>Intelligence artificielle (IA) sur le marché de la découverte de médicaments en Asie-Pacifique, par application (nouveaux candidats médicaments, optimisation et réorientation des médicaments, tests et approbations précliniques, surveillance des médicaments, recherche de nouvelles cibles et voies associées aux maladies, compréhension des mécanismes des maladies, agrégation et synthèse d'informations, formation et qualification d'hypothèses, conception de nouveaux médicaments, recherche de cibles médicamenteuses d'un ancien médicament et autres), technologie (apprentissage automatique, apprentissage profond, traitement du langage naturel et autres), type de médicament (petite et grande molécule), offre (logiciels et services), indication (immuno-oncologie, maladies neurodégénératives, maladies cardiovasculaires, maladies métaboliques et autres), utilisation finale (organismes de recherche sous contrat (CRO), sociétés pharmaceutiques et biotechnologiques, centres de recherche et instituts universitaires et autres) Tendances et prévisions de l'industrie jusqu'en 2029.
Analyse et perspectives du marché de l'intelligence artificielle (IA) dans la découverte de médicaments en Asie-Pacifique
L’intelligence artificielle (IA) devrait devenir une technologie lucrative dans le secteur de la santé. La mise en œuvre de l’IA réduit le déficit de R&D dans le processus de fabrication des médicaments et contribue à la fabrication ciblée de médicaments. Par conséquent, les sociétés biopharmaceutiques se tournent vers l’IA pour accroître leur part de marché. L’IA pour la découverte de médicaments est une technologie qui utilise des machines pour simuler l’intelligence humaine afin de résoudre des problèmes complexes dans la procédure de développement de médicaments.
L'adoption de solutions d'IA dans le processus d'essais cliniques élimine les obstacles possibles, réduit la durée du cycle des essais cliniques et augmente la productivité et la précision du processus d'essais cliniques. Les avancées technologiques de l'IA pour la découverte de médicaments et la réduction du temps total nécessaire au processus de découverte de médicaments sont d'autres facteurs qui stimulent la croissance du marché au cours de la période de prévision. Cependant, la faible qualité et l'incohérence des données disponibles entraveront la croissance du marché. De plus, les coûts élevés associés à la technologie et les limitations techniques freineront la croissance du marché.
Data Bridge Market Research analyse que le marché de l'intelligence artificielle (IA) dans la découverte de médicaments en Asie-Pacifique devrait atteindre la valeur de 3 424,04 millions USD d'ici 2029, à un TCAC de 50,9 % au cours de la période de prévision. Les logiciels représentent le segment technologique le plus important du marché en raison de l'évolution rapide des avancées technologiques pour commercialiser l'utilisation de l'IA dans le marché de la découverte de médicaments. Ce rapport de marché couvre également en profondeur l'analyse des prix, l'analyse des brevets et les avancées technologiques.
|
Rapport métrique |
Détails |
|
Période de prévision |
2022 à 2029 |
|
Année de base |
2021 |
|
Années historiques |
2020 (personnalisable pour 2019-2014) |
|
Unités quantitatives |
Chiffre d'affaires en millions USD, prix en USD |
|
Segments couverts |
By Application (Novel Drug Candidates, Drug Optimization and Repurposing Preclinical Testing and Approval, Drug Monitoring, Finding New Diseases Associated Targets and Pathways, Understanding Disease Mechanisms, Aggregating and Synthesizing Information, Formation & Qualification of Hypotheses, De Novo Drug Design, Finding Drug Targets of an Old Drug and Others), Technology (Machine Learning, Deep Learning, Natural Language Processing and Others), Drug Type (Small Molecule and Large Molecule), Offering (Software and Services), Indication (Immuno-Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases and Others), End Use (Contract Research Organizations (CROs), Pharmaceutical & Biotechnology Companies, Research Centers and Academic Institutes and Others) |
|
Countries Covered |
China, Japan, India, South Korea, Singapore, Thailand, Malaysia, Australia & New Zealand, Philippines, Indonesia, rest of Asia-Pacific |
|
Market Players Covered |
Some of the key players operating in the market are NVIDIA Corporation, IBM Corp., Atomwise Inc., Microsoft, Benevolent AI, Aria Pharmaceuticals, Inc., DEEP GENOMICS, Exscientia, Cloud, Insilico Medicine, Cyclica, NuMedii, Inc., Envisagenics, Owkin Inc., BERG LLC, Schrödinger, Inc., XtalPi Inc., and BIOAGE Inc. among others |
Asia-Pacific Artificial Intelligence (AI) in Drug Discovery Market Definition
AI has caught the attention and minds of medical technology practitioners in the past few years, as several companies and major research laboratories have worked to perfect these technologies for clinical use. The first commercialized demonstrations of how AI (also known as Deep Learning (DL), Machine Learning (ML), or Artificial Neural Networks (ANNs)) could assist clinicians are now available. These systems could lead to a paradigm shift in clinician workflow, and increase productivity while simultaneously enhancing treatment and patient throughput. AI for drug discovery is a technology that uses machines to simulate human intelligence to solve complicated challenges in the drug development procedure. The adoption of AI solutions in the clinical trial process eliminates possible obstacles, reduces clinical trial cycle time, and increases the productivity and accuracy of the clinical trial process. Therefore, the adoption of these advanced AI solutions in drug discovery processes is gaining popularity amongst life science industry stakeholders. In the pharmaceutical sector, it aids in the discovery of novel compounds, therapeutic target identification, and the development of customized medications. AI platforms used for drug discovery can prove to be a feasible option for deriving insights into the discovery of drugs to treat and minimize the severity of various chronic diseases.
