Artificial Intelligence in Drug Discovery Market Size to Reach USD 2,127.9 Million by 2027 | Reports And Data

Artificial Intelligence in Drug Discovery Market Size to Reach USD 2,127.9 Million by 2027 | Reports And Data

Artificial Intelligence in Drug Discovery Market
The study methodologies used to examine Artificial Intelligence in Drug Discovery Market for the forecast period, 2020 – 2027 further classifies the industry by type, geography, end-use and end-user to add more precision and bring to light factors responsible for augmenting business development.

According to Reports and Data, the Artificial Intelligence in Drug Discovery Market was 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. Also, various patents acquired by the companies are expected to be on the verge of expiry, which could drive the market growth. On the other hand, the shortage of skilled personnel and insufficient data in drug discovery could be some restraints for the market.

Key participants in the market include NVIDIA Corporation, Deep Genomics, Cloud Pharmaceuticals, IBM Corporation, Microsoft and Google, Insilico Medicine, BenevolentAI, Cyclica, BERG LLC, and Envisagenics. 

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For the purpose of this report, Reports and Data has segmented the Artificial Intelligence in Drug Discovery Market on the basis of drug type, offerings, technology, application, end use and region:


By Drug Type Outlook (Revenue in Million USD; 2017–2027)

  • Small Molecule
  • Large Molecule


By Offerings Outlook (Revenue in Million USD; 2017–2027)

  • Software
  • Services


By Technology Outlook (Revenue in Million USD; 2017–2027)

  • Deep Learning
  • Machine Learning
  • Others


By Application Outlook (Revenue in Million USD; 2017–2027)

  • Metabolic Diseases
  • Neurodegenerative Diseases
  • Cardiovascular Diseases
  • Oncology
  • Others


By End Use Outlook (Revenue in Million USD; 2017–2027)

  • Pharmaceutical & Medical Device Manufacturing Companies
  • Life Sciences & Biotechnology Research Organizations
  • Hospitals & Healthcare Facilities


Regional Outlook (Revenue in Million USD; 2017–2027)

  • North America
    • U.S
    • Canada
  • Europe
    • Germany
    • France
    • UK
    • Spain
    • Italy
    • Rest of the Europe
  • Asia Pacific
    • China
    • India
    • Japan
    • Rest of Asia-Pacific
  • Middle East & Africa
  • Latin America
    • Brazil


COVID-19 Impact
As the COVID-19 outbreak continues to spread all across the globe, scientists and researchers are exploring every possible option for help battling the coronavirus pandemic. The industry players and researchers are looking to use artificial intelligence as a way of addressing the challenges of the virus. The artificial intelligence represents an engrossing avenue.  Moreover, AI has been used to search for new molecules capable of treating Covid-19, of scanning through lung CTs for signs of Covid-related pneumonia, and to aid the epidemiologists who tracked the disease’s spread early on.

Numerous research projects are using AI to identify timely drugs. For instance, BenevolentAI, a London-based drug-discovery company, the company’s AI-powered knowledge graph can digest large volumes of scientific literature and biomedical research to find links between the genetic and biological properties of diseases and the composition and action of drugs. Furthermore, DeepMind, the AI arm of Google’s parent company Alphabet, is using data on genomes to predict organisms’ protein structure, potentially shedding light on which drugs could work against COVID-19. Additionally, Canadian startup DarwinAI has developed a neural network that can screen X-rays for signs of COVID-19 infection. While using swabs from patients is the default for testing for coronavirus, analyzing chest X-rays could offer an alternative to hospitals that don’t have enough staff or testing kits to process all their patients quickly.

Furthermore, Germany-based Innoplexus has used its drug discovery information engine to design a novel molecule candidate with a high binding affinity to a target protein on the coronavirus while maintaining drug-likeness criteria such as bioavailability, absorption, toxicity, etc. AI firm, Gero, which specializes in AI-driven drug discovery, has used its AI platform to identify the possible anti-COVID-19 drugs. Six of them have been approved, three were withdrawn, and nine have been already tested in clinical trials for other indications. In March 2020, TCS partnered with CSIR to design the AI-based drug discovery process for COVID-19. Besides that, AI is not only able to warn us of an impending epidemic, but it can help us develop, identify and scale new treatments and vaccines as we continue to navigate the solution to contain the pandemic. However, during a pandemic, when people are eager for quick solutions, the dangers of trusting an unproven technology are greater than ever.


Deals landscape

  • In February 2020, Lantheus Holdings Inc. a diagnostic imaging company and Progenics Pharmaceuticals, Inc. an oncology products company, entered into an merger extension
  • In February 2020, Lantheus Holdings Inc. a manufacture and commercialization of innovative diagnostic imaging agents, and Progenics Pharmaceuticals, Inc. a oncology products company, amended a previous merger which has been successfully approved. Such collaborations will help to enhance the sales and the consumer base across the geography.
  • In February 2020, Novartis got into a collaboration with Microsoft for artificial intelligence innovation lab and Amazon Web Services to build an enterprise including data and analytics platform that would produce advanced medicines.
  • In February 2020, OSE Immunotherapeutics formed a merger with MAbSilico to establish and incorporate artificial intelligence for development of new monoclonal antibodies…Continued


Further key findings from the report suggest

  • Applications of Artificial intelligence are huge in drug discovery. Issues such as complex cellular interactions and structures of drugs, while drug targeting could be encountered using artificial intelligence.
  • The market will further propel expected to witness a surge in demand as these tools have become increasingly important. For instance, Pfizer is using IBM Watson, a system that uses machine learning, to power its search for immuno-oncology drugs. Such techniques combined with automation will provide traction to the market in the near future.
  • On industrial level, research organizations is expected to dominate market and it is expected to witness a surge in demand in the midst of COVID-19 pandemic. It is mainly because of the shift of focus towards ongoing research and development in various areas to develop and strategize the best potential clinical outcome for the outbreak
  • Artificial intelligence will utilize complex algorithms and machine learning that would extract meaningful information from a huge dataset. For instance, a dataset of RNA sequencing can be used to identify genes whose expression correlates with a given cellular condition.


Table of Content:

Chapter 1. Market Synopsis
    1.1. Market Definition
    1.2. Research Scope & Premise
    1.3. Methodology
    1.4. Market Estimation Technique
Chapter 2. Executive Summary
    2.1. Summary Snapshot, 2017-2027
Chapter 3. Indicative Metrics
    3.1. Macro-Economic Indicators
          3.1.1. Increasing demand for new types of drug treatments
          3.1.2. Growing prevalence of chronic disorders
Chapter 4. COVID 19 impact assessment
    4.1. Artificial Intelligence in Drug Discovery Industry Outlook
 Q1 2020
 Q2 2020
 Q3 2020
    4.2. Rising Demand for Artificial Intelligence in Drug Discovery market due to COVID-19 pandemic
          4.2.1. Scenario 1: Artificial Intelligence in Drug Discovery market decreased by 4%
         Scenario 1 timeline
         Key indicators for scenario 1
         Covid-19 virus impact on global Artificial Intelligence in Drug Discovery market revenue, 2019–2027: scenario-1


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