (USD MILLION)
    7.3 SOFTWARE 
           7.3.1 BENEFITS OF SOFTWARE IN DRUG DISCOVERY AND STRONG DEMAND AMONG END USERS TO DRIVE GROWTH
                    TABLE 17 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR SOFTWARE, BY COUNTRY, 2021–2028 (USD MILLION)
 
8 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY (Page No. - 127)
    8.1 INTRODUCTION 
          TABLE 18 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
    8.2 MACHINE LEARNING 
          TABLE 19 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
          TABLE 20 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY COUNTRY, 2021–2028 (USD MILLION)
           8.2.1 DEEP LEARNING
                    8.2.1.1 Deep learning to see growing adoption in drug discovery
                                TABLE 21 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR DEEP LEARNING, BY COUNTRY, 2021–2028 (USD MILLION)
           8.2.2 SUPERVISED LEARNING
                    8.2.2.1 Applications in drug repositioning to drive market
                                TABLE 22 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR SUPERVISED LEARNING, BY COUNTRY, 2021–2028 (USD MILLION)
           8.2.3 REINFORCEMENT LEARNING
                    8.2.3.1 Potential for machines and software to automatically determine behavior to support adoption
                                TABLE 23 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR REINFORCEMENT LEARNING, BY COUNTRY, 2021–2028 (USD MILLION)
           8.2.4 UNSUPERVISED LEARNING
                    8.2.4.1 Unpredictability to affect end-user adoption
                                TABLE 24 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR UNSUPERVISED LEARNING, BY COUNTRY, 2021–2028 (USD MILLION)
           8.2.5 OTHER MACHINE LEARNING TECHNOLOGIES
                    TABLE 25 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR OTHER MACHINE LEARNING TECHNOLOGIES, BY COUNTRY, 2021–2028 (USD MILLION)
    8.3 NATURAL LANGUAGE PROCESSING 
           8.3.1 POTENTIAL APPLICATIONS IN DATA IDENTIFICATION TO SUPPORT GROWTH
                    TABLE 26 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR NATURAL LANGUAGE PROCESSING, BY COUNTRY, 2021–2028 (USD MILLION)
    8.4 CONTEXT-AWARE PROCESSING & CONTEXT-AWARE COMPUTING 
           8.4.1 RISING PROCESSING POWER, IMPROVED CONNECTIVITY TO BOOST USAGE
                    TABLE 27 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR CONTEXT-AWARE PROCESSING & CONTEXT-AWARE COMPUTING, BY COUNTRY, 2021–2028 (USD MILLION)
    8.5 OTHER TECHNOLOGIES 
          TABLE 28 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR OTHER TECHNOLOGIES, BY COUNTRY, 2021–2028 (USD MILLION)
 
9 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA (Page No. - 139)
    9.1 INTRODUCTION 
          TABLE 29 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
    9.2 ONCOLOGY 
           9.2.1 HIGH PREVALENCE OF CANCER AND SHORTAGE OF EFFECTIVE CANCER DRUGS TO DRIVE SEGMENT GROWTH
                    TABLE 30 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR ONCOLOGY, BY COUNTRY, 2021–2028 (USD MILLION)
    9.3 INFECTIOUS DISEASES 
           9.3.1 RISING EPIDEMIC OUTBREAKS TO BOOST DRUG DISCOVERY ACTIVITY
                    TABLE 31 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR INFECTIOUS DISEASES, BY COUNTRY, 2021–2028 (USD MILLION)
    9.4 NEUROLOGY 
           9.4.1 NEED TO BOOST DISCOVERY AND DEVELOPMENT TO DRIVE MARKET
                    TABLE 32 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR NEUROLOGY, BY COUNTRY, 2021–2028 (USD MILLION)
    9.5 CARDIOVASCULAR DISEASES 
           9.5.1 RISING DEMAND FOR CVD DRUGS TO DRIVE SEGMENT
                    TABLE 33 INDICATIVE LIST OF DEVELOPMENTS IN CARDIOVASCULAR DRUG DEVELOPMENT
                    TABLE 34 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR CARDIOVASCULAR DISEASES, BY COUNTRY, 2021–2028 (USD MILLION)
    9.6 IMMUNOLOGY 
           9.6.1 GROWING DRUG PIPELINE FOR IMMUNOLOGICAL DISORDERS TO FAVOR MARKET GROWTH
                    TABLE 35 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR IMMUNOLOGY, BY COUNTRY, 2021–2028 (USD MILLION)
    9.7 METABOLIC DISEASES 
           9.7.1 ROLE OF AI IN UNCOVERING SMALL-MOLECULE THERAPIES TO DRIVE ADOPTION
                    TABLE 36 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR METABOLIC DISEASES, BY COUNTRY, 2021–2028 (USD MILLION)
    9.8 OTHER THERAPEUTIC AREAS 
           TABLE 37 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR OTHER THERAPEUTIC AREAS, BY COUNTRY, 2021–2028 (USD MILLION)
 