Asia-Pacific Artificial Intelligence (AI) in Drug Discovery Market Dynamics
This section deals with understanding the market drivers, advantages, opportunities, restraints, and challenges. All of this is discussed in detail below:
Drivers
- Rise in incidence of chronic diseases propels need for AI in drug discovery
The incidence of chronic diseases is increasing at a rapid pace across the globe. According to the Centers for Disease Control and Prevention (CDC), six in 10 adults in the U.S. have a chronic disease. Furthermore, the CDC also highlights that chronic diseases such as heart disease and diabetes are the leading causes of death in the U.S. Such statistics shed light on the growing prevalence of chronic diseases and the need to bring down the fatality rate caused due to these diseases.
AI platforms used for drug discovery can prove to be a feasible option for deriving insights into the discovery of drugs to treat and minimize the severity of various chronic diseases. Thus, these factors are expected to act as a driver for the market growth during the forecast period.
- Strategic collaborations, partnerships, and products launch
AI has the potential to transform drug discovery by rapidly accelerating the R&D timeline, making drug development cheaper and faster, and improving the probability of approval. AI can also increase the effectiveness of drug repurposing research.
An increase in cross-industry alliances and collaborations drives the market. Rise in relevance of AI in drug discovery & development, and a surge in funding for R&D activities, including AI technology in the field of drug research, are projected to propel the global market growth. Hence, increase in cross-industry collaborations and partnerships is driving the market.
Restraint
- High cost associated with technology and technical limitations
The current healthcare sector is facing several complex challenges, such as the increased cost of drugs and therapies, and society needs specific significant changes in this area. The entire success of AI depends on the availability of a substantial amount of data because these data are used for the subsequent training provided to the system. Access to data from various database providers can incur extra costs for a company. Clinical trials are directed towards establishing the safety and efficacy of a drug product in humans for a particular disease condition and require six to seven years along with a substantial financial investment. However, only one out of ten molecules entering these trials gain successful clearance, which is a massive loss for the industry. These failures can result from inappropriate patient selection, shortage of technical requirements, and poor infrastructure. Thus, increasing costs with the technology is acting as a restraint for the market growth.
Opportunity
-
Rise in the investments for R&D
The rise in R&D activities and increasing adoption of cloud-based services and applications will provide beneficial opportunities for market growth.
The industry of AI in biopharma continues to grow after a long period of sepsis. This is reflected in the ongoing flow of investments and increase in the number of collaborations between pharmaceutical corporations and AI companies in 2021 to the previous years. The Biopharma industry’s growth is largely influenced by the active engagement of leading pharmaceutical corporations in AI-related investments. The number of scientific publications in the field of AI in Biopharma, and research collaborations between pharma companies and AI-expertise vendors are rapidly increasing, yet, some pharma corporations are still critical of AI applications. ML and AI applications in the pharmaceutical and healthcare industries lead to the formation of a new interdisciplinary field of data-driven drug discovery in healthcare. Thus, rise in investment in R&D activities is acting as an opportunity for market growth.
Challenge
- Lack of skilled professionals
The shortage of skilled professionals is expected to hamper the market growth. The employees have to re-train or learn new skill sets to work efficiently on the complex AI machines to get the desired results for the drug. This challenge that prevents full-fledged adoption of AI in the pharmaceutical industry includes the lack of skilled personnel to operate AI-based platforms, limited budget for small organizations, apprehension of replacing humans leading to job loss, skepticism about the data generated by AI, and the black box phenomenon (that is, how the conclusions are reached by the AI platform). The shortage of skills acts as a major hindrance to drug discovery through AI, discouraging companies to adopt AI-based machines for drug discovery.
As skill demands are too high, it has manifested as a challenge to retain and manage skill-specified professionals. Moreover, technological advancement is another aspect that leads to the increased demand for skilled professionals. There is an urgent need for the education of professionals for AI-based technology. Lack of trained and experienced professionals and persistent skill gaps limit the employability prospects and access to quality jobs. It is therefore apparent that the availability of professionals equipped with adequate skills is challenging the market growth.
