Artificial Intelligence 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
Updated on : September 24, 2024
Overview of the AI in drug discovery Market
Key entities in the global artificial intelligence (AI) in drug discovery market include major players such as NVIDIA Corporation, Exscientia, and Google. AI in drug discovery market forecasted to transform from $0.9 billion in 2023 to $4.9 billion by 2028, driven by a CAGR of 40.2%. Key drivers include the need to reduce drug development costs and time, as AI enhances drug discovery through faster and more efficient research. However, challenges such as a shortage of AI expertise, regulatory uncertainties, and limited data availability may restrain growth. Emerging markets in India, China, and the Middle East offer significant growth opportunities.
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.
AI in Drug Discovery Market Trends
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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.
Source: Secondary Literature, Interviews with Experts, and MarketsandMarkets Analysis
The global AI in drug discovery market is segmented by offering, technology, therapeutic area, 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.
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Some of the prominent players are Exscientia (UK), BenevolentAI (UK), Recursion (US), Schrödinger, Inc. (US), Microsoft Corporation (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), 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 Size in 2023 |
$0.9 billion |
Projected Revenue Size by 2028 |
$4.9 billion |
Industry Growth 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
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North America
- US
- Canada
- Mexico
-
Europe
- Germany
- UK
- France
- Italy
- Rest of Europe
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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.
Frequently Asked Questions (FAQ):
What is the projected market revenue value of the global AI in drug discovery market?
The global AI in drug discovery market boasts a total revenue value of $4.9 billion by 2028.
What is the estimated growth rate (CAGR) of the global AI in drug discovery market?
The global AI in drug discovery market has an estimated compound annual growth rate (CAGR) of 40.2% and a revenue size in the region of $0.9 billion in 2023.
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- 5.1 INTRODUCTION
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5.2 MARKET DYNAMICSDRIVERS- Growing cross-industry collaborations and partnerships- Growing need to reduce time and cost of drug discovery and development- Patent expiry of several drugsRESTRAINTS- Shortage of AI workforce and ambiguous regulatory guidelines for medical softwareOPPORTUNITIES- Growing biotechnology industry- Emerging markets- Focus on developing human-aware AI systemsCHALLENGES- Limited availability of data sets- Lack of required tools and usability
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6.1 OVERVIEW OF KEY INDUSTRY TRENDSEVOLUTION OF AI IN DRUG DISCOVERYCOMPUTER-AIDED DRUG DESIGN AND AI
- 6.2 SUPPLY CHAIN ANALYSIS
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6.3 PORTER’S FIVE FORCES ANALYSISINTENSITY OF COMPETITIVE RIVALRYBARGAINING POWER OF BUYERSBARGAINING POWER OF SUPPLIERSTHREAT OF SUBSTITUTESTHREAT OF NEW ENTRANTS
- 6.4 ECOSYSTEM/MARKET MAP
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6.5 TECHNOLOGY ANALYSISDRY LAB SERVICESWET LAB SERVICES- Chemistry services- BIOLOGICAL SERVICES
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6.6 PRICING ANALYSISAVERAGE SELLING PRICE TRENDS, BY REGIONINDICATIVE PRICING ANALYSIS, BY PROCESS
