The new Artificial Intelligence (AI) in Drug Discovery Market report offers a comprehensive study of the present scenario of the market coupled with major market dynamics. Also, it highlights the in-depth market analysis with the latest trends, drivers and its segments with respect to regional and country. Further, this report profiles the top key players of the Artificial Intelligence (AI) in Drug Discovery and analyze their market share, strategic development, and other development across the globe.
The research report also covers the comprehensive profiles of the key players in the market and an in-depth view of the competitive landscape worldwide. The major players in the artificial intelligence ( ai) in drug discovery market include Microsoft Corporation (US), Exscientia (UK), NVIDIA Corporation (US), Schrödinger (US), Atomwise, Inc. (US), BenevolentAI (UK), NuMedii (US), Google (US), Insilico Medicine (US), BERG LLC (US), Cloud Pharmaceuticals (US), Cyclica (Canada), Deep Genomics (Canada), IBM (US), BIOAGE (US), Valo Health (US), Envisagenics (US), twoXAR (US), XtalPi (US), Verge Genomics (US), Owkin, Inc. (US), Biovista (US), Evaxion Biotech (Denmark), Iktos (France), Standigm (South Korea), and BenchSci (Canada). This section consists of a holistic view of the competitive landscape that includes various strategic developments such as key mergers acquisitions, future capacities, partnerships, financial overviews, collaborations, new product developments, new product launches, and other developments.
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Market Dynamics
Some of the main drivers propelling the growth of AI in the drug delivery market include the rising usage of cloud-based applications and services and the impending patent expiration of blockbuster pharmaceuticals. Additional factors boosting demand are the growing need to control drug discovery costs and less time required for drug development. Further, the technology demand is also rising due to the discovery and development of novel pharmacological therapies and the expanding manufacturing capabilities of the life science industry. However, several problems are anticipated to impede the growth of this industry in the years to come, including a lack of skilled AI workers, hazy regulatory requirements for medical software, and a lack of data sets in this area. Nonetheless, the growing frequency of cross-industry partnerships will be a major driver influencing the market's development rate.
The report covers Porter’s Five Forces Model, Market Attractiveness Analysis, and Value Chain analysis. These tools help to get a clear picture of the industry’s structure and evaluate the competition attractiveness at a global level. Additionally, these tools also give an inclusive assessment of each segment in the global market of artificial intelligence ( ai) in drug discovery. The growth and trends of Artificial Intelligence ( AI) in Drug Discovery Industry provide a holistic approach to this study.
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Market Segmentation
This section of the artificial intelligence ( ai) in drug discovery market report provides detailed data on the segments by analyzing them at country and regional level, thereby assisting the strategist in identifying the target demographics for the respective product or services with the upcoming opportunities.
By Offering
- Software
- Services
By Technology
- Machine Learning
- Deep Learning
- Supervised Learning
- Reinforcement Learning
- Unsupervised Learning
- Other Machine Learning Technologies
- Other Technologies
By Application
- Immuno-Oncology
- Neurodegenerative Diseases
- Cardiovascular Diseases
- Metabolic Diseases
- Other Applications
By End User
- Pharmaceutical Biotechnology Companies
- Contract Research Organizations
- Research Centers And Academic Government Institutes
Regional Analysis
This section covers the regional outlook, which accentuates current and future demand for the Artificial Intelligence ( AI) in Drug Discovery market across North America, Europe, Asia-Pacific, Latin America, and Middle East Africa. Further, the report focuses on demand, estimation, and forecast for individual application segments across all the prominent regions.
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