Post-COVID-19 Impact on Asia-Pacific Artificial Intelligence (AI) in Drug Discovery Market
The COVID-19 outbreak had a beneficial impact on the expansion of AI in drug discovery industry due to its widespread use by various organizations for the identification as well as screening of existing medicines used in the treatment of COVID-19. AI is useful in detecting active chemicals for the prevention of SARS-CoV, HIV, SARS-CoV-2, influenza virus, and others. During the pandemic, economies all over the world relied on AI-based medication discovery rather than traditional vaccine detection processes, which take years to create and are equally expensive, contributing to the growth of the market.
Manufacturers are making various strategic decisions to bounce back post-COVID-19. The players are conducting multiple R&D activities to improve the technology involved in the Wireless microphone. With this, the companies will bring advanced and accurate AI software to the market.
Recent Developments
- In March 2022, NVIDIA Corporation launched Clara Holoscan MGX to develop and deploy real-time AI applications. Clara Holoscan MGX expands the Clara Holoscan platform to provide an all-in-one, medical-grade reference architecture, as well as long-term software support, to accelerate innovation in the medical device industry. This will help the company for better AI performance in health sector for surgery, diagnostics, and drug discovery.
- In May 2022, Benevolent AI, a leading clinical-stage AI-enabled drug discovery company, announced that AstraZeneca has selected an additional novel target for Idiopathic Pulmonary Fibrosis (IPF) for its drug development portfolio, resulting in a milestone payment to Benevolent AI. This is the third novel target from the collaboration that has been identified using the Benevolent Platform across two disease areas, IPF and chronic kidney disease, and subsequently validated and selected for portfolio entry by AstraZeneca. This builds upon the recent extension of the collaboration with AstraZeneca to include two new disease areas, systemic lupus erythematosus, and heart failure, signed in January 2022. This has helped the company to make its collaboration stronger.
Asia-Pacific Artificial Intelligence (AI) in Drug Discovery Market Scope
Asia-Pacific Artificial Intelligence (AI) in drug discovery market is segmented into application, technology, drug type, offering, indication, and end use. The growth among segments helps you analyze niche pockets of growth and strategies to approach the market and determine your core application areas and the difference in your target markets.
APPLICATION
- Novel Drug Candidates
- Drug Optimization and Repurposing Preclinical Testing and Approval
- Drug Monitoring
- Finding New Diseases Associated Targets and Pathways
- Understanding Disease Mechanisms
- Aggregating and Synthesizing Information
- Formation & Qualification of Hypotheses
- De Novo Drug Design
- Finding Drug Targets of an Old Drug
- Others
En fonction des applications, le marché est segmenté en nouveaux candidats médicaments, optimisation et réorientation des médicaments, tests précliniques et approbation, surveillance des médicaments, recherche de nouvelles cibles et voies associées aux maladies, compréhension des mécanismes des maladies, agrégation et synthèse des informations, formation et qualification d'hypothèses, conception de médicaments de novo, recherche de cibles médicamenteuses d'un ancien médicament, et autres.
TECHNOLOGIE
- Apprentissage automatique (ML)
- Apprentissage profond (AP)
- Traitement du langage naturel (TLN)
- Autres
Sur la base de la technologie, le marché est segmenté en Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP) et autres.
TYPE DE MÉDICAMENT
- Petite molécule
- Grosse molécule
En fonction du type de médicament, le marché est segmenté en petites molécules et en grandes molécules.
OFFRE
- Logiciel
- Services
En fonction de l’offre, le marché est segmenté en logiciels et services.
INDICATION
- Immuno-Oncologie
- Maladies neurodégénératives
- Maladies cardiovasculaires
- Maladies métaboliques
- Autres
En fonction des indications, le marché est segmenté en immuno-oncologie, maladies neurodégénératives, maladies cardiovasculaires, maladies métaboliques et autres.
UTILISATION FINALE
- Sociétés pharmaceutiques et biotechnologiques
- Organismes de recherche sous contrat (ORC)
- Centres de recherche et instituts universitaires
- Autres
En fonction de l'utilisation finale, le marché est segmenté en sociétés pharmaceutiques et biotechnologiques, organisations de recherche sous contrat (CRO), centres de recherche et instituts universitaires, et autres.
Analyse/perspectives régionales du marché de la découverte de médicaments en Asie-Pacifique
Le marché de l’intelligence artificielle (IA) dans la découverte de médicaments en Asie-Pacifique est analysé et des informations sur la taille du marché sont fournies par application, technologie, type de médicament, offre, indication et utilisation finale.
Les pays couverts dans ce rapport de marché sont la Chine, le Japon, l'Inde, la Corée du Sud, Singapour, la Thaïlande, la Malaisie, l'Australie et la Nouvelle-Zélande, les Philippines, l'Indonésie et le reste de l'Asie-Pacifique.
