The global Intelligent Drug Discovery Market is forecasted to be worth USD 3,711.8 Million by 2027, according to a current analysis by Emergen Research. The intelligent drug technology market is growing, and several pharmaceutical companies are focusing on the development of drugs using artificial intelligence. The pharma companies are taking advantage of the technology to discover drugs for more complex diseases.
The Global Intelligent Drug Discovery Market report assesses the historical and current data along with a thorough analysis of the market dynamics. The report also sheds light on the significant market growth driving and restraining factors that are anticipated to influence the market growth through the forecast period. The Global Intelligent Drug Discovery Market studies the market scenario to offer growth projections for the Intelligent Drug Discovery Market industry for the forecast period of 2020-2027. The report focuses on potential growth opportunities and limitations the prominent players of the industry might face during the entirety of the forecast timeline. The report pays special heed to the emerging business components, niche sectors, and product launches and brand promotions occurring in the market to help the readers make fruitful investment strategies.
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Key participants include IBM Corporation, Microsoft Corporation, Google, NVIDIA Corporation, Cloud Pharmaceuticals, Inc., Atomwise, Inc., Insilico Medicine, Exscientia, Bioage, and Envisagenics, among others.
The report further studies the key companies operating in the industry and their company profiles, product portfolio, expansion strategies, and strategic alliances such as mergers and acquisitions, collaborations, and joint ventures, among others. It also offers insights into their market reach and global position, along with highlights about their achievements and financial standings.
Covid 19 impact analysis:
The current COVID-19 pandemic is expected to have an effect on the growth of the Intelligent Drug Discovery Market majorly attributable to the movement restrictions and impact on the supply and demand due to the lockdowns. The economic slowdown and dynamic changes in the demands will further affect the growth of the industry.
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For the purpose of this report, Emergen Research has segmented into the global Intelligent Drug Discovery Market on the offering, technology, application, end-user, and region:
Offering Outlook (Revenue, USD Billion; 2017-2027)
- Software
- Services
Technology Outlook (Revenue, USD Billion; 2017-2027)
- Machine Learning
- Supervised Learning
- Deep Learning
- Reinforcement Learning
- Unsupervised Learning
- Other Technologies
Application Outlook (Revenue, USD Billion; 2017-2027)
- Neurodegenerative Diseases
- Metabolic Diseases
- Immuno-Oncology
- Cardiovascular Disease
- Others
Key regions in the market include:
North America
U.S.
Canada
Europe
U.K.
Italy
Germany
France
Rest of EU
Asia Pacific
India
Japan
China
South Korea
Australia
Rest of APAC
Latin America
Chile
Brazil
Argentina
Rest of Latin America
Middle East Africa
Saudi Arabia
U.A.E.
South Africa
Rest of MEA
Key questions addressed in the report:
Which regional market offers the most attractive growth opportunities to the companies operating in this market?
How is the raw material availability affecting the demand for Intelligent Drug Discovery Market in this industry vertical?
Who are the leading players dominating the global Intelligent Drug Discovery Market Market?
Which factors could potentially hamper the global market growth during the forecast period?
Key Benefits of the Report:
Critical understanding of the key market segments
Comprehensive analysis of the drivers, restraints, trends, and opportunities
Extensive assessment of current and emerging trends of the market
Comprehensive analysis of the competitive scenario and its changing dynamics
Analytical data with detailed SWOT analysis and Porter’s Five Forces analysis
In-depth 8-year analysis of the Global Intelligent Drug Discovery Market
Detailed regional analysis and extensive company profiling
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