The Global Intelligent Drug Discovery Market research study by Emergen Research is a thorough compendium of analytical data regarding the Intelligent Drug Discovery sector. The Intelligent Drug Discovery Market is segmented in the study, along with a thorough breakdown of the market's size in terms of volume and value. The research includes a detailed prediction for the years 2020–2027 as well as the present Intelligent Drug Discovery Market scenario. The Intelligent Drug Discovery Market research contains a thorough analysis of each industry vertical, segment, end-use industry, application, and region's historical, current, and forecast revenue.

According to a recent report by Emergen Research, the worldwide intelligent drug discovery market is expected to be valued USD 3,711.8 million by 2027. The market for intelligent medication technology is expanding, and several pharmaceutical firms are concentrating on the creation of medicines that use artificial intelligence. Pharma firms are utilising technology to find treatments for ailments that are more complex.

The growing adoption of cloud-based applications and the expiration of patented drugs will pave the way for new generic and OTC medicines, which will influence market demand. The advancement in deep learning and machine learning will allow pharmaceutical companies to reorganize molecule binding properties with high accuracy.

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Global Intelligent Drug Discovery Market Highlights:

• Regional demand estimation and forecast
• Product Mix Matrix
• RD Analysis
• Cost-Benefit Analysis
• Pre-commodity pricing volatility
• Supply chain optimization analysis
• Technological updates analysis
• Raw Material Sourcing Strategy
• Competitive Analysis
• Mergers Acquisitions
• Location Quotients Analysis
• Carbon Footprint Analysis
• Patent Analysis
• Vendor Management

Competitive Landscape:

The latest study provides an insightful analysis of the broad competitive landscape of the global Intelligent Drug Discovery market, emphasizing the key market rivals and their company profiles. A wide array of strategic initiatives, such as new business deals, mergers acquisitions, collaborations, joint ventures, technological upgradation, and recent product launches, undertaken by these companies has been discussed in the report. The report analyzes various elements of the market’s competitive scenario, such as the regulatory standards and policies implemented across the industry over recent years. Our team of experts has leveraged several powerful analytical tools, such as Porter’s Five Forces analysis and SWOT analysis, to deliver a comprehensive overview of the global Intelligent Drug Discovery market and pinpoint the fundamental growth trends.  

Key Companies Profiled in the Report are:

IBM Corporation, Microsoft Corporation, Google, NVIDIA Corporation, Cloud Pharmaceuticals, Inc., Atomwise, Inc., Insilico Medicine, Exscientia, Bioage, Envisagenics

Key Parameters Analyzed in This Section:

• Company Profiles
• Gross Revenue
• Profit margins
• Product sales trends
• Product pricing
• Industry Analysis
• Sales distribution channels

Regional Segmentation:

• North America
• Latin America
• Europe
• Middle East Africa
• Asia Pacific

Key Points Covered in This Section:

• Regional contribution
• Estimated revenue generation
• Vital data and information about the consumption rate in all the leading regional segments
• An expected rise in market share
• Forecast growth in the overall consumption rate

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Some Key Highlights from the Report

• In October 2020, Optibrium launched Cerella, an intelligence platform for active learning in drug discovery. Cerella’s architecture combines cloud computing with on-premises deployment offering both scalability and data security.
• The software segment held a larger market share, and factors such as less cost and time, low rate of failure, a large number of software developers for the discovery of drugs, and strong demand from big pharmaceuticals are driving the segment’s demand.
• Machine learning help in optimizing therapy by integrating clinical and biomedical data with computational models. It is used to build software for combinational therapies and testing drugs. Machine learning offers a lucrative potential for drug discovery and personalized medicine.
• The growing incidence of oncology and the potential to affect several facets of cancer therapy will affect the demand for the market. The convergence of cancer therapy and AI has resulted in multiple solutions that address complex challenges. Intelligent platforms can accelerate the drug discovery process.
• AI in medical imaging is witnessing lucrative growth in the Asia Pacific region due to a rise in RD activities and development in the biotechnology and pharmaceutical sectors. Moreover, the presence of a significant patient pool will fuel the demand for better healthcare services, which will drive the demand for the market.

Market Overview:

The report bifurcates the Intelligent Drug Discovery market on the basis of different product types, applications, end-user industries, and key regions of the world where the market has already established its presence. The report accurately offers insights into the supply-demand ratio and production and consumption volume of each segment.

Segments Covered in this report are:

• Offering Outlook (Revenue, USD Billion; 2017-2027)
• Software
• Services

• Technology Outlook (Revenue, USD Billion; 2017-2027)
• Machine Learning
1. Supervised Learning
2. Deep Learning
3. Reinforcement Learning
4. Unsupervised Learning
• Other Technologies

• Application Outlook (Revenue, USD Billion; 2017-2027)
• Neurodegenerative Diseases
• Metabolic Diseases
• Immuno-Oncology
• Cardiovascular Disease
• Others

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Additional information offered by the report:

• Along with a complete overview of the global Cobots market, the report provides detailed scrutiny of the diverse market trends observed on both regional and global levels.
• The report elaborates on the global Cobots market size and share governed by the major geographies.
• It performs a precise market growth forecast analysis, cost analysis, and a study of the micro- and macro-economic indicators.
• It further presents a detailed description of the company profiles of the key market contenders.

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