AI in Drug Discovery Market is Expected to Reach $4.0 billion | MarketsandMarkets.

Chicago, Oct. 24, 2023 (GLOBE NEWSWIRE) -- In the near future, artificial intelligence (AI) will catalyze a transformative revolution in the drug discovery industry. By leveraging advanced machine learning algorithms and high-performance computing, AI will expedite the process of drug development, substantially reducing costs and timelines. With the ability to rapidly analyze massive datasets, AI will identify novel drug candidates, predict potential side effects, and optimize compound design with unparalleled precision. Moreover, AI-driven virtual clinical trials will enable more efficient testing and approval processes. As a result, the drug discovery landscape will witness a paradigm shift towards more personalized, effective, and accessible healthcare solutions, fundamentally changing the way we combat diseases and improve patient outcomes.

AI in Drug Discovery market in terms of revenue was estimated to be worth $0.6 billion in 2022 and is poised to reach $4.0 billion by 2027, growing at a CAGR of 45.7% from 2022 to 2027 according to a latest report published by MarketsandMarkets™. The growing need to curb the drug discovery cost & reduce the overall time taken in this process, the rising adoption of cloud-based applications and services, and the impending patent expiry of blockbuster drugs are some of the key factors driving the growth of this market.

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AI in Drug Discovery Market Scope:

Report Coverage Details
Market Revenue in 2022 $0.6 billion
Estimated Value by 2027 $4.0 billion
Growth Rate Poised to grow at a CAGR of 45.7%
Market Size Available for 2020-2027
Forecast Period 2022-2027
Forecast Units Value (USD Billion)
Report Coverage Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
Segments Covered Offering, Technology, Application, End User, and Region
Geographies Covered North America (US, and Canada), Europe (Germany, France, UK, Italy, and the RoE), Asia Pacific (Japan, China, India, and RoAPAC), and RoW
Report Highlights Updated financial information / product portfolio of players
Key Market Opportunity Growing biotechnology industry
Key Market Driver Growing number of cross-industry collaborations and partnerships

AI in Drug Discovery market major players covered in the report, such as:

  • NVIDIA Corporation (US)
  • Microsoft (US)
  • Google (US)
  • Exscientia (UK)
  • Schrödinger (US)
  • Atomwise, Inc. (US)
  • BenevolentAI (UK)
  • NuMedii (US)
  • Cloud Pharmaceuticals (US)
  • Insilico Medicine (US)
  • Cyclica (Canada)
  • Deep Genomics (Canada)
  • IBM (US)
  • Valo Health (US)
  • Envisagenics (US)
  • twoXAR (US)
  • Owkin, Inc. (US)
  • XtalPi (US)
  • Verge Genomics (US)
  • Biovista (US)
  • Evaxion Biotech (Denmark)
  • Iktos (France)
  • Standigm (South Korea)
  • BenchSci (Canada)
  • and Among Others

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The study categorizes the AI in drug discovery market into the following segments and subsegments:

AI in drug discovery market, By Offering

  • Software
  • Services

AI in drug discovery market, By Technology

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

AI in drug discovery market, by Application

  • Immuno-oncology
  • Neurodegenerative diseases
  • Cardiovascular diseases
  • Metabolic diseases
  • Other Applications

AI in drug discovery market, By End User

  • Pharmaceutical & biotechnology companies       
  • Contract research organizations
  • Research centers and academic & government institutes

AI in drug discovery Market, By Region,

  • North America  
    • US
    • Canada
  • Europe
    • Germany
    • France
    • UK
    • Italy
    • Rest of Europe
  • Asia Pacific         
    • Japan
    • China
    • India
    • Rest of Asia Pacific
  • ROW

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The key stakeholders in the AI in Drug Discovery market include:

