2032, Global Artificial Intelligence (AI) in Drug Discovery Market Revenue Report

The Global Artificial Intelligence (AI) In Drug Discovery Market is rapidly expanding due to its potential to revolutionize the pharmaceutical industry. AI enables the analysis of vast amounts of data at an unprecedented speed, helping to identify potential drug targets and streamline the drug development process. It offers improved accuracy, efficiency, and cost-effectiveness in predicting drug interaction, toxicity, and efficacy. The market is expected to witness significant growth in the coming years as more pharmaceutical companies adopt AI technologies for faster and more effective drug discovery.

Global artificial intelligence (AI) in drug discovery market will reach $2.57 billion by 2026, growing by 30.3% annually over 2020-2026 despite the COVID-19 impact.

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Highlighted with 86 tables and 86 figures, this 178-page report “Global Artificial Intelligence (AI) in Drug Discovery Market 2020-2026 by Offering, Technology, Drug Type, Therapeutic Area, Application, End User, and Region: Trend Forecast and Growth Opportunity” is based on a comprehensive research of the entire global AI in drug discovery market and all its sub-segments through extensively detailed classifications. Profound analysis and assessment are generated from premium primary and secondary information sources with inputs derived from industry professionals across the value chain. The report provides historical market data for 2015-2019, revenue estimates for 2020, and forecasts from 2021 till 2026. (Please note: The report will be updated before delivery so that the latest historical year is the base year and the forecast covers at least 5 years over the base year.)

In-depth qualitative analyses include identification and investigation of the following aspects:

• Market Structure
• Growth Drivers
• Restraints and Challenges
• Emerging Product Trends & Market Opportunities
• Porter’s Fiver Forces

The trend and outlook of global market is forecast in optimistic, balanced, and conservative view by taking into account of COVID-19. The balanced (most likely) projection is used to quantify global AI in drug discovery market in every aspect of the classification from perspectives of Offering, Technology, Drug Type, Therapeutic Area, Application, End User, and Region.

Based on offering, the global market is segmented into the following sub-markets with annual revenue for 2015-2026 (historical and forecast) included in each section.

• Software
• Service

Based on technology, the global market is segmented into the following sub-markets with annual revenue for 2015-2026 (historical and forecast) included in each section.

• Deep Learning
• Supervised Learning
• Reinforcement Learning
• Unsupervised Learning
• Other Technologies

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Based on drug type, the global market is segmented into the following sub-markets with annual revenue for 2015-2026 (historical and forecast) included in each section.

• Large-molecule Drugs
• Small-molecular Drugs

Based on therapeutic area, the global market is segmented into the following sub-markets with annual revenue for 2015-2026 (historical and forecast) included in each section.

• Oncology
• Neurodegenerative Diseases
• Cardiovascular Disease
• Metabolic Diseases
• Other Therapeutic Areas

Some of the key questions answered in this report: 

• Which are the five top players of the Global Artificial Intelligence (AI) in Drug Discovery Market?
• How will the Global Artificial Intelligence (AI) in Drug Discovery Market change in the upcoming years?
• Which product and application will take a share of the Global Artificial Intelligence (AI) in Drug Discovery Market?
• What are the drivers and restraints of the Global Artificial Intelligence (AI) in Drug Discovery Market?
• Which regional market will show the highest growth?
• What will be the CAGR and size of the Global Artificial Intelligence (AI) in Drug Discovery Market throughout the forecast period?
• What is the current market size, what will the market size be in 2030 and what will the growth rate be?
• What are the challenges to grow in the market?
• What are the market opportunities and challenges faced by the key vendors?
• Who are the major competitors and what is their strategy?
• What are the barriers to entry for new players in the market?

Based on application, the global market is segmented into the following sub-markets with annual revenue for 2015-2026 (historical and forecast) included in each section.

• Information & Data Analysis
• Drug Design
• Drug Evaluation
• Clinical Trials
• Other Applications

Based on end user, the global market is segmented into the following sub-markets with annual revenue for 2015-2026 (historical and forecast) included in each section.

• Pharmaceutical & Biotechnology Companies
• Academic & Research Institutes
• Contract Research Organizations

Geographically, the following regions together with the listed national/local markets are fully investigated:

• APAC (Japan, China, South Korea, Australia, India, and Rest of APAC; Rest of APAC is further segmented into Malaysia, Singapore, Indonesia, Thailand, New Zealand, Vietnam, and Sri Lanka)
• Europe (Germany, UK, France, Spain, Italy, Russia, Rest of Europe; Rest of Europe is further segmented into Belgium, Denmark, Austria, Norway, Sweden, The Netherlands, Poland, Czech Republic, Slovakia, Hungary, and Romania)
• North America (U.S., Canada, and Mexico)
• South America (Brazil, Chile, Argentina, Rest of South America)
• RoW (Saudi Arabia, UAE, Egypt)

For each of the aforementioned regions and countries, detailed analysis and data for annual revenue are available for 2015-2026. The breakdown of all regional markets by country and split of key national markets by Technology, Therapeutic Area, and End User over the forecast years are also included.

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The report also covers current competitive scenario and the predicted trend; and profiles key vendors including market leaders and important emerging players.

Specifically, potential risks associated with investing in global AI in drug discovery market are assayed quantitatively and qualitatively through Market Data Library’s Risk Assessment System. According to the risk analysis and evaluation, Critical Success Factors (CSFs) are generated as a guidance to help investors & stockholders identify emerging opportunities, manage and minimize the risks, develop appropriate business models, and make wise strategies and decisions.

Key Players (this may not be a complete list and extra companies can be added upon request):

Atomwise, Inc.

BenevolentAI

Berg LLC

Bioage

BIOAGE

Cloud Pharmaceuticals, Inc.

Cyclica

Deep Genomics

Envisagenics

Exscientia

Google

IBM Corporation

Insilico Medicine

Microsoft Corporation

Numedii, Inc.

Numerate

NVIDIA Corporation

Owkin, Inc.

Twoxar, Incorporated

Verge Genomics

Xtalpi, Inc.

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