- 6.7 BUSINESS MODELS
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6.8 CASE STUDY ANALYSISCASE STUDY 1: BRISTOL MYERS SQUIBB AND EXSCIENTIACASE STUDY 2: APEIRON LLC AND EXSCIENTIA
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6.9 REGULATORY ANALYSISAI IN DRUG DISCOVERY MARKET: REGULATORY LANDSCAPE, BY REGIONREGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
- 6.10 PATENT ANALYSIS
- 6.11 KEY CONFERENCES & EVENTS (Q1 2023–Q2 2024)
- 6.12 TRENDS/DISRUPTIONS IMPACTING CUSTOMERS’ BUSINESSES
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6.13 KEY STAKEHOLDERS & BUYING CRITERIAKEY STAKEHOLDERS IN BUYING PROCESSBUYING CRITERIA FOR AI IN DRUG DISCOVERY MARKET
- 6.14 AI-DERIVED CLINICAL ASSETS
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6.15 UNMET NEEDSUNMET NEEDS IN AI IN DRUG DISCOVERYSINGLE-CELL ANALYSIS LANDSCAPE: KEY CHALLENGES AND PAIN POINTS IN DRUG DISCOVERYKEY UNMET NEEDS AND PAIN POINTS FOR AI APPLICATIONS IN SINGLE-CELL ANALYSIS FOR DRUG DISCOVERY
- 7.1 INTRODUCTION
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7.2 SERVICESSERVICES SEGMENT TO WITNESS HIGHEST GROWTH
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7.3 SOFTWAREBENEFITS OF SOFTWARE IN DRUG DISCOVERY AND STRONG DEMAND AMONG END USERS TO DRIVE GROWTH
- 8.1 INTRODUCTION
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8.2 MACHINE LEARNINGDEEP LEARNING- Deep learning to see growing adoption in drug discoverySUPERVISED LEARNING- Applications in drug repositioning to drive marketREINFORCEMENT LEARNING- Potential for machines and software to automatically determine behavior to support adoptionUNSUPERVISED LEARNING- Unpredictability to affect end-user adoptionOTHER MACHINE LEARNING TECHNOLOGIES
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8.3 NATURAL LANGUAGE PROCESSINGPOTENTIAL APPLICATIONS IN DATA IDENTIFICATION TO SUPPORT GROWTH
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8.4 CONTEXT-AWARE PROCESSING & CONTEXT-AWARE COMPUTINGRISING PROCESSING POWER, IMPROVED CONNECTIVITY TO BOOST USAGE
- 8.5 OTHER TECHNOLOGIES
- 9.1 INTRODUCTION
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9.2 ONCOLOGYHIGH PREVALENCE OF CANCER AND SHORTAGE OF EFFECTIVE CANCER DRUGS TO DRIVE SEGMENT GROWTH
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9.3 INFECTIOUS DISEASESRISING EPIDEMIC OUTBREAKS TO BOOST DRUG DISCOVERY ACTIVITY
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9.4 NEUROLOGYNEED TO BOOST DISCOVERY AND DEVELOPMENT TO DRIVE MARKET
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9.5 CARDIOVASCULAR DISEASESRISING DEMAND FOR CVD DRUGS TO DRIVE SEGMENT
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9.6 IMMUNOLOGYGROWING DRUG PIPELINE FOR IMMUNOLOGICAL DISORDERS TO FAVOR MARKET GROWTH
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9.7 METABOLIC DISEASESROLE OF AI IN UNCOVERING SMALL-MOLECULE THERAPIES TO DRIVE ADOPTION
- 9.8 OTHER THERAPEUTIC AREAS
- 10.1 INTRODUCTION
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10.2 TARGET IDENTIFICATION & SELECTIONDEVELOPMENT OF NEW TECHNOLOGIES TO SUPPORT MARKET GROWTH
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10.3 TARGET VALIDATIONRISING EMPHASIS ON TARGET VALIDATION TO AVOID LATE-STAGE FAILURE
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10.4 HIT IDENTIFICATION & PRIORITIZATIONNEED FOR LARGE-SCALE DATA ANALYSIS TO DRIVE ADOPTION
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10.5 HIT-TO-LEAD IDENTIFICATION/LEAD GENERATIONHIT-TO-LEAD IDENTIFICATION TO HOLD LARGEST MARKET SHARE
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10.6 LEAD OPTIMIZATIONNEED FOR TRANSPARENT PRESENTATION AND ANALYSIS TO BOOST FOCUS ON LEAD OPTIMIZATION