  • Pharmaceutical Companies: These organizations are investing heavily in AI to streamline drug discovery processes, reduce costs, and accelerate the development of new drugs.
  • Biotechnology Companies: Biotech firms are utilizing AI to enhance their research and development efforts, identify potential drug candidates, and optimize drug design.
  • AI Technology Providers: Companies specializing in AI and machine learning technologies offer the tools, software, and platforms needed for drug discovery, such as virtual screening, predictive modeling, and data analysis.
  • Academic and Research Institutions: Universities and research centers are actively involved in AI-driven drug discovery, contributing to the development of innovative methodologies and solutions.
  • Contract Research Organizations (CROs): CROs provide specialized services in AI-assisted drug discovery, allowing pharmaceutical companies to outsource specific aspects of their research processes.
  • Regulatory Authorities: Government agencies and regulatory bodies play a crucial role in overseeing the incorporation of AI technologies in drug development and ensuring compliance with safety and efficacy standards.
  • Investors and Venture Capitalists: Funding and investment entities support startups and innovative companies in the AI in Drug Discovery space, fostering innovation and growth.
  • Healthcare Providers: Hospitals and healthcare institutions benefit from AI in drug discovery by gaining access to more effective and targeted treatment options for their patients.
  • Patients: Ultimately, patients stand to gain from AI in drug discovery as it leads to the development of more precise and personalized therapies, potentially improving health outcomes and quality of life.
  • Ethics and Privacy Advocates: Organizations and individuals focused on the ethical implications and data privacy concerns related to AI in drug discovery are essential stakeholders in ensuring responsible and transparent use of these technologies.

Recent Developments:

  • In March 2021, Iktos (France) collaborated with Pfizer (US) to apply Iktos’ AI-driven de novo design software to selected small-molecule programs of Pfizer
  • In October 2020, Genesis Therapeutics (US) partnered with Genentech (US) for a multi-target drug development deal using Genesis’ graph machine learning capabilities to identify drug candidates for a range of disorders.
  • In February 2021, Exscientia (UK) and the University of Oxford collaborated to develop treatments for Alzheimer's disease

Frequently Asked Questions (FAQs) of AI in Drug Discovery Market:

What is the projected market of the global AI in drug discovery market in 2027?
The projected market of the global AI in drug discovery market is expected to be 4.0 billion in 2027.

Who are the leading and emerging players in the AI in drug discovery market?
Some of the leading players in the 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).

Who are the major end-users of the AI in drug discovery market?
Pharmaceutical & biotechnology companies, CROs, and research centers and academic & government institutes. Pharmaceutical & biotechnology companies are the largest end user of this market

What are the major Offering/product in the AI in drug discovery market?
Based on offering, the AI in drug discovery market is segmented into software, and services. The services segment accounted for the largest share of the global market

What are the major applications of AI in drug discovery market?
Neurodegenerative diseases, immuno-oncology, cardiovascular diseases, metabolic diseases, and few other applications.

What are the major technology in the AI in drug discovery market?
Machine learning and other technology. The machine learning technology further includes deep learning, supervised learning. reinforcement learning, unsupervised learning, and other machine learning technologies

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Report Objectives:

  • To define, describe, and forecast the global AI in drug discovery market based on offering, application, technology, end user, and region
  • To provide detailed information regarding the major factors (such as drivers, restraints, opportunities, and challenges) influencing the market growth
  • To strategically analyze micromarkets1 with respect to individual growth trends, prospects, and contributions to the overall AI in drug discovery market
  • To analyze opportunities in the market for stakeholders and provide details of the competitive landscape for market leaders
  • To strategically analyze the market structure and profile the key players of the AI in drug discovery market and comprehensively analyze their core competencies2
  • To forecast the size of the market segments with respect to four regions, namely, North America, Europe, Asia Pacific, and the Rest of the World (Latin America and the Middle East & Africa)
  • To track and analyze competitive developments such as product launches, acquisitions, partnerships, agreements, and collaborations in the AI in drug discovery market during the forecast period

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