- En 2022, l'Asie-Pacifique est la troisième région la plus dominante en raison de la demande accrue de kits de diagnostic des maladies infectieuses due à l'augmentation du nombre de patients et à la sensibilisation croissante de la population. La Chine devrait croître en raison de l'augmentation des avancées technologiques dans le domaine de l'IA pour la découverte de médicaments.
La section pays du rapport fournit également des facteurs d'impact sur les marchés individuels et des changements de réglementation sur le marché national qui ont un impact sur les tendances actuelles et futures du marché. Des points de données tels que les nouvelles ventes, les ventes de remplacement, la démographie des pays, les actes réglementaires et les tarifs d'importation et d'exportation sont quelques-uns des principaux indicateurs utilisés pour prévoir le scénario de marché pour les différents pays. En outre, la présence et la disponibilité des marques d'Asie-Pacifique et les défis auxquels elles sont confrontées en raison de la concurrence importante ou rare des marques locales et nationales, ainsi que l'impact des canaux de vente sont pris en compte lors de l'analyse prévisionnelle des données nationales.
Paysage concurrentiel et analyse des parts de marché de l'intelligence artificielle (IA) dans la découverte de médicaments en Asie-Pacifique
Le paysage concurrentiel du marché de l'intelligence artificielle (IA) dans la découverte de médicaments en Asie-Pacifique fournit des détails par concurrent. Les détails inclus sont la présentation de l'entreprise, les finances de l'entreprise, les revenus générés, le potentiel du marché, les investissements en R&D, les nouvelles initiatives du marché, les sites et installations de production, les forces et les faiblesses de l'entreprise, le lancement de produits, les pipelines d'essais de produits, les approbations de produits, les brevets, la largeur et l'ampleur du produit, la domination des applications, la courbe de survie technologique. Les points de données ci-dessus fournis ne concernent que l'orientation de l'entreprise vers le marché de l'intelligence artificielle (IA) dans la découverte de médicaments en Asie-Pacifique.
Certains des principaux acteurs opérant sur le marché sont NVIDIA Corporation, IBM Corp., Atomwise Inc., Microsoft, Benevolent AI, Aria Pharmaceuticals, Inc., DEEP GENOMICS, Exscientia, Cloud, Insilico Medicine, Cyclica, NuMedii, Inc., Envisagenics, Owkin Inc., BERG LLC, Schrödinger, Inc., XtalPi Inc. et BIOAGE Inc. entre autres.