10 AI IN DRUG DISCOVERY MARKET, BY PROCESS (Page No. - 149)
     10.1 INTRODUCTION 
             FIGURE 42 HIT-TO-LEAD IDENTIFICATION/LEAD GENERATION SEGMENT HELD LARGEST MARKET SHARE IN 2022
             TABLE 38 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
     10.2 TARGET IDENTIFICATION & SELECTION 
             10.2.1 DEVELOPMENT OF NEW TECHNOLOGIES TO SUPPORT MARKET GROWTH
                        TABLE 39 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR TARGET IDENTIFICATION & SELECTION, BY COUNTRY, 2021–2028 (USD MILLION)
     10.3 TARGET VALIDATION 
             10.3.1 RISING EMPHASIS ON TARGET VALIDATION TO AVOID LATE-STAGE FAILURE
                        TABLE 40 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR TARGET VALIDATION, BY COUNTRY, 2021–2028 (USD MILLION)
     10.4 HIT IDENTIFICATION & PRIORITIZATION 
             10.4.1 NEED FOR LARGE-SCALE DATA ANALYSIS TO DRIVE ADOPTION
                        TABLE 41 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR HIT IDENTIFICATION & PRIORITIZATION, BY COUNTRY, 2021–2028 (USD MILLION)
     10.5 HIT-TO-LEAD IDENTIFICATION/LEAD GENERATION 
             10.5.1 HIT-TO-LEAD IDENTIFICATION TO HOLD LARGEST MARKET SHARE
                        TABLE 42 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR HIT-TO-LEAD IDENTIFICATION/LEAD GENERATION, BY COUNTRY, 2021–2028 (USD MILLION)
     10.6 LEAD OPTIMIZATION 
             10.6.1 NEED FOR TRANSPARENT PRESENTATION AND ANALYSIS TO BOOST FOCUS ON LEAD OPTIMIZATION
                        TABLE 43 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR LEAD OPTIMIZATION, BY COUNTRY, 2021–2028 (USD MILLION)
     10.7 CANDIDATE SELECTION & VALIDATION 
             10.7.1 POSSIBILITY OF DRUG FAILURE DURING DEVELOPMENT TO DRIVE ADOPTION OF CANDIDATE VALIDATION SERVICES
                        TABLE 44 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR CANDIDATE SELECTION & VALIDATION, BY COUNTRY, 2021–2028 (USD MILLION)
 
11 AI IN DRUG DISCOVERY MARKET, BY USE CASE (Page No. - 160)
     11.1 INTRODUCTION 
             FIGURE 43 SMALL-MOLECULE DESIGN & OPTIMIZATION SEGMENT ACCOUNTED FOR LARGEST MARKET SHARE IN 2022
             TABLE 45 AI IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
     11.2 SMALL-MOLECULE DESIGN & OPTIMIZATION 
             11.2.1 AVAILABILITY OF WELL-VALIDATED AI TOOLS TO BOOST MARKET GROWTH
                        TABLE 46 AI IN DRUG DISCOVERY MARKET FOR SMALL-MOLECULE DESIGN & OPTIMIZATION, BY COUNTRY, 2021–2028 (USD MILLION)
     11.3 UNDERSTANDING DISEASE 
             11.3.1 RISING DATA MINING TO LINK TARGETS TO DISEASES AND DRUG REPURPOSING TO DRIVE MARKET
                        TABLE 47 AI IN DRUG DISCOVERY MARKET FOR UNDERSTANDING DISEASE, BY COUNTRY, 2021–2028 (USD MILLION)
     11.4 SAFETY & TOXICITY 
             11.4.1 TOXICOLOGY AND OFF-TARGET EFFECT PREDICTION, PK/PD SIMULATION, AND QSP MODELING TO PROPEL MARKET GROWTH
                        TABLE 48 AI IN DRUG DISCOVERY MARKET FOR SAFETY & TOXICITY, BY COUNTRY, 2021–2028 (USD MILLION)
     11.5 VACCINE DESIGN & OPTIMIZATION 
             11.5.1 GROWING ADOPTION OF AI FOR EPITOPE SELECTION, PREDICTION, AND BINDING TO AUGMENT MARKET GROWTH
                        TABLE 49 AI IN DRUG DISCOVERY MARKET FOR VACCINE DESIGN & OPTIMIZATION, BY COUNTRY, 2021–2028 (USD MILLION)
     11.6 ANTIBODY & OTHER BIOLOGIC DESIGN & OPTIMIZATION 
             11.6.1 GROWING ADOPTION OF AI FOR ANTIBODY PROPERTY PREDICTION TO DRIVE MARKET
                        TABLE 50 AI IN DRUG DISCOVERY MARKET FOR ANTIBODY & OTHER BIOLOGIC DESIGN & OPTIMIZATION, BY COUNTRY, 2021–2028 (USD MILLION)
 