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10.7 CANDIDATE SELECTION & VALIDATIONPOSSIBILITY OF DRUG FAILURE DURING DEVELOPMENT TO DRIVE ADOPTION OF CANDIDATE VALIDATION SERVICES
- 11.1 INTRODUCTION
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11.2 SMALL-MOLECULE DESIGN & OPTIMIZATIONAVAILABILITY OF WELL-VALIDATED AI TOOLS TO BOOST MARKET GROWTH
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11.3 UNDERSTANDING DISEASERISING DATA MINING TO LINK TARGETS TO DISEASES AND DRUG REPURPOSING TO DRIVE MARKET
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11.4 SAFETY & TOXICITYTOXICOLOGY AND OFF-TARGET EFFECT PREDICTION, PK/PD SIMULATION, AND QSP MODELING TO PROPEL MARKET GROWTH
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11.5 VACCINE DESIGN & OPTIMIZATIONGROWING ADOPTION OF AI FOR EPITOPE SELECTION, PREDICTION, AND BINDING TO AUGMENT MARKET GROWTH
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11.6 ANTIBODY & OTHER BIOLOGIC DESIGN & OPTIMIZATIONGROWING ADOPTION OF AI FOR ANTIBODY PROPERTY PREDICTION TO DRIVE MARKET
- 12.1 INTRODUCTION
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12.2 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIESRISING DEMAND FOR SOLUTIONS TO CUT TIME AND COSTS OF DRUG DEVELOPMENT TO DRIVE MARKET
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12.3 CONTRACT RESEARCH ORGANIZATIONSGROWING TREND OF OUTSOURCING TO PROVIDE SIGNIFICANT OPPORTUNITIES FOR CONTRACT RESEARCH ORGANIZATIONS
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12.4 RESEARCH CENTERS AND ACADEMIC & GOVERNMENT INSTITUTESSEGMENT TO REGISTER HIGHEST CAGR OVER FORECAST PERIOD
- 13.1 INTRODUCTION
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13.2 NORTH AMERICANORTH AMERICA: RECESSION IMPACTUS- Strong economy and trend of early adoption of technologies to drive marketCANADA- Growing research on AI technologies and emergence of new AI-based start-ups to support market growthMEXICO- Government initiatives to support market growth
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13.3 EUROPEEUROPE: RECESSION IMPACTUK- UK to hold largest share in EuropeGERMANY- Government support and favorable training programs to propel market growthFRANCE- Strong government support and favorable strategies & initiatives to drive marketITALY- Strong pharmaceutical industry to support market growthREST OF EUROPE
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13.4 ASIA PACIFICASIA PACIFIC: RECESSION IMPACTJAPAN- Japan to dominate APAC marketCHINA- Growing CMO market and cross-industry collaborations to drive marketINDIA- Steady adoption of AI technologies to support market growthREST OF ASIA PACIFIC
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13.5 SOUTH AMERICASHORTAGE OF SKILLED LABOR AND GROWING REQUIREMENTS TO DRIVE AI ADOPTIONSOUTH AMERICA: RECESSION IMPACT
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13.6 MIDDLE EAST & AFRICALIMITED COMPANY PRESENCE AND LARGE SCOPE FOR GROWTH TO FAVOR AI MARKETMIDDLE EAST & AFRICA: RECESSION IMPACT
- 14.1 KEY PLAYER STRATEGIES/RIGHT TO WIN
- 14.2 REVENUE ANALYSIS
- 14.3 MARKET SHARE ANALYSIS
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14.4 COMPANY EVALUATION MATRIXSTARSEMERGING LEADERSPERVASIVE PLAYERSPARTICIPANTSCOMPANY FOOTPRINT
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14.5 START-UP/SME EVALUATION MATRIXPROGRESSIVE COMPANIESRESPONSIVE COMPANIESDYNAMIC COMPANIESSTARTING BLOCKSAI IN DRUG DISCOVERY MARKET: COMPETITIVE BENCHMARKING
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14.6 COMPETITIVE SCENARIOS AND TRENDSPRODUCT LAUNCHES & ENHANCEMENTSDEALSOTHER DEVELOPMENTS
