Intelligent Drug Discovery Market Competitive Landscape, Analysis, Share, Company Profiles and Forecast by 2027

The growing demand for cost-effective medicines and the adoption of cloud-based applications will drive the demand for intelligent drug discovery.

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.

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.

Global Intelligent Drug Discovery Market Report Forecast to 2027 equips the readers with an overall evaluation of the current market dynamics of the Intelligent Drug Discovery market along with the scope of the study. The global Intelligent Drug Discovery market analyzed in this report is done for scrutinizing and assisting the companies to capitalize on the potential investment and growth opportunities. The report is also furnished with beneficial strategic recommendations that will enable the companies to fortify their market positions.

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Key Market Highlights: The Intelligent Drug Discovery report deeply inspects factors like revenue accumulation, cost, capacity utilization rate, production capacity, production rate, consumption rate, import/export, supply/demand, gross, market share, CAGR, and gross margin. It further presents an all-inclusive study of the market growth factors and their latest trends.

Key Highlights From The Report

  • 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 R&D 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.
  • Key participants include IBM Corporation, Microsoft Corporation, Google, NVIDIA Corporation, Cloud Pharmaceuticals, Inc., Atomwise, Inc., Insilico Medicine, Exscientia, Bioage, and Envisagenics, among others.

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It offers a lucid picture of current trends in the global market, with an unbiased perspective of the leading market players, key regions/countries, end-use industries, and various product types. To be updated, the report is furnished with the latest impact of the currently unfolding coronavirus pandemic on the Sensor Fusion industry. The pandemic began in late 2019 and hit the world in early 2020, disrupting the normal lives and affecting every segment of the world. The report covers the impact of the pandemic on the Sensor Fusion market and its key segment.

  • 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
  • End-User Outlook (Revenue, USD Billion; 2017-2027)
    • Contract Research Organizations
    • Pharmaceutical & Biotechnology Companies
    • Research Centers and Academic & Government Institutes

The Intelligent Drug Discovery market intelligence report exhaustively examines the market value, share, demand, growth prospects, latest and historical trends, manufacturers, gross revenue collection, competitive terrain, market growth forecast, available products, and end-use applications.

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Geographical Intelligent Drug Discovery Market:

  • North America (U.S., Canada, and Mexico)
  • Europe (Germany, France, the U.K, Russia, and Italy)
  • Asia Pacific (China, Japan, Korea, India, and Southeast Asia)
  • Latin America (Brazil, Argentina, Colombia, etc.)
  • Middle East & Africa (Saudi Arabia, UAE, Egypt, Nigeria, and South Africa)

Global Sensor Fusion Market Report – Table of Contents:

  1. Report Overview
  • 1 Research Scope
  • 2 Key Sensor Fusion market segments
  • 3 Target players
  • 4 Market analysis by type
  • 5 Market analysis by application
  • 6 Key learning objectives
  • 7 Report timeline
  1. Global Growth Trends
  • 1 Global Sensor Fusion market size
  • 2 Latest trends of the Sensor Fusion market by region
  • 3 Key corporate trends
  1. Global Sensor Fusion Market share by key players
  • 1 Global Sensor Fusion Market size by manufacturers
  • 2 Global Sensor Fusion Market key players
  • 3 Products/solutions/services of major players
  • 4 New entrants in the Sensor Fusion market
  • 5 Mergers, acquisitions, joint ventures, and expansion plans
  1. Global Sensor Fusion Market by product type
  • 1 Global Sensor Fusion Sales by Product
  • 2 Global Sensor Fusion by Product Revenue

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