12 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER (Page No. - 171)
     12.1 INTRODUCTION 
             TABLE 51 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
     12.2 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES 
             12.2.1 RISING DEMAND FOR SOLUTIONS TO CUT TIME AND COSTS OF DRUG DEVELOPMENT TO DRIVE MARKET
                        TABLE 52 INDICATIVE LIST OF DEVELOPMENTS RELATED TO AI IN PHARMACEUTICAL & BIOTECHNOLOGY INDUSTRY
                        TABLE 53 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES, BY COUNTRY, 2021–2028 (USD MILLION)
     12.3 CONTRACT RESEARCH ORGANIZATIONS 
             12.3.1 GROWING TREND OF OUTSOURCING TO PROVIDE SIGNIFICANT OPPORTUNITIES FOR CONTRACT RESEARCH ORGANIZATIONS
                        TABLE 54 INDICATIVE LIST OF COLLABORATIONS WITH CROS
                        TABLE 55 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR CONTRACT RESEARCH ORGANIZATIONS, BY COUNTRY, 2021–2028 (USD MILLION)
     12.4 RESEARCH CENTERS AND ACADEMIC & GOVERNMENT INSTITUTES 
             12.4.1 SEGMENT TO REGISTER HIGHEST CAGR OVER FORECAST PERIOD
                        TABLE 56 INDICATIVE LIST OF RESEARCH COLLABORATIONS
                        TABLE 57 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR RESEARCH CENTERS AND ACADEMIC & GOVERNMENT INSTITUTES, BY COUNTRY, 2021–2028 (USD MILLION)
 
