Artificial Intelligence in Drug Discovery Market to Witness Robust Growth by 2027| Top Players mbu timeline – mbu timeline
According to Reports and Data, theArtificial Intelligence in Drug Discovery Marketwas valued at USD 253.8 million in 2019 and is expected to reach USD 2,127.9 million by the year 2027, at a CAGR of 31.9%. Artificial intelligence has known to have enormous applications in the field of drug discovery as it helps to analyze outbreaks, develop cures for diseases, and also predict which animal viruses tend to mutate. In drug discovery, artificial intelligence has known to improve research and development, which allowed researchers to discover treatments for chronic diseases. The use of machine learning to manage the huge number of data sets is increasing advances in drug discovery. The rising need to manage drug discovery costs is expected to drive the market in the future.
Drug discovery includes various processes and stages that demand a huge amount of funds. Moreover, clinical trials and acceptance of the drug in the market could be a challenging task. Artificial intelligence is capable of reducing such high costs in research and development as it finds solutions faster and with precision. Furthermore, increasing collaborations among companies to produce patented drugs could also be a major driver for the market. Artificial intelligence may reduce a large amount of time utilized in the drug discovery process. Therefore, reduction in time factor could be a primary market driver in the forecast period. The increasing demand for cloud-based software that enables the researcher to design drugs quickly and accurately is expected to drive the market widely.
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Some Key Factors Contributing to the Global Pharma & Healthcare Market Growth
Unprecedented revenue growth of the global pharma & healthcare industry is attributed to factors such as rising prevalence of chronic and acute diseases worldwide, increasing geriatric population, rising awareness of health & wellness among consumers, and growing demand for more advanced healthcare services. Increasing demand for advanced drugs and therapeutics, growing availability of next-generation diagnostics and treatment options especially in developing countries like India and China rise in R&D activities and clinical trials in the pharmaceutical and biotechnology sectors, increasing public and private investments in healthcare research projects, and rising consumer expenditure on healthcare are among the other significant factors contributing to the industry revenue growth.
Further key findings from the report suggest
Top Players in the Global Artificial Intelligence in Drug Discovery Market:
NVIDIA Corporation, Deep Genomics, Cloud Pharmaceuticals, IBM Corporation, Microsoft and Google, Insilico Medicine, BenevolentAI, Cyclica, BERG LLC, and Envisagenics.
The coronavirus pandemic has had a drastic impact on the global healthcare industry, with rising cases of COVID-19 worldwide, substantially growing hospital admission and readmission rates, and rising demand for telehealth and telemedicine services for remote patient monitoring. Furthermore, rising focus on development of rapid COVID-19 diagnostics such as the RT-PCR test kits, increased government funding for vaccine development, stringent regulatory norms and protocols for COVID-19 safety, and increasing sales of COVID-19 safety equipment, such as N-95 masks, face shields, PPE kits, and hand sanitizers, have driven the global pharma & healthcare industry revenue growth over the recent past.
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Artificial Intelligence in Drug Discovery Market Segmentation:
By Drug Type Outlook (Revenue in Million USD; 20172027)
By Offerings Outlook (Revenue in Million USD; 20172027)
By Technology Outlook (Revenue in Million USD; 20172027)
By Application Outlook (Revenue in Million USD; 20172027)
By End Use Outlook (Revenue in Million USD; 20172027)
Global Artificial Intelligence in Drug Discovery Market Report: Regional Segmentation
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Global Artificial Intelligence in Drug Discovery Market: Table of Contents
Chapter 1. Methodology & Sources
1.1. Market Definition
1.2. Research Scope
1.3. Methodology
1.4. Research Sources
1.4.1. Primary Sources
1.4.2. Secondary Sources
1.4.3. Paid Sources
1.5. Market Estimation Technique
Chapter 2. Executive Summary
Chapter 3. Key Insights
Chapter 4. Global Pharma & Healthcare Market Segmentation
4.1. Global Pharma & Healthcare Market COVID-19 Impact Analysis
4.2. Industrial Outlook
4.2.1. Market indicators analysis
4.2.2. Market drivers analysis
4.2.3. Market restraints analysis
4.3. Technological Insights
4.4. Porters Five Forces Analysis
4.5. Regulatory Framework
4.6. Price trend Analysis
4.7. Competitive Metric Space Analysis
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