Artificial Intelligence (AI) in Drug Discovery Market Seeking Excellent Growth |Industry Share, Size …

Artificial intelligence (AI) in drug discovery market report brings into light key market dynamics of the sector. It gives an in-depth knowledge on what the recent developments are, product launches are, while also keeping the track for recent acquisitions, mergers, joint ventures and competitive research in the global market industry. This report is intended to help the readers develop a practical and intelligent approach to market dynamics and exploit opportunities. The Artificial intelligence (AI) in drug discovery market report is a professional yet exhaustive study on the current as well as future state for the market. This report analyzes the status and future forecast involving sales, value (revenue), growth rate (CAGR), market share, historical and forecast in the major regions of the world.

Artificial intelligence (AI) in drug discovery market is expected to gain market growth in the forecast period of 2020 to 2027. Data Bridge Market Research analyses the market to account to USD 3,932.87 million by 2027 growing at a CAGR of 40.5% in the above-mentioned forecast period. The growing awareness amongst the physicians and patients regarding the benefits of artificial intelligence has been directly impacting the growth of the market.

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Competitive Landscape and Artificial Intelligence (AI) in Drug Discovery Market Share Analysis

Artificial intelligence (AI) in drug discovery market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in research and development, new market initiatives, global presence, production sites and facilities, production capacities, company strengths and weaknesses, product launch, product width and breadth, application dominance. The above data points provided are only related to the companies’ focus related to artificial intelligence (AI) in drug discovery market.

The major players covered in the artificial intelligence (AI) in drug discovery market report are Microsoft, NVIDIA Corporation, IBM Corporation, Atomwise, Inc., DEEP GENOMICS, Cloud Pharmaceuticals, Inc., Insilico Medicine, BenevolentAI   Ltd, Exscientia, Cyclica Inc., Numerate, NuMedii, Inc., Envisagenics., twoXAR, Incorporated, OWKIN, INC., XtalPi Inc., BERG LLC, among other domestic and global players. Market share data is available for Global, North America, Europe, Asia-Pacific (APAC), Middle East and Africa (MEA) and South America separately. DBMR analysts understand competitive strengths and provide competitive analysis for each competitor separately.

The market analysis and insights covered in this Artificial intelligence (AI) in drug discovery market   business document offers key statistics on the market status of global and regional manufacturers and is an imperative source of guidance which provides exact direction to the companies and individuals interested in the industry. This report contains a bottomless knowledge and information on what the market’s definition, classifications, applications, and engagements are and also explains the drivers and restraints of the market which is derived from SWOT analysis. The important highlights of this market report are key market dynamics, current market scenario and future prospects of the sector.

Increasing need to reduce cost and drug discovery along with reduce time, growth of pharmaceutical industries by collaborations with other industries, adoption of cloud based services and applications, delay in patent expiry are some of the factors that will enhance the growth of artificial intelligence (AI) in drug discovery market in the forecast period of 2020-2027. On the other hand, expansion of biotechnology industries will further create new and ample opportunities for the growth of artificial intelligence (AI) in drug discovery market in the above mentioned forecast period.

Unavailability of skilled labour and lack of data sets are acting as market challenges for the growth of artificial intelligence (AI) in drug discovery in the above mentioned forecast period.

This artificial intelligence (AI) in drug discovery market report provides details of new recent developments, trade regulations, import export analysis, production analysis, value chain optimization, market share, impact of domestic and localised market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on artificial intelligence (AI) in drug discovery market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.