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15.1 KEY PLAYERSNVIDIA CORPORATION- Business overview- Products/Solutions/Services offered- Recent developments- MnM viewEXSCIENTIA- Business overview- Products/Solutions/Services offered- Recent developments- MnM viewGOOGLE- Business overview- Products/Solutions/Services offered- Recent developments- MnM viewBENEVOLENTAI- Business overview- Products/Solutions/Services offered- Recent developments- MnM viewRECURSION- Business overview- Products/Solutions/Services offered- Recent developments- MnM viewINSILICO MEDICINE- Business overview- Products/Solutions/Services offered- Recent developmentsSCHRÖDINGER, INC.- Business overview- Products/Solutions/Services offered- Recent developmentsMICROSOFT CORPORATION- Business overview- Products/Solutions/Services offered- Recent developmentsATOMWISE INC.- Business overview- Products/Solutions/Services offered- Recent developmentsILLUMINA, INC.- Business overview- Products/Solutions/Services offered- Recent developmentsNUMEDII, INC.- Business overview- Products/Solutions/Services offeredXTALPI INC.- Business overview- Products/Solutions/Services offered- Recent developmentsIKTOS- Business overview- Products/Solutions/Services offered- Recent developmentsTEMPUS LABS- Business overview- Products/Solutions/Services offered- Recent developmentsDEEP GENOMICS, INC.- Business overview- Products/Solutions/Services offered- Recent developmentsVERGE GENOMICS- Business overview- Products/Solutions/Services offered- Recent developmentsBENCHSCI- Business overview- Products/Solutions/Services offered- Recent developmentsINSITRO- Business overview- Products/Solutions/Services offered- Recent developmentsVALO HEALTH- Business overview- Products/Solutions/Services offered- Recent developmentsBPGBIO, INC.- Business overview- Products/Solutions/Services offered- Recent developments
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15.2 OTHER EMERGING PLAYERSPREDICTIVE ONCOLOGY, INC.LABCORPIQVIA INC.TENCENT HOLDINGS LIMITEDCELSIUS THERAPEUTICSCYTOREASONOWKIN, INC.CLOUD PHARMACEUTICALSEVAXION BIOTECHSTANDIGMBIOAGE LABSENVISAGENICSARIA PHARMACEUTICALS, INC.
- 16.1 DISCUSSION GUIDE
- 16.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
- 16.3 CUSTOMIZATION OPTIONS
- 16.4 RELATED REPORTS
- 16.5 AUTHOR DETAILS
- TABLE 1 EXCHANGE RATES UTILIZED FOR CONVERSION TO USD
- TABLE 2 FACTOR ANALYSIS
- TABLE 3 RISK ASSESSMENT: AI IN DRUG DISCOVERY MARKET
- 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)
- TABLE 7 AI IN DRUG DISCOVERY MARKET: IMPACT ANALYSIS
- TABLE 8 INDICATIVE LIST OF COLLABORATIONS AND PARTNERSHIPS (2021−2023)
- TABLE 9 INDICATIVE LIST OF DRUGS LOSING PATENTS IN 2023
- TABLE 10 AI IN DRUG DISCOVERY MARKET: PORTER’S FIVE FORCES ANALYSIS
- TABLE 11 AI IN DRUG DISCOVERY MARKET: INDICATIVE PRICING, BY PROCESS
- TABLE 12 LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
- TABLE 13 LIST OF PATENTS/PATENT APPLICATIONS IN AI IN DRUG DISCOVERY MARKET, 2021–2023
- TABLE 14 KEY AI-DERIVED CLINICAL ASSETS, BY COMPANY
- TABLE 15 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY OFFERING, 2021–2028 (USD MILLION)
- TABLE 16 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR SERVICES, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 17 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR SOFTWARE, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 18 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2021–2028 (USD MILLION)
- 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)
