AI in Drug Discovery Market Worth $ 2,015.1 Million by 2025 at 40.8% CAGR – Report by Market Research Future (MRFR)

AI in Drug Discovery Market Insights and Industry Analysis by Product Type (Software, Services), Molecule Type (Large Molecule, Small Molecule), Technology (Machine Learning, Deep Learning and others), Indication (Immune-Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases and others), Application (Target Identification, Candidate Screening, De novo Drug Designing, Drug Optimization and Repurposing and Preclinical Testing), End-User (Pharmaceutical & Biotechnology Companies, Contract Research Organizations and Research Centers and Academic & Government Institutes), Region (Americas, Europe, Asia-Pacific, Middle East & Africa), Competitive Market Size, Share, Trends, and Forecast


New York, US, June 17, 2021 (GLOBE NEWSWIRE) -- Artificial Intelligence in Drug Discovery Market Overview:

According to a comprehensive research report by Market Research Future (MRFR), “AI in Drug Discovery Market - Information by Product Type, Molecule Type, Technology, Indication, Application, End-User, and Region - Forecast till 2025” the market is Predicted to reach USD 2,015.1 Million by 2025 at 40.8% CAGR.

Market Scope:

Over the last few years, artificial intelligence (AI) has caught the interest and minds of medical technology practitioners as many firms and major research laboratories have worked to perfect these technologies for clinical use. The first commercialised demonstrations of how AI (also known as deep learning, machine learning, or artificial neural networks) can assist clinicians are now available. These systems can provide a paradigm shift in clinician workflow, increasing productivity while simultaneously improving treatment and patient throughput.

Artificial intelligence in healthcare is booming, and with the limitless possibilities offered by this cutting-edge technology, a slew of business behemoths are investing in healthcare applications. Integration of AI and machine learning tools in drug discovery and development applications could improve healthcare outcomes by increasing drug discovery efficiency, facilitating targeted molecule identification, reducing drug discovery timeframes, and, most importantly, lowering drug development costs for drug manufacturers. Apart from these, a vast number of pharmaceutical firms and entrepreneurs all over the world are launching projects and investing in the creation of AI and machine learning technologies for bettering drug discovery and improving drug development outcomes.

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Competitive Landscape

The major players profiled in Report are:

  • Microsoft Corporation
  • IBM Corporation
  • Google LLC. (A Subsidiary of Alphabet Inc.)
  • Atomwise, Inc.
  • Deep Genomics
  • Cloud Pharmaceuticals, Inc.
  • Insilico Medicine
  • BenevolentAI
  • Exscientia
  • Cyclica
  • Bioage
  • Numerate,Inc.
  • Numedii, Inc.
  • Envisagenics
  • Twoxar
  • Incorporated
  • Owkin, Inc.
  • Xtalpi, Inc.
  • Verge Genomics
  • Berg LLC

Segmental Analysis

The industry is divided into two types of products: software and services. The AI industry is dominated by software, which includes AI platforms focused on machine learning and deep learning technologies. In the global market for AI in drug discovery, the software division has the largest share. Microsoft Azure and Google AI are two of the most popular AI platforms on the market. However, a growing number of small-scale businesses are building AI platforms, propelling the industry forward at an unprecedented pace.

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The market has been divided into large molecules and small molecules based on molecular type. Drug applicants with a huge and diverse molecular structure, such as biologic products, fall into the large segment. Increased use of AI technologies in studying complex molecular structures and drug development in biologics, as well as increased demand for life-saving medicines and biologics.

By technology, the market has been segmented into machine learning, deep learning, others. Machine learning (ML) methods include a range of techniques that can help people make better decisions because they have a lot of good data. The use of machine learning will help to facilitate data-driven decision making, which has the ability to speed up the drug discovery and production process and minimise failure rates. This segment is expected to grow in importance. During the evaluation time, deep learning is projected to be the fastest-growing segment in the AI in drug discovery industry.

By indication, the market has been segmented into immune-oncology, neurodegenerative diseases, cardiovascular diseases, metabolic diseases, and others. In the global market, the immuno-oncology group is projected to have the highest share. In the field of precision medicine, AI technology is showing promise in differentiating genetic mutations. Oncologists can help handle their patients by evaluating and pinpointing genetic abnormalities. The use of artificial intelligence in cancer drug research has enormous potential, and a growing number of businesses are doing so.

The industry has been divided into five segments based on application: target recognition, candidiate screening, drug optimization and repurposing, de novo drug design, and preclinical testing. In the global AI in drug discovery industry, the applicant screening division is projected to have the largest share.

The industry has been divided into Pharmaceutical and Biotechnology Companies, CROs and Research Centers, and Academic and Government Institutes based on end-users. AI incorporation of drug research would be most beneficial to pharmaceutical and biotechnology industries. With AI, drug developers can greatly increase the productivity of their drug development process while also reducing the time it takes. Over the evaluation era, pharmaceutical and biotechnology firms are expected to have the highest market share in the global market. In the global AI in drug discovery industry, the contract research agency group is projected to be the second-largest market. AI convergence is projected to significantly lower drug research and manufacturing prices, which would favour both service providers and innovators.

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Regional Analysis:

Countries in the Americas, such as the United States and Canada, have long been at the forefront of the healthcare sector. One of the main reasons for the region's rapid growth in the AI in drug development market is the growing number of large AI platform developers. Big Pharma firms are using some of the top AI tools, such as Google AI, Microsoft Azure, and TensorFlow, for use in the drug development process. Furthermore, the industry is being driven by growing demand for Artificial Intelligence technology from Big Pharma companies such as AbbVie, Genentech, Amgen, and Eli Lilly and Company, among others. Furthermore, the demand for new medicines in Latin America is propelling the Americas' rise in the AI in drug development industry.

After the Americas, Europe is the second-largest market for AI in drug discovery. Growing R&D initiatives in the pharmaceutical industry, as well as a strong demand for AI solutions from Big Pharma firms, are projected to propel the regional market forward. To incorporate AI technology into the drug development process, top pharma firms have formed relationships with AI service providers. A the number of startups, such as Pharnext, Alphanosos, and Antiverse, among others, are also contributing to the market's expansion in Europe.

The increasing demand for successful drug development solutions can be attributed to the Asia-Pacific market's rise. A variety of startups are attempting to incorporate AI into the drug development process. With the rapidly emerging pharmaceutical industry in Asia, it is anticipated that AI innovations will be integrated into conventional drug development protocols in the near future. As a result, during the forecast period, the Asia-Pacific region is expected to have the fastest growth rate in the AI in drug discovery industry.

Due to inadequate healthcare facilities, a small number of players involved in drug research and growth, and low per capita disposable incomes in Africa's underdeveloped areas, the Middle East and Africa is the smallest sector.

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