TABLE OF CONTENTS

PART 01: EXECUTIVE SUMMARY

PART 02: SCOPE OF THE REPORT

PART 03: RESEARCH METHODOLOGY

PART 04: MARKET LANDSCAPE

• Market ecosystem
• Market characteristics
• Market segmentation analysis

PART 05: PIPELINE ANALYSIS

• Pipeline analysis

PART 06: MARKET SIZING

• Market definition
• Market sizing
• Market size and forecast

PART 07: FIVE FORCES ANALYSIS

• Bargaining power of buyers
• Bargaining power of suppliers
• Threat of new entrants
• Threat of substitutes
• Threat of rivalry
• Market condition

PART 08: MARKET SEGMENTATION

• Segmentation
• Comparison
• Market opportunity

PART 09: CUSTOMER LANDSCAPE

PART 10: REGIONAL LANDSCAPE

• Geographical segmentation
• Regional comparison
• North America
• South America
• Europe
• MEA
• APAC
• Market opportunity

PART 11: DECISION FRAMEWORK

PART 12: DRIVERS AND CHALLENGES

• Market drivers
• Market challenges

PART 13: MARKET TRENDS

PART 14: VENDOR LANDSCAPE

• Overview
• Landscape disruption

PART 15: VENDOR ANALYSIS

• Vendors covered
• Vendor classification
• Market positioning of vendors

PART 16: APPENDIX

• List of abbreviations

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Global Artificial Intelligence (AI) in Drug Discovery Market Scope and Market Size

Artificial intelligence (AI) in drug discovery market is segmented on the basis of offering, technology, drug type, application and end user. The growth amongst these segments will help you analyse meagre growth segments in the industries, and provide the users with valuable market overview and market insights to help them in making strategic decisions for identification of core market applications.

Based on offering, artificial intelligence (AI) in drug discovery market is segmented into software and services.
On the basis of technology, artificial intelligence (AI) in drug discovery market is segmented into machine learning and other technologies. Machine learning has been further segmented into deep learning, supervised learning, reinforcement learning, unsupervised learning and other machine learning technologies.
Based on drug type, artificial intelligence (AI) in drug discovery market is segmented into small molecule and large molecules.
On the basis of application, artificial intelligence (AI) in drug discovery market is segmented into immuno-oncology, neurodegenerative diseases, cardiovascular disease, metabolic diseases and other applications.
Artificial intelligence (AI) in drug discovery market has also been segmented based on the end user into pharmaceutical & biotechnology companies, contract research organizations, research centres and academic & government institutes.

Research objectives

To perceive the most influencing pivoting and hindering forces in Artificial intelligence (AI) in drug discovery market and its footprint in the international market.
Learn about the market policies that are being endorsed by ruling respective organizations.
To gain a perceptive survey of the market and have an extensive interpretation of the Artificial intelligence (AI) in drug discovery market and its materialistic landscape.
To understand the structure of Artificial intelligence (AI) in drug discovery market by identifying its various sub segments.
Focuses on the key global Artificial intelligence (AI) in drug discovery market  players, to define, describe and analyze the sales volume, value, market share, market competition landscape, SWOT analysis and development plans in next few years.
To analyze competitive developments such as expansions, agreements, new product launches, and acquisitions in the market.
To share detailed information about the key factors influencing the growth of the market (growth potential, opportunities, drivers, industry-specific challenges and risks).
To project the consumption of Artificial intelligence (AI) in drug discovery market  submarkets, with respect to key regions (along with their respective key countries).
To strategically profile the key players and comprehensively analyze their growth strategies
To analyze the Artificial intelligence (AI) in drug discovery market  with respect to individual growth trends, future prospects, and their contribution to the total market.

Growth of Pharmaceutical Companies and Cloud Based Services

Artificial intelligence (AI) in drug discovery market also provides you with detailed market analysis for every country growth in healthcare expenditure for capital equipment’s, installed base of different kind of products for artificial intelligence (AI) in drug discovery market, impact of technology using life line curves and changes in healthcare regulatory scenarios and their impact on the artificial intelligence (AI) in drug discovery market. The data is available for historic period 2010 to 2018.

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The Global Anomaly Detection Market was valued at USD 1.89 billion in 2016 and is projected to reach USD 7.56 billion by 2025, growing at a CAGR of 16.65% from 2017 to 2025.