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Table des matières
1 INTRODUCTION
1.1 OBJECTIVES OF THE STUDY
1.2 MARKET DEFINITION
1.3 OVERVIEW OF ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET
1.4 CURRENCY AND PRICING
1.5 LIMITATIONS
1.6 MARKETS COVERED
2 MARKET SEGMENTATION
2.1 MARKETS COVERED
2.2 GEOGRAPHICAL SCOPE
2.3 YEARS CONSIDERED FOR THE STUDY
2.4 DBMR TRIPOD DATA VALIDATION MODEL
2.5 PRIMARY INTERVIEWS WITH KEY OPINION LEADERS
2.6 MULTIVARIATE MODELLING
2.7 MARKET APPLICATION COVERAGE GRID
2.8 SOURCE LIFELINE CURVE
2.9 DBMR MARKET POSITION GRID
2.1 VENDOR SHARE ANALYSIS
2.11 SECONDARY SOURCES
2.12 ASSUMPTIONS
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHT
4.1 PESTEL ANALYSIS
4.2 PORETSR’S FIVE FORCES
5 MARKET OVERVIEW
5.1 DRIVERS
5.1.1 THE RISE IN INCIDENCE OF CHRONIC DISEASES PROPELS NEED FOR ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY
5.1.2 STRATEGIC COLLABORATIONS, PARTNERSHIPS, AND PRODUCTS LAUNCH
5.1.3 REDUCTION IN TOTAL TIME INVOLVED IN DRUG DISCOVERY PROCESS
5.1.4 ADVANCEMENT OF ARTIFICIAL INTELLIGENCE IN THE HEALTHCARE INDUSTRY
5.2 RESTRAINTS
5.2.1 HIGH COST ASSOCIATED WITH TECHNOLOGY AND TECHNICAL LIMITATIONS
5.2.2 DISADVANTAGES AND RISKS ASSOCIATED WITH AI IN DRUG DISCOVERY
5.2.3 LACK OF AVAILABLE QUALITY DATA
5.3 OPPORTUNITIES
5.3.1 RISE IN THE INVESTMENTS FOR R&D
5.3.2 RISING HEALTHCARE INFRASTRUCTURE
5.3.3 DEVELOPMENT OF NOVEL TOOLS
5.4 CHALLENGES
5.4.1 THE ASIA PACIFIC SHORTAGE OF AI TALENT
5.4.2 ETHICAL, LEGAL, AND REGULATORY ISSUES FOR AI ADOPTION IN THE PHARMACEUTICAL SCIENCES
6 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING
6.1 OVERVIEW
6.2 SOFTWARE
6.2.1 INTEGRATED
6.2.2 STANDALONE
6.3 SERVICES
7 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY
7.1 OVERVIEW
7.2 MACHINE LEARNING (ML)
7.2.1 SUPERVISED LEARNING
7.2.2 UNSUPERVISED LEARNING
7.2.3 REINFORCEMENT LEARNING
7.3 DEEP LEARNING
7.4 NATURAL LANGUAGE PROCESSING (NLP)
7.5 OTHERS
8 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET , BY DRUG TYPE
8.1 OVERVIEW
8.2 SMALL MOLECULE
8.3 LARGE MOLECULE
9 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION
9.1 OVERVIEW
9.2 NOVEL DRUG CANDIDATES
9.2.1 PREDICT BIOACTIVITY OF SMALL MOLECULE
9.2.2 IDENTIFY BIOLOGICS TARGET
9.2.3 OTHERS
9.3 DRUG OPTIMISATION AND RE-PURPOSING PRE-CLINICAL TESTING AND APPROVAL
9.4 DRUG MONITORING
9.5 AGGREGATING AND SYNTHESIZING INFORMATION
9.6 DE NOVO DRUG DESIGN
9.7 FINDING DRUG TARGETS OF AN OLD DRUG
9.8 FORMATION & QUALIFICATION OF HYPOTHESES
9.9 UNDERSTANDING DISEASE MECHANISMS
9.1 FINDING NEW DISEASE-ASSOCIATED TARGETS AND PATHWAYS
9.11 OTHERS
10 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION
10.1 OVERVIEW
10.2 IMMUNE-ONCOLOGY
10.2.1 BREAST CANCER
10.2.2 LUNG CANCER
10.2.3 COLORECTAL CANCER
10.2.4 PROSTATE CANCER
10.2.5 PANCREATIC CANCER
10.2.6 BRAIN CANCER
10.2.7 LEUKEMIA
10.2.8 OTHERS
10.3 NEURODEGENERATIVE DISEASES
10.4 CARDIOVASCULAR DISEASES
10.5 METABOLIC DISEASES
10.6 OTHERS
11 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET , BY END USE
11.1 OVERVIEW
11.2 CONTRACT RESEARCH ORGANIZATIONS
11.3 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES
11.4 RESEARCH CENTERS AND ACADEMIC INSTITUTES
11.5 OTHERS
12 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION
12.1 ASIA-PACIFIC
12.1.1 CHINA
12.1.2 JAPAN
12.1.3 SOUTH KOREA
12.1.4 INDIA
12.1.5 AUSTRALIA & NEW ZEALAND
12.1.6 SINGAPORE
12.1.7 THAILAND
12.1.8 MALAYSIA
12.1.9 INDONESIA
12.1.10 PHILIPPINES
12.1.11 REST OF ASIA-PACIFIC
13 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: COMPANY LANDSCAPE
13.1 COMPANY SHARE ANALYSIS: ASIA PACIFIC
14 SWOT ANALYSIS
15 COMPANY PROFILES
15.1 NVIDIA CORPORATION
15.1.1 COMPANY SNAPSHOT
15.1.2 REVENUE ANALYSIS
15.1.3 COMPANY SHARE ANALYSIS
15.1.4 PRODUCT PORTFOLIO
15.1.5 RECENT DEVELOPMENTS
15.2 MICROSOFT
15.2.1 COMPANY SNAPSHOT
15.2.2 REVENUE ANALYSIS
15.2.3 COMPANY SHARE ANALYSIS
15.2.4 PRODUCT PORTFOLIO
15.2.5 RECENT DEVELOPMENT
15.3 IBM CORP
15.3.1 COMPANY SNAPSHOT
15.3.2 REVENUE ANALYSIS
15.3.3 COMPANY SHARE ANALYSIS
15.3.4 PRODUCT PORTFOLIO
15.3.5 RECENT DEVELOPMENT
15.4 SCHRÖDINGER, INC.
15.4.1 COMPANY SNAPSHOT
15.4.2 REVENUE ANALYSIS
15.4.3 COMPANY SHARE ANALYSIS
15.4.4 PRODUCT PORTFOLIO
15.4.5 RECENT DEVELOPMENTS
15.5 BERG LLC
15.5.1 COMPANY SNAPSHOT
15.5.2 COMPANY SHARE ANALYSIS
15.5.3 PRODUCT PORTFOLIO
15.5.4 RECENT DEVELOPMENTS
15.6 ARDIGEN
15.6.1 COMPANY SNAPSHOT
15.6.2 PRODUCT PORTFOLIO
15.6.3 RECENT DEVELOPMENTS
15.7 EXSCIENTIA
15.7.1 COMPANY SNAPSHOT
15.7.2 REVENUE ANALYSIS
15.7.3 PRODUCT PORTFOLIO
15.7.4 RECENT DEVELOPMENTS
15.8 ARIA PHARMACEUTICALS, INC.
15.8.1 COMPANY SNAPSHOT
15.8.2 PRODUCT PORTFOLIO
15.8.3 RECENT DEVELOPMENTS
15.9 ATOMWISE INC.
15.9.1 COMPANY SNAPSHOT
15.9.2 PRODUCT PORTFOLIO
15.9.3 RECENT DEVELOPMENTS
15.1 BENEVOLENT AI
15.10.1 COMPANY SNAPSHOT
15.10.2 REVENUE ANALYSIS
15.10.3 PRODUCT PORTFOLIO
15.10.4 RECENT DEVELOPMENTS
15.11 BIOAGE INC.,
15.11.1 COMPANY SNAPSHOT
15.11.2 PRODUCT PORTFOLIO
15.11.3 RECENT DEVELOPMENTS
15.12 CLOUD
15.12.1 COMPANY SNAPSHOT
15.12.2 PRODUCT PORTFOLIO
15.12.3 RECENT DEVELOPMENT
15.13 CYCLICA
15.13.1 COMPANY SNAPSHOT
15.13.2 PRODUCT PORTFOLIO
15.13.3 RECENT DEVELOPMENTS
15.14 DEEP GENOMICS
15.14.1 COMPANY SNAPSHOT
15.14.2 PRODUCT PORTFOLIO
15.14.3 RECENT DEVELOPMENTS
15.15 ENVISAGENICS
15.15.1 COMPANY SNAPSHOT
15.15.2 PRODUCT PORTFOLIO
15.15.3 RECENT DEVELOPMENTS
15.16 INSILICO MEDICINE
15.16.1 COMPANY SNAPSHOT
15.16.2 PRODUCT PORTFOLIO
15.16.3 RECENT DEVELOPMENTS
15.17 NUMEDII, INC.
15.17.1 COMPANY SNAPSHOT
15.17.2 PRODUCT PORTFOLIO
15.17.3 RECENT DEVELOPMENT
15.18 OWKIN INC.
15.18.1 COMPANY SNAPSHOT
15.18.2 PRODUCT PORTFOLIO
15.18.3 RECENT DEVELOPMENT
15.19 XTALPI INC.
15.19.1 COMPANY SNAPSHOT
15.19.2 PRODUCT PORTFOLIO
15.19.3 RECENT DEVELOPMENTS
16 QUESTIONNAIRE
17 RELATED REPORTS
Liste des tableaux