- TABLE 21 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR DEEP LEARNING, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 22 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR SUPERVISED LEARNING, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 23 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR REINFORCEMENT LEARNING, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 24 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR UNSUPERVISED LEARNING, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 25 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR OTHER MACHINE LEARNING TECHNOLOGIES, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 26 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR NATURAL LANGUAGE PROCESSING, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 27 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR CONTEXT-AWARE PROCESSING & CONTEXT-AWARE COMPUTING, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 28 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR OTHER TECHNOLOGIES, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 29 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY THERAPEUTIC AREA, 2021–2028 (USD MILLION)
- TABLE 30 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR ONCOLOGY, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 31 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR INFECTIOUS DISEASES, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 32 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR NEUROLOGY, BY COUNTRY, 2021–2028 (USD MILLION)
- 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)
- TABLE 35 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR IMMUNOLOGY, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 36 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR METABOLIC DISEASES, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 37 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR OTHER THERAPEUTIC AREAS, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 38 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY PROCESS, 2021–2028 (USD MILLION)
- TABLE 39 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR TARGET IDENTIFICATION & SELECTION, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 40 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR TARGET VALIDATION, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 41 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR HIT IDENTIFICATION & PRIORITIZATION, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 42 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR HIT-TO-LEAD IDENTIFICATION/LEAD GENERATION, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 43 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR LEAD OPTIMIZATION, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 44 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET FOR CANDIDATE SELECTION & VALIDATION, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 45 AI IN DRUG DISCOVERY MARKET, BY USE CASE, 2021–2028 (USD MILLION)
- TABLE 46 AI IN DRUG DISCOVERY MARKET FOR SMALL-MOLECULE DESIGN & OPTIMIZATION, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 47 AI IN DRUG DISCOVERY MARKET FOR UNDERSTANDING DISEASE, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 48 AI IN DRUG DISCOVERY MARKET FOR SAFETY & TOXICITY, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 49 AI IN DRUG DISCOVERY MARKET FOR VACCINE DESIGN & OPTIMIZATION, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 50 AI IN DRUG DISCOVERY MARKET FOR ANTIBODY & OTHER BIOLOGIC DESIGN & OPTIMIZATION, BY COUNTRY, 2021–2028 (USD MILLION)
- TABLE 51 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY END USER, 2021–2028 (USD MILLION)
- 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)
- 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)