13 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY REGION (Page No. - 179)
     13.1 INTRODUCTION 
             TABLE 58 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY REGION, 2021–2028 (USD MILLION)
     13.2 NORTH AMERICA 
             13.2.1 NORTH AMERICA: RECESSION IMPACT
                        FIGURE 44 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET SNAPSHOT
                        TABLE 59 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY COUNTRY, 2021–2028 (USD MILLION)
                        TABLE 60 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                        TABLE 61 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                        TABLE 62 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                        TABLE 63 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
                        TABLE 64 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
                        TABLE 65 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                        TABLE 66 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
             13.2.2 US
                        13.2.2.1 Strong economy and trend of early adoption of technologies to drive market
                                      FIGURE 45 DISTRIBUTION OF R&D COMPANIES, BY COUNTRY/REGION (2021 VS. 2022)
                                      TABLE 67 US: INDICATIVE LIST OF STRATEGIC DEVELOPMENTS
                                      TABLE 68 US: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                                      TABLE 69 US: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                                      TABLE 70 US: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                                      TABLE 71 US: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA 2021–2028 (USD MILLION)
                                      TABLE 72 US: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS 2021–2028 (USD MILLION)
                                      TABLE 73 US: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                                      TABLE 74 US: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
             13.2.3 CANADA
                        13.2.3.1 Growing research on AI technologies and emergence of new AI-based start-ups to support market growth
                                      TABLE 75 CANADA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                                      TABLE 76 CANADA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                                      TABLE 77 CANADA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                                      TABLE 78 CANADA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
                                      TABLE 79 CANADA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
                                      TABLE 80 CANADA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                                      TABLE 81 CANADA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
             13.2.4 MEXICO
                        13.2.4.1 Government initiatives to support market growth
                                      TABLE 82 MEXICO: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                                      TABLE 83 MEXICO: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                                      TABLE 84 MEXICO: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                                      TABLE 85 MEXICO: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
                                      TABLE 86 MEXICO: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
                                      TABLE 87 MEXICO: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                                      TABLE 88 MEXICO: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
     13.3 EUROPE 
             13.3.1 EUROPE: RECESSION IMPACT
                        TABLE 89 EUROPE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY COUNTRY, 2021–2028 (USD MILLION)
                        TABLE 90 EUROPE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                        TABLE 91 EUROPE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                        TABLE 92 EUROPE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                        TABLE 93 EUROPE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
                        TABLE 94 EUROPE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
                        TABLE 95 EUROPE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                        TABLE 96 EUROPE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
             13.3.2 UK
                        13.3.2.1 UK to hold largest share in Europe
                                      TABLE 97 UK: INDICATIVE LIST OF STRATEGIC DEVELOPMENTS
                                      TABLE 98 UK: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                                      TABLE 99 UK: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                                      TABLE 100 UK: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                                      TABLE 101 UK: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
                                      TABLE 102 UK: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
                                      TABLE 103 UK: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                                      TABLE 104 UK: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
             13.3.3 GERMANY
                        13.3.3.1 Government support and favorable training programs to propel market growth
                                      TABLE 105 GERMANY: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                                      TABLE 106 GERMANY: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                                      TABLE 107 GERMANY: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                                      TABLE 108 GERMANY: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
                                      TABLE 109 GERMANY: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
                                      TABLE 110 GERMANY: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                                      TABLE 111 GERMANY: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
             13.3.4 FRANCE
                        13.3.4.1 Strong government support and favorable strategies & initiatives to drive market
                                      TABLE 112 FRANCE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                                      TABLE 113 FRANCE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                                      TABLE 114 FRANCE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                                      TABLE 115 FRANCE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
                                      TABLE 116 FRANCE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
                                      TABLE 117 FRANCE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                                      TABLE 118 FRANCE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
             13.3.5 ITALY
                        13.3.5.1 Strong pharmaceutical industry to support market growth
                                      TABLE 119 ITALY: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                                      TABLE 120 ITALY: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                                      TABLE 121 ITALY: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                                      TABLE 122 ITALY: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
                                      TABLE 123 ITALY: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
                                      TABLE 124 ITALY: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                                      TABLE 125 ITALY: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
             13.3.6 REST OF EUROPE
                        TABLE 126 REST OF EUROPE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                        TABLE 127 REST OF EUROPE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                        TABLE 128 REST OF EUROPE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                        TABLE 129 REST OF EUROPE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
                        TABLE 130 REST OF EUROPE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
                        TABLE 131 REST OF EUROPE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                        TABLE 132 REST OF EUROPE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
     13.4 ASIA PACIFIC 
             13.4.1 ASIA PACIFIC: RECESSION IMPACT
                        TABLE 133 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY COUNTRY, 2021–2028 (USD MILLION)
                        TABLE 134 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                        TABLE 135 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                        TABLE 136 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                        TABLE 137 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
                        TABLE 138 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
                        TABLE 139 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                        TABLE 140 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
             13.4.2 JAPAN
                        13.4.2.1 Japan to dominate APAC market
                                      TABLE 141 JAPAN: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                                      TABLE 142 JAPAN: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                                      TABLE 143 JAPAN: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                                      TABLE 144 JAPAN: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
                                      TABLE 145 JAPAN: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
                                      TABLE 146 JAPAN: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                                      TABLE 147 JAPAN: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
             13.4.3 CHINA
                        13.4.3.1 Growing CMO market and cross-industry collaborations to drive market
                                      TABLE 148 CHINA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                                      TABLE 149 CHINA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                                      TABLE 150 CHINA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                                      TABLE 151 CHINA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
                                      TABLE 152 CHINA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
                                      TABLE 153 CHINA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                                      TABLE 154 CHINA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
             13.4.4 INDIA
                        13.4.4.1 Steady adoption of AI technologies to support market growth
                                      TABLE 155 INDIA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                                      TABLE 156 INDIA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                                      TABLE 157 INDIA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                                      TABLE 158 INDIA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
                                      TABLE 159 INDIA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
                                      TABLE 160 INDIA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                                      TABLE 161 INDIA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
             13.4.5 REST OF ASIA PACIFIC
                        TABLE 162 REST OF ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                        TABLE 163 REST OF ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                        TABLE 164 REST OF ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                        TABLE 165 REST OF ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
                        TABLE 166 REST OF ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
                        TABLE 167 REST OF ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                        TABLE 168 REST OF ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
     13.5 SOUTH AMERICA 
             13.5.1 SHORTAGE OF SKILLED LABOR AND GROWING REQUIREMENTS TO DRIVE AI ADOPTION
             13.5.2 SOUTH AMERICA: RECESSION IMPACT
                        TABLE 169 SOUTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                        TABLE 170 SOUTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                        TABLE 171 SOUTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                        TABLE 172 SOUTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
                        TABLE 173 SOUTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
                        TABLE 174 SOUTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                        TABLE 175 SOUTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
     13.6 MIDDLE EAST & AFRICA 
             13.6.1 LIMITED COMPANY PRESENCE AND LARGE SCOPE FOR GROWTH TO FAVOR AI MARKET
             13.6.2 MIDDLE EAST & AFRICA: RECESSION IMPACT
                        TABLE 176 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
                        TABLE 177 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
                        TABLE 178 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR MACHINE LEARNING, BY TYPE, 2021–2028 (USD MILLION)
                        TABLE 179 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
                        TABLE 180 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
                        TABLE 181 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
                        TABLE 182 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
 