TABLE 1 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 2 ASIA PACIFIC SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 3 ASIA PACIFIC SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 4 ASIA PACIFIC SERVICES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 5 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 6 ASIA PACIFIC MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 7 ASIA PACIFIC MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 8 ASIA PACIFIC DEEP LEARNING IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 9 ASIA PACIFIC NATURAL LANGUAGE PROCESSING (NLP) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 10 ASIA PACIFIC OTHERS IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 11 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 12 ASIA PACIFIC SMALL MOLECULE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 13 ASIA PACIFIC LARGE MOLECULE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 14 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 15 ASIA PACIFIC NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 16 ASIA PACIFIC NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 17 ASIA PACIFIC DRUG OPTIMISATION AND RE-PURPOSING PRE-CLINICAL TESTING AND APPROVAL IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 18 ASIA PACIFIC DRUG MONITORING IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 19 ASIA PACIFIC AGGREGATING AND SYNTHESIZING INFORMATION IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 20 ASIA PACIFIC DE NOVO DRUG DESIGN IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 21 ASIA PACIFIC FINDING DRUG TARGETS OF AN OLD DRUG IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 22 ASIA PACIFIC FORMATION & QUALIFICATION OF HYPOTHESES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 23 ASIA PACIFIC UNDERSTANDING DISEASE MECHANISMS IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 24 ASIA PACIFIC FINDING NEW DISEASE-ASSOCIATED TARGETS AND PATHWAYS IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 25 ASIA PACIFIC OTHERS IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 26 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 27 ASIA PACIFIC IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 28 ASIA PACIFIC IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 29 ASIA PACIFIC NEURODEGENERATIVE DISEASES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 30 ASIA PACIFIC CARDIOVASCULAR DISEASES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 31 ASIA PACIFIC METABOLIC DISEASES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 32 ASIA PACIFIC OTHERS IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 33 GLOB ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 34 ASIA PACIFIC CONTRACT RESEARCH ORGANIZATIONS IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 35 ASIA PACIFIC PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 36 ASIA PACIFIC RESEARCH CENTRES AND ACADEMIC INSTITUTES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 37 ASIA PACIFIC OTHERS IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 38 ASIA-PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY COUNTRY, 2020-2029 (USD MILLION)
TABLE 39 ASIA-PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 40 ASIA-PACIFIC SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 41 ASIA-PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 42 ASIA-PACIFIC MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 43 ASIA-PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 44 ASIA-PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 45 ASIA-PACIFIC NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 46 ASIA-PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 47 ASIA-PACIFIC IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 48 ASIA-PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 49 CHINA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 50 CHINA SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 51 CHINA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 52 CHINA MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 53 CHINA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 54 CHINA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 55 CHINA NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 56 CHINA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 57 CHINA IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 58 CHINA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 59 JAPAN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 60 JAPAN SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 61 JAPAN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 62 JAPAN MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 63 JAPAN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 64 JAPAN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 65 JAPAN NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 66 JAPAN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 67 JAPAN IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 68 JAPAN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 69 SOUTH KOREA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 70 SOUTH KOREA SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 71 SOUTH KOREA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 72 SOUTH KOREA MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 73 SOUTH KOREA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 74 SOUTH KOREA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 75 SOUTH KOREA NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 76 SOUTH KOREA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 77 SOUTH KOREA IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 78 SOUTH KOREA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 79 INDIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 80 INDIA SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 81 INDIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 82 INDIA MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 83 INDIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 84 INDIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 85 INDIA NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 86 INDIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 87 INDIA IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 88 INDIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 89 AUSTRALIA & NEW ZEALAND ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 90 AUSTRALIA & NEW ZEALAND SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 91 AUSTRALIA & NEW ZEALAND ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 92 AUSTRALIA & NEW ZEALAND MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 93 AUSTRALIA & NEW ZEALAND ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 94 AUSTRALIA & NEW ZEALAND ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 95 AUSTRALIA & NEW ZEALAND NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 96 AUSTRALIA & NEW ZEALAND ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 97 AUSTRALIA & NEW ZEALAND IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 98 AUSTRALIA & NEW ZEALAND ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 99 SINGAPORE ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 100 SINGAPORE SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 101 SINGAPORE ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 102 SINGAPORE MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 103 SINGAPORE ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 104 SINGAPORE ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 105 SINGAPORE NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 106 SINGAPORE ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 107 SINGAPORE IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 108 SINGAPORE AARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 109 THAILAND ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 110 THAILAND SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 111 THAILAND ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 112 THAILAND MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 113 THAILAND ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 114 THAILAND ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 115 THAILAND NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 116 THAILAND ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 117 THAILAND IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 118 THAILAND ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 119 MALAYSIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 120 MALAYSIA SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 121 MALAYSIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 122 MALAYSIA MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 123 MALAYSIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 124 MALAYSIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 125 MALAYSIA NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 126 MALAYSIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 127 MALAYSIA IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 128 MALAYSIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 129 INDONESIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 130 INDONESIA SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 131 INDONESIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 132 INDONESIA MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 133 INDONESIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 134 INDONESIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 135 INDONESIA NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 136 INDONESIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 137 INDONESIA IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 138 INDONESIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 139 PHILIPPINES ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 140 PHILIPPINES SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 141 PHILIPPINES ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 142 PHILIPPINES MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 143 PHILIPPINES ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 144 PHILIPPINES ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 145 PHILIPPINES NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 146 PHILIPPINES ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 147 PHILIPPINES IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 148 PHILIPPINES ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 149 REST OF ASIA-PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
Liste des figures
FIGURE 1 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: SEGMENTATION
FIGURE 2 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: DATA TRIANGULATION
FIGURE 3 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: DROC ANALYSIS
FIGURE 4 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: ASIA PACIFIC VS REGIONAL MARKET ANALYSIS
FIGURE 5 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: COMPANY RESEARCH ANALYSIS
FIGURE 6 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: INTERVIEW DEMOGRAPHICS
FIGURE 7 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: MARKET APPLICATION COVERAGE GRID
FIGURE 8 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: DBMR MARKET POSITION GRID
FIGURE 9 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: VENDOR SHARE ANALYSIS
FIGURE 10 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: SEGMENTATION
FIGURE 11 THE GROWING NEED TO CURB DRUG DISCOVERY COSTS AND REDUCE TIME INVOLVED IN THE DRUG DEVELOPMENT PROCESS, THE RISING ADOPTION OF CLOUD-BASED APPLICATIONS AND SERVICES, AND THE IMPENDING PATENT EXPIRY OF BLOCKBUSTER DRUGS ARE EXPECTED TO DRIVE THE GROWTH OF THE ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET IN THE FORECAST PERIOD OF 2022 TO 2029
