Global Artificial Intelligence (AI) in Drug Discovery Market report involves use of latest tools and techniques for researching, analyzing and gathering of data and information. This market report performs systematic gathering, recording and analysis of data about the issues related to the marketing of goods and services and serves the businesses with an excellent market research report. The report provides intelligent solutions to the complex business challenges and commences an effortless decision-making process. DBMR team of enthusiastic analysts, skilled researchers and experienced forecasters work meticulously to generate such kind of market reports. Research report is a painstaking investigation of current scenario of the market and future estimations which covers several market dynamics.
The large scale Global Artificial Intelligence (AI) in Drug Discovery Market business report gives CAGR values along with its fluctuations for the specific forecast period. The report contains top to bottom analysis and estimation of various market related factors that are incredibly crucial for better decision making. This industry analysis document provides comprehensive explanation of market definition, market segmentation, competitive analysis and key developments in the industry. This market research report is framed with the most excellent and sophisticated tools of collecting, recording, estimating and analyzing market data. The comprehensive report comprises of data that can be pretty indispensable when it is about dominating the market or making a mark in the market as a latest emergent.
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
• Market opportunity
PART 09: CUSTOMER LANDSCAPE
PART 10: REGIONAL LANDSCAPE
• Geographical segmentation
• Regional comparison
• North America
• South America
• Market opportunity
PART 11: DECISION FRAMEWORK
PART 12: DRIVERS AND CHALLENGES
• Market drivers
• Market challenges
PART 13: MARKET TRENDS
PART 14: VENDOR LANDSCAPE
• 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.
- 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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