14 COMPETITIVE LANDSCAPE (Page No. - 251)
     14.1 KEY PLAYER STRATEGIES/RIGHT TO WIN 
             TABLE 183 OVERVIEW OF STRATEGIES ADOPTED BY KEY AI IN DRUG DISCOVERY PLAYERS, FEBRUARY 2021– MAY 2022
     14.2 REVENUE ANALYSIS 
             FIGURE 46 REVENUE ANALYSIS OF TOP MARKET PLAYERS, 2022
     14.3 MARKET SHARE ANALYSIS 
             FIGURE 47 AI IN DRUG DISCOVERY MARKET: MARKET SHARE ANALYSIS, 2022
             TABLE 184 AI IN DRUG DISCOVERY MARKET: DEGREE OF COMPETITION
     14.4 COMPANY EVALUATION MATRIX 
             14.4.1 STARS
             14.4.2 EMERGING LEADERS
             14.4.3 PERVASIVE PLAYERS
             14.4.4 PARTICIPANTS
                        FIGURE 48 AI IN DRUG DISCOVERY MARKET: COMPANY EVALUATION MATRIX, 2022
             14.4.5 COMPANY FOOTPRINT
                        TABLE 185 USE CASE FOOTPRINT (24 COMPANIES)
                        TABLE 186 PROCESS FOOTPRINT (24 COMPANIES)
                        TABLE 187 REGION FOOTPRINT (24 COMPANIES)
                        TABLE 188 COMPANY FOOTPRINT (24 COMPANIES)
     14.5 START-UP/SME EVALUATION MATRIX 
             14.5.1 PROGRESSIVE COMPANIES
             14.5.2 RESPONSIVE COMPANIES
             14.5.3 DYNAMIC COMPANIES
             14.5.4 STARTING BLOCKS
                        FIGURE 49 AI IN DRUG DISCOVERY MARKET: START-UP/SME EVALUATION MATRIX, 2022
             14.5.5 AI IN DRUG DISCOVERY MARKET: COMPETITIVE BENCHMARKING
                        TABLE 189 AI IN DRUG DISCOVERY MARKET: DETAILED LIST OF KEY SMES/START-UPS
                        TABLE 190 USE CASE FOOTPRINT (START-UPS/SMES)
                        TABLE 191 PROCESS FOOTPRINT (START-UPS/SMES)
                        TABLE 192 REGION FOOTPRINT (START-UPS/SMES)
                        TABLE 193 COMPANY FOOTPRINT (START-UPS/SMES)
     14.6 COMPETITIVE SCENARIOS AND TRENDS 
             14.6.1 PRODUCT LAUNCHES & ENHANCEMENTS
                        TABLE 194 AI IN DRUG DISCOVERY MARKET: PRODUCT LAUNCHES & ENHANCEMENTS, 2021–2023
             14.6.2 DEALS
                        TABLE 195 AI IN DRUG DISCOVERY MARKET: DEALS, 2021–2023
             14.6.3 OTHER DEVELOPMENTS
                        TABLE 196 AI IN DRUG DISCOVERY MARKET: OTHER DEVELOPMENTS, 2021–2023
 