FIGURE 12 SOFTWARE IS EXPECTED TO ACCOUNT FOR THE LARGEST SHARE OF THE ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET IN 2022 AND 2029
FIGURE 13 DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES OF THE ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET
FIGURE 14 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY OFFERING, 2021
FIGURE 15 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY OFFERING, 2022-2029 (USD MILLION)
FIGURE 16 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY OFFERING, CAGR (2022-2029)
FIGURE 17 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY OFFERING, LIFELINE CURVE
FIGURE 18 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY TECHNOLOGY, 2021
FIGURE 19 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY TECHNOLOGY, 2022-2029 (USD MILLION)
FIGURE 20 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY TECHNOLOGY, CAGR (2022-2029)
FIGURE 21 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY TECHNOLOGY, LIFELINE CURVE
FIGURE 22 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET : BY DRUG TYPE, 2021
FIGURE 23 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET : BY DRUG TYPE, 2022-2029 (USD MILLION)
FIGURE 24 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET : BY DRUG TYPE, CAGR (2022-2029)
FIGURE 25 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET : BY DRUG TYPE, LIFELINE CURVE
FIGURE 26 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY APPLICATION, 2021
FIGURE 27 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY APPLICATION, 2020-2029 (USD MILLION)
FIGURE 28 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY APPLICATION, CAGR (2022-2029)
FIGURE 29 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY APPLICATION, LIFELINE CURVE
FIGURE 30 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY INDICATION, 2021
FIGURE 31 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY INDICATION, 2020-2029 (USD MILLION)
FIGURE 32 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY INDICATION, CAGR (2022-2029)
FIGURE 33 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY INDICATION, LIFELINE CURVE
FIGURE 34 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY END USE, 2021
FIGURE 35 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY END USE, 2022-2029 (USD MILLION)
FIGURE 36 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET : BY END USE, CAGR (2022-2029)
FIGURE 37 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET : BY END USE, LIFELINE CURVE
FIGURE 38 ASIA-PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: SNAPSHOT (2021)
FIGURE 39 ASIA-PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY COUNTRY (2021)
FIGURE 40 ASIA-PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY COUNTRY (2022 & 2029)
FIGURE 41 ASIA-PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY COUNTRY (2021 & 2029)
FIGURE 42 ASIA-PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY OFFERING (2022-2029)
FIGURE 43 ASIA PACIFIC ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: COMPANY SHARE 2021 (%)
Méthodologie de recherche
La collecte de données et l'analyse de l'année de base sont effectuées à l'aide de modules de collecte de données avec des échantillons de grande taille. L'étape consiste à obtenir des informations sur le marché ou des données connexes via diverses sources et stratégies. Elle comprend l'examen et la planification à l'avance de toutes les données acquises dans le passé. Elle englobe également l'examen des incohérences d'informations observées dans différentes sources d'informations. Les données de marché sont analysées et estimées à l'aide de modèles statistiques et cohérents de marché. De plus, l'analyse des parts de marché et l'analyse des tendances clés sont les principaux facteurs de succès du rapport de marché. Pour en savoir plus, veuillez demander un appel d'analyste ou déposer votre demande.
La méthodologie de recherche clé utilisée par l'équipe de recherche DBMR est la triangulation des données qui implique l'exploration de données, l'analyse de l'impact des variables de données sur le marché et la validation primaire (expert du secteur). Les modèles de données incluent la grille de positionnement des fournisseurs, l'analyse de la chronologie du marché, l'aperçu et le guide du marché, la grille de positionnement des entreprises, l'analyse des brevets, l'analyse des prix, l'analyse des parts de marché des entreprises, les normes de mesure, l'analyse globale par rapport à l'analyse régionale et des parts des fournisseurs. Pour en savoir plus sur la méthodologie de recherche, envoyez une demande pour parler à nos experts du secteur.
Personnalisation disponible
Data Bridge Market Research est un leader de la recherche formative avancée. Nous sommes fiers de fournir à nos clients existants et nouveaux des données et des analyses qui correspondent à leurs objectifs. Le rapport peut être personnalisé pour inclure une analyse des tendances des prix des marques cibles, une compréhension du marché pour d'autres pays (demandez la liste des pays), des données sur les résultats des essais cliniques, une revue de la littérature, une analyse du marché des produits remis à neuf et de la base de produits. L'analyse du marché des concurrents cibles peut être analysée à partir d'une analyse basée sur la technologie jusqu'à des stratégies de portefeuille de marché. Nous pouvons ajouter autant de concurrents que vous le souhaitez, dans le format et le style de données que vous recherchez. Notre équipe d'analystes peut également vous fournir des données sous forme de fichiers Excel bruts, de tableaux croisés dynamiques (Fact book) ou peut vous aider à créer des présentations à partir des ensembles de données disponibles dans le rapport.