- 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)
- TABLE 58 ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET, BY REGION, 2021–2028 (USD MILLION)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- TABLE 183 OVERVIEW OF STRATEGIES ADOPTED BY KEY AI IN DRUG DISCOVERY PLAYERS, FEBRUARY 2021– MAY 2022
- TABLE 184 AI IN DRUG DISCOVERY MARKET: DEGREE OF COMPETITION
- 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)
- 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)
- TABLE 194 AI IN DRUG DISCOVERY MARKET: PRODUCT LAUNCHES & ENHANCEMENTS, 2021–2023
- TABLE 195 AI IN DRUG DISCOVERY MARKET: DEALS, 2021–2023
- TABLE 196 AI IN DRUG DISCOVERY MARKET: OTHER DEVELOPMENTS, 2021–2023
- TABLE 197 NVIDIA CORPORATION: COMPANY OVERVIEW
- TABLE 198 NVIDIA CORPORATION: PRODUCTS/SOLUTIONS/SERVICES OFFERED
- TABLE 199 NVIDIA CORPORATION: PRODUCT/SERVICE LAUNCHES
- TABLE 200 NVIDIA CORPORATION: DEALS
- TABLE 201 EXSCIENTIA: COMPANY OVERVIEW
- TABLE 202 EXSCIENTIA: PRODUCTS/SOLUTIONS/SERVICES OFFERED
- TABLE 203 EXSCIENTIA: PRODUCT/SERVICE LAUNCHES
- TABLE 204 EXSCIENTIA: DEALS
- TABLE 205 EXSCIENTIA: OTHER DEVELOPMENTS
- TABLE 206 GOOGLE: COMPANY OVERVIEW
- TABLE 207 GOOGLE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
- TABLE 208 GOOGLE: PRODUCT/SERVICE LAUNCHES
- TABLE 209 GOOGLE: DEALS
- TABLE 210 GOOGLE: OTHER DEVELOPMENTS
- TABLE 211 BENEVOLENTAI: COMPANY OVERVIEW
- TABLE 212 BENEVOLENTAI: PRODUCTS/SOLUTIONS/SERVICES OFFERED
- TABLE 213 BENEVOLENTAI: DEALS
- TABLE 214 RECURSION: COMPANY OVERVIEW
- TABLE 215 RECURSION: PRODUCTS/SOLUTIONS/SERVICES OFFERED
- TABLE 216 RECURSION: PRODUCT/SERVICE LAUNCHES
- TABLE 217 RECURSION: DEALS
- TABLE 218 RECURSION: OTHER DEVELOPMENTS
- 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
- TABLE 224 SCHRÖDINGER, INC.: COMPANY OVERVIEW
- TABLE 225 SCHRÖDINGER, INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
- TABLE 226 SCHRÖDINGER, INC.: DEALS
- TABLE 227 SCHRÖDINGER, INC.: OTHER DEVELOPMENTS
- TABLE 228 MICROSOFT CORPORATION: COMPANY OVERVIEW
- TABLE 229 MICROSOFT CORPORATION: PRODUCTS/SOLUTIONS/SERVICES OFFERED
- TABLE 230 MICROSOFT CORPORATION: SERVICE LAUNCHES
- TABLE 231 MICROSOFT CORPORATION: DEALS
- TABLE 232 ATOMWISE INC.: COMPANY OVERVIEW
- TABLE 233 ATOMWISE INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
- TABLE 234 ATOMWISE INC.: DEALS
- TABLE 235 ILLUMINA, INC.: COMPANY OVERVIEW
- TABLE 236 ILLUMINA, INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
- TABLE 237 ILLUMINA, INC.: PRODUCT/SERVICE LAUNCHES
- TABLE 238 ILLUMINA, INC.: DEALS
- TABLE 239 NUMEDII, INC.: COMPANY OVERVIEW
- TABLE 240 NUMEDII, INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
- TABLE 241 XTALPI INC.: COMPANY OVERVIEW
- TABLE 242 XTALPI INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
- TABLE 243 XTALPI INC.: DEALS
- TABLE 244 IKTOS: COMPANY OVERVIEW
- TABLE 245 IKTOS: PRODUCTS/SOLUTIONS/SERVICES OFFERED
- TABLE 246 IKTOS: DEALS
- TABLE 247 IKTOS: OTHER DEVELOPMENTS
- 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
- 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
- TABLE 257 VERGE GENOMICS: COMPANY OVERVIEW
- TABLE 258 VERGE GENOMICS: PRODUCTS/SERVICES OFFERED
- TABLE 259 VERGE GENOMICS: DEALS
- TABLE 260 BENCHSCI: COMPANY OVERVIEW
- TABLE 261 BENCHSCI: PRODUCTS/SOLUTIONS/SERVICES OFFERED
- TABLE 262 BENCHSCI: PRODUCT/SERVICE LAUNCHES
- TABLE 263 BENCHSCI: OTHER DEVELOPMENTS
- TABLE 264 INSITRO: COMPANY OVERVIEW
- TABLE 265 INSITRO: PRODUCTS/SOLUTIONS/SERVICES OFFERED
- TABLE 266 INSITRO: OTHER DEVELOPMENTS
- 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
- TABLE 271 BPGBIO, INC.: COMPANY OVERVIEW
- TABLE 272 BPGBIO, INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