15 COMPANY PROFILES (Page No. - 276)
     15.1 KEY PLAYERS 
(Business Overview, Products Offered, Recent Developments, and MnM View (Key strengths/Right to Win, Strategic Choices Made, and Weaknesses and Competitive Threats))*
             15.1.1 NVIDIA CORPORATION
                        TABLE 197 NVIDIA CORPORATION: COMPANY OVERVIEW
                        FIGURE 50 NVIDIA CORPORATION: COMPANY SNAPSHOT, 2022
                        TABLE 198 NVIDIA CORPORATION: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 199 NVIDIA CORPORATION: PRODUCT/SERVICE LAUNCHES
                        TABLE 200 NVIDIA CORPORATION: DEALS
             15.1.2 EXSCIENTIA
                        TABLE 201 EXSCIENTIA: COMPANY OVERVIEW
                        FIGURE 51 EXSCIENTIA: COMPANY SNAPSHOT (2022)
                        TABLE 202 EXSCIENTIA: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 203 EXSCIENTIA: PRODUCT/SERVICE LAUNCHES
                        TABLE 204 EXSCIENTIA: DEALS
                        TABLE 205 EXSCIENTIA: OTHER DEVELOPMENTS
             15.1.3 GOOGLE
                        TABLE 206 GOOGLE: COMPANY OVERVIEW
                        FIGURE 52 GOOGLE: COMPANY SNAPSHOT (2022)
                        TABLE 207 GOOGLE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 208 GOOGLE: PRODUCT/SERVICE LAUNCHES
                        TABLE 209 GOOGLE: DEALS
                        TABLE 210 GOOGLE: OTHER DEVELOPMENTS
             15.1.4 BENEVOLENTAI
                        TABLE 211 BENEVOLENTAI: COMPANY OVERVIEW
                        FIGURE 53 BENEVOLENTAI: COMPANY SNAPSHOT (2022)
                        TABLE 212 BENEVOLENTAI: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 213 BENEVOLENTAI: DEALS
             15.1.5 RECURSION
                        TABLE 214 RECURSION: COMPANY OVERVIEW
                        FIGURE 54 RECURSION: COMPANY SNAPSHOT (2022)
                        TABLE 215 RECURSION: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 216 RECURSION: PRODUCT/SERVICE LAUNCHES
                        TABLE 217 RECURSION: DEALS
                        TABLE 218 RECURSION: OTHER DEVELOPMENTS
             15.1.6 INSILICO MEDICINE
                        TABLE 219 INSILICO MEDICINE: COMPANY OVERVIEW
                        TABLE 220 INSILICO MEDICINE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 221 INSILICO MEDICINE: PRODUCT/SERVICE LAUNCHES
                        TABLE 222 INSILICO MEDICINE: DEALS
                        TABLE 223 INSILICO MEDICINE: OTHER DEVELOPMENTS
             15.1.7 SCHRÖDINGER, INC.
                        TABLE 224 SCHRÖDINGER, INC.: COMPANY OVERVIEW
                        FIGURE 55 SCHRÖDINGER, INC.: COMPANY SNAPSHOT (2022)
                        TABLE 225 SCHRÖDINGER, INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 226 SCHRÖDINGER, INC.: DEALS
                        TABLE 227 SCHRÖDINGER, INC.: OTHER DEVELOPMENTS
             15.1.8 MICROSOFT CORPORATION
                        TABLE 228 MICROSOFT CORPORATION: COMPANY OVERVIEW
                        FIGURE 56 MICROSOFT CORPORATION: COMPANY SNAPSHOT (2023)
                        TABLE 229 MICROSOFT CORPORATION: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 230 MICROSOFT CORPORATION: SERVICE LAUNCHES
                        TABLE 231 MICROSOFT CORPORATION: DEALS
             15.1.9 ATOMWISE INC.
                        TABLE 232 ATOMWISE INC.: COMPANY OVERVIEW
                        TABLE 233 ATOMWISE INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 234 ATOMWISE INC.: DEALS
             15.1.10 ILLUMINA, INC.
                        TABLE 235 ILLUMINA, INC.: COMPANY OVERVIEW
                        FIGURE 57 ILLUMINA, INC.: COMPANY SNAPSHOT (2022)
                        TABLE 236 ILLUMINA, INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 237 ILLUMINA, INC.: PRODUCT/SERVICE LAUNCHES
                        TABLE 238 ILLUMINA, INC.: DEALS
             15.1.11 NUMEDII, INC.
                        TABLE 239 NUMEDII, INC.: COMPANY OVERVIEW
                        TABLE 240 NUMEDII, INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
             15.1.12 XTALPI INC.
                        TABLE 241 XTALPI INC.: COMPANY OVERVIEW
                        TABLE 242 XTALPI INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 243 XTALPI INC.: DEALS
             15.1.13 IKTOS
                        TABLE 244 IKTOS: COMPANY OVERVIEW
                        TABLE 245 IKTOS: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 246 IKTOS: DEALS
                        TABLE 247 IKTOS: OTHER DEVELOPMENTS
             15.1.14 TEMPUS LABS
                        TABLE 248 TEMPUS LABS: COMPANY OVERVIEW
                        TABLE 249 TEMPUS LABS: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 250 TEMPUS LABS: PRODUCT/SERVICE LAUNCHES
                        TABLE 251 TEMPUS LABS: DEALS
                        TABLE 252 TEMPUS LABS: OTHER DEVELOPMENTS
             15.1.15 DEEP GENOMICS, INC.
                        TABLE 253 DEEP GENOMICS, INC.: COMPANY OVERVIEW
                        TABLE 254 DEEP GENOMICS, INC.: PRODUCTS/SERVICES OFFERED
                        TABLE 255 DEEP GENOMICS, INC.: DEALS
                        TABLE 256 DEEP GENOMICS, INC.: OTHER DEVELOPMENTS
             15.1.16 VERGE GENOMICS
                        TABLE 257 VERGE GENOMICS: COMPANY OVERVIEW
                        TABLE 258 VERGE GENOMICS: PRODUCTS/SERVICES OFFERED
                        TABLE 259 VERGE GENOMICS: DEALS
             15.1.17 BENCHSCI
                        TABLE 260 BENCHSCI: COMPANY OVERVIEW
                        TABLE 261 BENCHSCI: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 262 BENCHSCI: PRODUCT/SERVICE LAUNCHES
                        TABLE 263 BENCHSCI: OTHER DEVELOPMENTS
             15.1.18 INSITRO
                        TABLE 264 INSITRO: COMPANY OVERVIEW
                        TABLE 265 INSITRO: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 266 INSITRO: OTHER DEVELOPMENTS
             15.1.19 VALO HEALTH
                        TABLE 267 VALO HEALTH: COMPANY OVERVIEW
                        TABLE 268 VALO HEALTH: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 269 VALO HEALTH: DEALS
                        TABLE 270 VALO HEALTH: OTHER DEVELOPMENTS
             15.1.20 BPGBIO, INC.
                        TABLE 271 BPGBIO, INC.: COMPANY OVERVIEW
                        TABLE 272 BPGBIO, INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                        TABLE 273 BPGBIO, INC.: DEALS
     15.2 OTHER EMERGING PLAYERS 
             15.2.1 PREDICTIVE ONCOLOGY, INC.
             15.2.2 LABCORP
             15.2.3 IQVIA INC.
             15.2.4 TENCENT HOLDINGS LIMITED
             15.2.5 CELSIUS THERAPEUTICS
             15.2.6 CYTOREASON
             15.2.7 OWKIN, INC.
             15.2.8 CLOUD PHARMACEUTICALS
             15.2.9 EVAXION BIOTECH
             15.2.10 STANDIGM
             15.2.11 BIOAGE LABS
             15.2.12 ENVISAGENICS
             15.2.13 ARIA PHARMACEUTICALS, INC.
 
