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 latest market intelligence study on the Intelligent Drug Discovery market applies the best of both primary and secondary research techniques to bring to light the growth rate of the Intelligent Drug Discovery market for the forecast period, 2020 – 2027. The comprehensive study covers hard to find facts about the market landscape as well as its growth prospects in the years to come. Most importantly, the research report includes vital statistics about the major vendors occupying a strong foothold in this industry. Besides this, in order to calculate the market share, the study takes a closer look at the selling price of the product across different regions.
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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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 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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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
End-User Outlook (Revenue, USD Billion; 2017-2027)
Contract Research Organizations
Pharmaceutical & Biotechnology Companies
Research Centers and Academic & Government Institutes
Regional Outlook (Revenue, USD Billion; 2017-2027)
North America
Europe
Asia Pacific
Latin America
MEA
Table of Content
Chapter 1. Methodology & Sources
1.1. Intelligent Drug Discovery Market Definition
1.2. Intelligent Drug Discovery Market Research Scope
1.3. Intelligent Drug Discovery Market Methodology
1.4. Intelligent Drug Discovery Market Research Sources
1.4.1. Primary
1.4.2. Secondary
1.4.3. Paid Sources
1.5. Intelligent Drug Discovery Market Estimation Technique
Chapter 2. Executive Summary
2.1. Summary Snapshot, 2019-2027
Chapter 3. Key Insights
Chapter 4. Intelligent Drug Discovery Market Segmentation & Impact Analysis
Continued…
