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Global AI for Drug Discovery Market Projected to Grow to USD 2,596.6 Million by 2026

28-May-2021 | Facts and Factors

According to Facts and Factors, the global AI for Drug Discovery Market was valued at about USD 360.01 million in 2020 and is predicted to create revenue of about USD 2,596.6 million by the end of 2026, rising at a CAGR of roughly 39% between 2021 and 2026.

This report was duly updated with regards to the impacts of the COVID-19 pandemic on the AI for Drug Discovery Market on the global as well as regional levels in terms of qualitative and quantitative analysis.

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Artificial intelligence (AI) is increasingly being used in numerous sectors of society, particularly the pharmaceutical industry. In the pharmaceutical industry, there has been a significant increase in data digitization over the last few years. However, the test of acquiring, scrutinizing, and applying knowledge to resolve critical clinical problems comes with digitalization. This encourages the use of AI, which can handle large amounts of data with improved automation. Artificial intelligence is a technology-based system that employs a variety of advanced tools and networks to simulate human intelligence. It does not impend to replace human presence. AI employs systems and software which can read and learn from input data in order to make independent decisions for achieving specific goals. Its applications in the pharmaceutical field are constantly being expanded.

Existing players are competing fiercely, owing to the rising demand for lower drug discovery costs. Furthermore, strategic expansions by companies in the form of mergers and acquisitions, collaboration agreements are expected to increase competition and drive market growth. For example, in May 2021, Exscientia has announced the signing of a collaboration agreement with Bristol-Myers Squibb Company. This expanded collaboration has the potential to contribute to Bristol Myers Squibb's drug pipeline while also strengthening Exscientia's portfolio of shared assets. The collaboration will use artificial intelligence to speed up the discovery of small molecule therapeutic drug candidates in a variety of therapeutic areas, including oncology and immunology. The agreement calls for up to USD 50 million in upfront funding, up to USD 125 million in near-to-mid-term potential milestones, and additional clinical, regulatory, and commercial payments that could push the deal's potential value beyond USD 1.2 billion.

Top Market Players

As companies begin to expand their artificial intelligence offerings in the drug discovery space, the surge in AI adoption is expected to continue. Some of the key players in the artificial intelligence in drug discovery market are NVIDIA Corporation, IBM Watson, Google, Atomwise, Inc., Deep Genomics, Cloud Pharmaceuticals, Inc., Xtalpi, Inc., Verge Genomics, Insilico Medicine, Benevolent AI, Microsoft Corporation, Exscientia, Owkin, Inc., Berg LLC, Cyclica, Bioage, Numerate, Numedii, Inc., Envisagenics, Twoxar, Incorporated, GNS Healthcare, BioSymetrics and Euretos amongst others.

Market Dynamics

In recent years, there has been a growing push to reduce the cost of novel drug discovery and production, which is expected to boost demand for artificial intelligence (AI) platforms in the drug discovery space. According to industry publications, the average cost of novel drug discovery and development is USD 2.6 billion. This is primarily due to the narrow development testing funnel, which eliminates the vast majority of candidate therapies during preclinical and phase - 1 trial. As a result, the adoption of artificial intelligence for faster, more efficient, and cost-effective drug discovery is gaining traction among stakeholders in the pharmaceutical industry. A major factor promoting the use of artificial intelligence in drug discovery is the massive amount of data generated by molecule screening processes and preclinical studies. A large amount of data makes it difficult for the scientist to review all of the scientific literature. In such cases, artificial intelligence can aid in the screening process by shortening the time required to study and identify drug molecule interactions and histology data. Another important aspect of the increasing use of AI in drug discovery is the availability of a plethora of options for carrying out standard processes, such as data mining and the customization capabilities of artificial intelligence platforms. Advances in artificial intelligence, such as machine learning and deep learning, enable pharmaceutical companies to precisely recognize the drug's molecule binding properties.

In 2020, oncology had the highest revenue share of 29.8 percent in the AI in drug discovery market, based on therapeutic area. AI is already being used to aid in the early detection of cancer. Furthermore, because cancer treatments differ for each patient, personalized medicine has proven to be an effective alternative for cancer treatment. Artificial intelligence platforms that detect genetic mutations assist oncologists in designing effective personalized treatments for patients. Sophia Genetics, a Swiss company, for example, has developed an AI platform that aids in the detection of tumors by identifying gene variations and aids in the design of personalized medicine for cancer treatment.

North America Lead the Global AI for Drug Discovery Market Growth

In 2020, North America dominated the market, accounting for the highest revenue share of 57.8 percent. One of the main reasons for the large market share is the widespread adoption of AI systems in the United States, which is aided by the presence of several companies in the country. According to the findings of the RELX survey, AI adoption has increased from 48.0 percent in 2018 to 72.0 percent in 2019. This is primarily due to businesses' growing positive perception of AI. The Asia Pacific is expected to be the market's fastest-growing region. The region's market for AI platforms for drug discovery is expected to be driven by the growing adoption of new technology in India and China for new drug development, as well as a focus on boosting pharmaceutical capacities within the countries. By the end of the forecast period, the market in this region is expected to grow at a CAGR of 44.7 percent.

Browse the full report titled “AI in Drug Discovery Market by Drug Type (Small Molecule and Large Molecule), By Technology ((Machine Learning (Deep Learning, Supervised Learning, Reinforcement Learning, Unsupervised Learning) and Others)), By Therapeutic Area (Metabolic Diseases, Cardiovascular Diseases, Immuno-Oncology, Oncology, Neurodegenerative Diseases, Others), By End User (Pharmaceutical Companies, Biopharmaceutical Companies, Academic & Research Institutes, and Others): Global and Regional Industry Perspective, Comprehensive Analysis, and Forecasts, 2021–2026” report at https://www.fnfresearch.com/ai-for-drug-discovery-market-by-drug-type

The global AI for Drug Discovery market is segmented as follows: 

By Drug Type: 

  • Small Molecule
  • Large Molecule

By Technology:

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

By Therapeutic Area:

  • Metabolic Diseases
  • Cardiovascular Diseases
  • Immuno-Oncology
  • Oncology
  • Neurodegenerative Diseases
  • Others

By End User:

  • Pharmaceutical Companies
  • Biopharmaceutical Companies
  • Academic & Research Institutes
  • Others

By Region:

  • North America
    • The U.S.
    • Canada
  • Europe
    • France
    • The UK
    • Spain
    • Germany
    • Italy
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Southeast Asia
    • Rest of Asia Pacific
  • Latin America
    • Brazil
    • Mexico
    • Rest of Latin America
  • Middle East & Africa
    • GCC Countries
    • South Africa
    • Rest of Middle East & Africa

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