*Details on Business Overview, Products Offered, Recent Developments, and MnM View (Key strengths/Right to Win, Strategic Choices Made, and Weaknesses and Competitive Threats) might not be captured in case of unlisted companies.
 
16 APPENDIX (Page No. - 368)
     16.1 DISCUSSION GUIDE 
     16.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 
     16.3 CUSTOMIZATION OPTIONS 
     16.4 RELATED REPORTS 
     16.5 AUTHOR DETAILS 

This market research study involved the extensive use of secondary sources, directories, and databases to identify and collect information useful for this technical, market-oriented, and financial study of the AI in drug discovery market. In-depth interviews were conducted with various primary respondents, including key industry participants, subject-matter experts (SMEs), C-level executives of key market players, and industry consultants, among other experts, to obtain and verify critical qualitative and quantitative information and to assess market prospects. The size of the market was estimated through various secondary research approaches and triangulated with inputs from primary research to arrive at the final market size.

Secondary Research

The secondary research process involved the widespread use of secondary sources, directories, databases (such as Bloomberg Businessweek, Factiva, and D&B Hoovers), white papers, annual reports, company house documents, investor presentations, and SEC filings of companies. Some non-exclusive secondary sources include the Accreditation Council for Continuing Medical Education (ACCME), Royal College of Physicians and Surgeons of Canada (RCPSC), World Health Organization (WHO), European Accreditation Council for CME (EACCME), Agency for Healthcare Research and Quality (AHRQ), European Union of Medical Specialists (UEMS), Eurostat, The American College of Cardiology (ACC), The American Registry of Radiologic Technologists (ARRT), Expert Interviews, and MarketsandMarkets Analysis.

Secondary research was used to identify and collect information useful for the extensive, technical, market-oriented, and commercial study of the clinical decision support system market. It was also used to obtain important information about the key players and market classification and segmentation according to industry trends to the bottom-most level and key developments related to market and technology perspectives. A database of the key industry leaders was also prepared using secondary research.

Primary Research

Extensive primary research was conducted after acquiring basic knowledge about the global market scenario through secondary research. Several primary interviews were conducted with market experts from both the demand side (Purchase manager, Heads of Artificial Intelligence, Machine Learning, Drug Discovery, and Computational Molecular Design, research scientist) and supply side (such as C-level and D-level executives, technology experts, product managers, marketing and sales managers, distributors, and channel partners, among others) across five major regions—North America, Europe, the Asia Pacific, Latin America, Middle East and the Africa. Approximately 70% and 30% of primary interviews were conducted with supply-side and demand-side participants, respectively. This primary data was collected through questionnaires, e-mails, online surveys, personal interviews, and telephonic interviews.