- TABLE 273 BPGBIO, INC.: DEALS
- FIGURE 1 AI IN DRUG DISCOVERY MARKET: MARKET SEGMENTATION
- FIGURE 2 RESEARCH DESIGN
- FIGURE 3 BREAKDOWN OF PRIMARY INTERVIEWS: BY DEMAND SIDE, SUPPLY SIDE, DESIGNATION, AND REGION
- FIGURE 4 SUPPLY-SIDE MARKET ESTIMATION: REVENUE SHARE ANALYSIS
- FIGURE 5 BOTTOM-UP APPROACH: END-USER SPENDING ON AI IN DRUG DISCOVERY
- 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
- FIGURE 9 DATA TRIANGULATION METHODOLOGY
- 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
- FIGURE 17 GROWING NUMBER OF CROSS-INDUSTRY COLLABORATIONS & PARTNERSHIPS TO DRIVE MARKET
- FIGURE 18 NORTH AMERICA TO DOMINATE AI IN DRUG DISCOVERY MARKET DURING FORECAST PERIOD
- FIGURE 19 US TO REGISTER HIGHEST REVENUE GROWTH FROM 2023 TO 2028
- FIGURE 20 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES AND US HELD LARGEST SHARE IN NORTH AMERICA, 2022
- FIGURE 21 SERVICES TO HOLD MAJORITY MARKET SHARE IN 2028
- FIGURE 22 MACHINE LEARNING TO RETAIN MARKET LEADERSHIP TILL 2028
- FIGURE 23 ONCOLOGY TO DOMINATE MARKET IN 2028
- FIGURE 24 HIT-TO LEAD IDENTIFICATION/LEAD GENERATION TO DOMINATE MARKET IN 2028
- FIGURE 25 SMALL MOLECULE DESIGN & OPTIMIZATION TO REGISTER HIGHEST GROWTH OVER FORECAST PERIOD
- FIGURE 26 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES TO ACCOUNT FOR LARGEST MARKET SHARE IN 2028
- FIGURE 27 AI IN DRUG DISCOVERY: MARKET DYNAMICS
- FIGURE 28 EVOLUTION OF AI IN DRUG DISCOVERY MARKET
- FIGURE 29 STRUCTURE-BASED DRUG DESIGNING: AI IN DRUG DISCOVERY MARKET
- FIGURE 30 AI IN DRUG DISCOVERY MARKET: SUPPLY CHAIN ANALYSIS (2022)
- FIGURE 31 AI IN DRUG DISCOVERY MARKET ECOSYSTEM
- FIGURE 32 AI IN DRUG DISCOVERY MARKET: CLASSIFICATION
- FIGURE 33 AI IN LIFE SCIENCES: BUSINESS MODELS
- FIGURE 34 BENEFITS OF HYBRID BUSINESS MODELS
- FIGURE 35 SPECIALIZATION OF AI COMPANIES OVER TIME
- 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)
- FIGURE 39 REVENUE SHIFT IN AI IN DRUG DISCOVERY MARKET
- FIGURE 40 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS OF AI IN DRUG DISCOVERY MARKET
- FIGURE 41 KEY BUYING CRITERIA FOR END USERS
- FIGURE 42 HIT-TO-LEAD IDENTIFICATION/LEAD GENERATION SEGMENT HELD LARGEST MARKET SHARE IN 2022
- FIGURE 43 SMALL-MOLECULE DESIGN & OPTIMIZATION SEGMENT ACCOUNTED FOR LARGEST MARKET SHARE IN 2022
- FIGURE 44 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY MARKET SNAPSHOT
- FIGURE 45 DISTRIBUTION OF R&D COMPANIES, BY COUNTRY/REGION (2021 VS. 2022)
- FIGURE 46 REVENUE ANALYSIS OF TOP MARKET PLAYERS, 2022
- FIGURE 47 AI IN DRUG DISCOVERY MARKET: MARKET SHARE ANALYSIS, 2022
- FIGURE 48 AI IN DRUG DISCOVERY MARKET: COMPANY EVALUATION MATRIX, 2022
- FIGURE 49 AI IN DRUG DISCOVERY MARKET: START-UP/SME EVALUATION MATRIX, 2022
- FIGURE 50 NVIDIA CORPORATION: COMPANY SNAPSHOT, 2022
- FIGURE 51 EXSCIENTIA: COMPANY SNAPSHOT (2022)
- FIGURE 52 GOOGLE: COMPANY SNAPSHOT (2022)
- FIGURE 53 BENEVOLENTAI: COMPANY SNAPSHOT (2022)
- FIGURE 54 RECURSION: COMPANY SNAPSHOT (2022)
- FIGURE 55 SCHRÖDINGER, INC.: COMPANY SNAPSHOT (2022)
- FIGURE 56 MICROSOFT CORPORATION: COMPANY SNAPSHOT (2023)
- FIGURE 57 ILLUMINA, INC.: COMPANY SNAPSHOT (2022)
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
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.
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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
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Global AI in drug discovery market: Top-Down Approach
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:
With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:
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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