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The future of AI (Artificial intelligence) in the global drug discovery market looks promising with opportunities in pharmaceutical & biotechnology companies, contract research organizations, and research centers and academic & government institutes. The AI in the global drug discovery market is expected to grow with a CAGR of 39% to 41% from 2021 to 2026. The major drivers for this market are growing pharmaceutical industry, high demand for personalized drug, rising adoption of cloud-based applications & services, growing number of cross-industry collaborations and partnerships, and increasing awareness of AI among drug manufacturers.
A more than 150 page report is developed to help in your business decisions. Sample figures with some insights are shown below. To learn the scope of, benefits, companies researched and other details of AI in drug discovery market report download the report brochure.
The study includes trends and forecasts for the global AI in drug discovery market by offering, drug type, technology, application, end use industry, and region as follows:
By Offering [$M shipment analysis for 2015 – 2026]:
By Drug Type [$M shipment analysis for 2015 – 2026]:
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Small Molecules
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Large Molecules
By Technology [$M shipment analysis for 2015 – 2026]:
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Machine Learning
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Deep Learning
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Supervised Learning
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Reinforcement Learning
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Unsupervised Learning
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Other Machine Learning Technologies
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Other Technologies
By Application [$M shipment analysis for 2015 – 2026]:
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Immuno-Oncology
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Neurodegenerative Diseases
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Cardiovascular Diseases
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Metabolic Diseases
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Others
By End Use Industry [$M shipment analysis for 2015 – 2026]:
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Pharmaceutical & Biotechnology Companies
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Contract Research Organizations
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Research Centers and Academic & Government Institutes
By Region [$M shipment analysis for 2015 – 2026]:
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North America
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United States
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Canada
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Mexico
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Europe
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Germany
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United Kingdom
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France
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Italy
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Asia Pacific
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China
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Japan
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India
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South Korea
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The Rest of the World
Machine learning technology will remain the largest segment due to the capability to collect and handle big data and demand to improve productivity in many end use industries.
Pharmaceutical & biotechnology companies will remain the largest end use industry during the forecast period due to high adoption of AI in the pharmaceutical industry, AI’s high accuracy to identify drug’s molecule binding properties, and increasing demand for drugs for complex conditions.
North America will remain the largest region during the forecast period due to high adoption of AI systems, growing pharmaceutical industry, and a large presence of AI manufacturers and the consumer market.
Some of the AI in drug discovery companies profiled in this report include IBM, Microsoft, Google, NVIDIA, Atomwise, Deep Genomics, Cloud Pharmaceuticals, Insilico Medicine, BenevolentAI, Exscientia, Cyclica, BIOAGE, Numerate, NuMedii, Envisagenics, twoXAR , OWKIN, XtalPi, Verge Genomics, and BERG.
Features of AI in Drug Discovery Market
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Market Size Estimates: AI in drug discovery market size estimation in terms of value ($M)
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Trend and Forecast Analysis: Market trends (2015-2020) and forecast (2021-2026) by various segments and regions.
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Segmentation Analysis: Market size by offering, drug type, technology, application, end use industry
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Regional Analysis: AI in drug discovery market breakdown by North America, Europe, Asia Pacific, and the Rest of the World.
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Growth Opportunities: Analysis on growth opportunities in different end use industries, offering, drug type, technology, application, and regions for AI in drug discovery market.
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Strategic Analysis: This includes M&A, new product development, and competitive landscape for the AI in drug discovery market.
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Analysis of competitive intensity of the industry based on Porter’s Five Forces model.
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This report answers following 11 key questions |
Q.1 What are some of the most promising potential, high-growth opportunities for AI in the global drug discovery market by offering (software, services), drug type (small molecule, large molecules), technology (machine learning (deep learning, supervised learning, reinforcement learning, unsupervised learning, and others) and others technologies), application (immuno-oncology, neurodegenerative diseases, cardiovascular disease, metabolic diseases, and others), end user industry (pharmaceutical & biotechnology companies, contract research organizations, and research centers and academic & government institutes), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
Q.2 Which segments will grow at a faster pace and why?
Q.3 Which regions will grow at a faster pace and why?
Q.4 What are the key factors affecting market dynamics? What are the drivers and challenges for AI in the drug discovery market?
Q.5 What are the business risks and threats to AI in the drug discovery market?
Q.6 What are emerging trends of AI in the drug discovery market and the reasons behind them?
Q.7 What are some changing demands of customers for AI in the drug discovery market?
Q.8 What are the new developments in AI in the drug discovery market? Which companies are leading these developments?
Q.9 Who are the major AI players in the drug discovery market? What strategic initiatives are being implemented by key players for business growth?
Q.10 What are some of the competitive products and processes of AI in the drug discovery market, and how big of a threat do they pose for loss of market share via material or product substitution?
Q.11 What M&A activities did take place in the last five years for AI in the drug discovery market? |