Breakdown of Primary Interviews

AI in Drug Discovery Market Size, and Share

Note 1: Tiers are defined based on the total revenues of companies. As of 2022, Tier 1 = >USD 1 billion, Tier 2 = USD 500 million to USD 1 billion, and Tier 3 = <USD 500 million.

To know about the assumptions considered for the study, download the pdf brochure

Market Size Estimation

Both top-down and bottom-up approaches were used to estimate and validate the total size of the global AI in drug discovery market. These methods were also used extensively to estimate the size of various subsegments in the market. The research methodology used to estimate the market size includes the following:

  • The key players in the industry and markets have been identified through extensive secondary research.
  • The revenue generated from the sale of AI in drug discovery products by leading players has been determined through primary and secondary research.
  • All percentage shares, splits, and breakdowns have been determined using secondary sources and verified through primary sources.

Global AI in drug discovery market: Bottom-Up Approach

AI in Drug Discovery Market Size, and Share

To know about the assumptions considered for the study, Request for Free Sample Report

Global AI in drug discovery market: Top-Down Approach

AI in Drug Discovery Market Size, and Share

Data Triangulation

After arriving at the overall market size, from the market size estimation process explained above, the AI in drug discovery market was split into segments and subsegments. To complete the overall market engineering process and to arrive at the exact statistics for all segments and subsegments, the data triangulation and market breakdown procedures were employed, wherever applicable. The data was triangulated by studying various factors and trends from both the demand and supply sides in the market.

Market Definition:

Artificial intelligence (AI) in drug discovery is the use of Al algorithms and techniques to improve the efficiency and effectiveness of the drug discovery process. Al can be used to automate tasks, analyze large datasets, and generate new insights that would be difficult or impossible to obtain using traditional methods. Al algorithms, particularly machine learning and deep learning models, are employed to analyze vast datasets related to genetics, molecular structures, and biological interactions. These Al systems can predict potential drug candidates, assess their safety profiles, and optimize the drug development process.

AI in drug discovery enables faster target identification and in-silico drug design. It identifies patterns in data, which allows the precise prediction about which compounds will turn out to be medicines. Al is still in its early stages of development in drug discovery, but it has the potential to revolutionize the process. By automating tasks, analyzing large datasets, and generating to discover new drugs more quickly and efficiently. Al has the potential to create significant value in drug discovery, primarily through three main drivers: time and cost savings, increased probability of success, and novelty of both the molecular target and optimized therapeutic agent.

Key Stakeholders:

  • Artificial intelligence (AI) in drug discovery solution providers
  • AI Platform Providers
  • Technology Providers
  • AI System Providers
  • Platform providers
  • System Integrators
  • Pharmaceutical Companies
  • Biotechnology Companies and Start-ups
  • Drug Discovery Ventures
  • Contract Development and Manufacturing Organization (CDMO)
  • Contract Research Organizations
  • Research Centers and Universities
  • Academic Institutes
  • Forums, alliances, and associations
  • Distributors
  • Venture capitalists
  • Government organizations
  • Institutional investors and investment banks
  • Investors/Shareholders
  • Consulting companies in the drug discovery sector and regulatory consultants
  • Raw material and component manufacturers
  • Hardware Manufacturers and Suppliers
  • Data Providers
  • Regulatory Agencies
  • Healthcare Providers
  • Patient Advocacy Groups
  • Ethical and Legal Experts

Report Objectives

  • To define, describe, and forecast the global AI in drug discovery market based on offering, therapeutic area, process, use cases, technology, end user, and region.
  • To provide detailed information regarding the major factors (such as drivers, restraints, opportunities, and challenges) influencing the market growth
  • To strategically analyze micromarkets with respect to individual growth trends, prospects, and contributions to the overall market
  • To analyze opportunities in the market for stakeholders and provide details of the competitive landscape for market leaders.
  • To strategically analyze the market structure and profile the key players of the market and comprehensively analyze their core competencies.
  • To forecast the size of the market segments with respect to five regions, namely, North America, Europe, Asia Pacific, South America, and the Middle East & Africa.
  • To track and analyze competitive developments such as product launches and enhancements, and investments, partnerships, collaborations, joint ventures, funding, acquisition, expansions, agreements, sales contracts, and alliances in the market during the forecast period.

Available Customizations:

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Geographic Analysis

  • Further breakdown of the Rest of the Asia Pacific market into Singapore, Malaysia, Thailand, and Australia, and others
  • Further breakdown of the Rest of Europe market into Russia, Denmark, Sweden, Finland, and other European countries
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Report Code
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Published ON
Nov, 2023
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