Anomaly detection is the identification of data points, items, observations or events that do not conform to the expected pattern of a given group. Anomaly detection is used in behavioral analysis and other forms of analysis in order to aid in learning about the detection, identification and prediction of the occurrence of these anomalies. The benefits of anomaly detection includes the ability to – monitor any data source, rapidly identify zero-day attacks as well as unknown security threats, find unusual behavior across data sources, and discovers anomalies in event stream.

The Final Report will cover the impact analysis of COVID-19 on this industry:

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Sample Infographics:

Market Dynamics:
1. Market Drivers
1.1 Need for anomaly detection in streaming data from assets and optimization of business processes
1.2 Growing adoption of black box trading by market traders
1.3 Increasing data rate
1.4 Rise in cyber espionage and fraudulent activities
1.5 Increasing threats among enterprises
2. Market Restraints
2.1 Asymmetric faults detection
2.2 Lack of technical expertise
2.3 Presence of open source alternatives

Market Segmentation:
The Global Anomaly Detection Market is segmented on the technology, component, network behavior anomaly detection, user behavior anomaly detection, organization size, deployment model, vertical, and region.
1 BY TECHNOLOGY
1.1 Data mining and business intelligence
1.2 Machine learning and artificial intelligence
1.3 Big data analytics
2 BY COMPONENT
2.1 Solution
2.1.1 Network behavior anomaly detection
2.1.2 User behavior anomaly detection
2.2 Service
2.2.1 Managed services
2.2.2 Professional services
3 BY DEPLOYMENT TYPE
3.1 On-Premises
3.2 Cloud
3.3 Hybrid
4 BY VERTICAL
4.1 Government and Defense
4.2 IT and Telecommunications
4.3 Banking, Financial Services, and Insurance (BFSI)
4.4 Retail
4.5 Healthcare
4.6 Manufacturing
4.7 Others

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5 BY REGION:
1.1 North America (U.S., Canada, Mexico)
1.2 Europe (Germany, UK, France, Rest of Europe)
1.3 Asia Pacific (China, India, Japan, Rest of Asia Pacific)
1.4 Latin America (Brazil, Argentina, Rest of Latin America)
1.5 Middle East & Africa

Competitive Landscape:
The major players in the market are as follows:
1. IBM Corporation
2. SAS Institute Inc.
3. Dell Technologies, Inc.
4. Trustwave Holdings, Inc.
5. Cisco Systems, Inc.
6. LogRhythm, Inc.
7. Hewlett Packard Enterprise Company
8. Splunk, Inc.
9. Guardian Analytics
10. Symantec Corporation
11. Anodot, Ltd.
12. GreyCortex s.r.o.
13. Niara, Inc.
14. Securonix, Inc.
15. Wipro Limited

These major players have adopted various organic as well as inorganic growth strategies such as mergers & acquisitions, new product launches, expansions, agreements, joint ventures, partnerships, and others to strengthen their position in this market.

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RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH:
Research study on the Global Anomaly Detection Market was performed in five phases which include Secondary research, Primary research, subject matter expert advice, quality check and final review.
The market data was analyzed and forecasted using market statistical and coherent models. Also market shares and key trends were taken into consideration while making the report. Apart from this, other data models include Vendor Positioning Grid, Market Time Line Analysis, Market Overview and Guide, Company Positioning Grid, Company Market Share Analysis, Standards of Measurement, Top to Bottom Analysis and Vendor Share Analysis.

To know more about the research methodology of verified market research and other aspects of the research study, kindly get in touch with our sales team

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Kenneth Research provides market research reports to different individuals, industries, associations and organizations with an aim of helping them to take prominent decisions. Our research library comprises of more than 10,000 research reports provided by more than 15 market research publishers across different industries. Our collection of market research solutions covers both macro level as well as micro level categories with relevant and suitable market research titles. As a global market research reselling firm, Kenneth Research provides significant analysis on various markets with pure business intelligence and consulting services on different industries across the globe. In addition to that, our internal research team always keep a track on the international and domestic market for any economic changes impacting the products’ demand, growth and opportunities for new and existing players.

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