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Global Artificial Intelligence (AI) in Drug Discovery Market – Industry Trends and Forecast to 2030

  • Healthcare
  • Upcoming Report
  • Oct 2023
  • Global
  • 350 Pages
  • No of Tables: 220
  • No of Figures: 60

Global Artificial Intelligence (AI) in Drug Discovery Market, By Application (Novel Drug Candidates, Drug Optimization and Repurposing Preclinical Testing and Approval, Drug Monitoring, Finding New Diseases Associated Targets and Pathways, Understanding Disease Mechanisms, Aggregating and Synthesizing Information, Formation & Qualification of Hypotheses, De Novo Drug Design, Finding Drug Targets of an Old Drug, and Others), Technology (Machine Learning, Deep Learning, Natural Language Processing, and Others), Drug Type (Small Molecule and Large Molecule), Offering (Software and Services), Indication (Immuno-Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases, and Others), End Use (Contract Research Organizations (CROs), Pharmaceutical & Biotechnology Companies, Research Centers and Academic Institutes, and Others) - Industry Trends and Forecast to 2030.

 Artificial Intelligence (AI) in Drug Discovery Market

Artificial Intelligence (AI) in Drug Discovery Market Analysis and Size

Artificial Intelligence (AI) is expected to be a lucrative technology in the healthcare industry. The implementation of AI reduces the R&D gap in the drug manufacturing process and helps in the targeted manufacturing of drug. Hence, biopharmaceutical companies are turning to AI to enhance their market share. AI for drug discovery is a technology that uses machines to simulate human intelligence to solve complicated challenges in the drug development procedure. The adoption of AI solutions in the clinical trial process eliminates possible obstacles, reduces clinical trial cycle time and increases the productivity and accuracy of the clinical trial process. However, low-quality and inconsistent available data will obstruct market growth. Also, the high cost associated with technology and technical limitations will restrain the market growth.

Data Bridge Market Research analyses that the global Artificial Intelligence (AI) in drug discovery market which was USD 885.32 million in 2022, would rocket up to USD 13,998.71 billion by 2030, and is expected to undergo a CAGR of 5.3% during the forecast period 2023 to 2030. In addition to the market insights such as market value, growth rate, market segments, geographical coverage, market players, and market scenario, the market report curated by the Data Bridge Market Research team also includes in-depth expert analysis, patient epidemiology, pipeline analysis, pricing analysis, and regulatory framework.

Artificial Intelligence (AI) in Drug Discovery Market Scope and Segmentation

Report Metric

Details

Forecast Period

2023 to 2030

Base Year

2022

Historic Years

2021 (Customizable to 2015-2021)

Quantitative Units

Revenue in USD Billion, Volumes in Units, Pricing in USD

Segments Covered

Application (Novel Drug Candidates, Drug Optimization and Repurposing Preclinical Testing and Approval, Drug Monitoring, Finding New Diseases Associated Targets and Pathways, Understanding Disease Mechanisms, Aggregating and Synthesizing Information, Formation & Qualification of Hypotheses, De Novo Drug Design, Finding Drug Targets of an Old Drug, and Others), Technology (Machine Learning, Deep Learning, Natural Language Processing, and Others), Drug Type (Small Molecule and Large Molecule), Offering (Software and Services), Indication (Immuno-Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases, and Others), End Use (Contract Research Organizations (CROs), Pharmaceutical & Biotechnology Companies, Research Centers and Academic Institutes, and Others)

Countries Covered

U.S., Canada, Mexico, Germany, France, U.K., Italy, Spain, Russia, Turkey, Belgium, Netherlands, Switzerland, rest of Europe, China, Japan, India, South Korea, Singapore, Thailand, Malaysia, Australia & New Zealand, Philippines, Indonesia, rest of Asia-Pacific, U.A.E, Israel, South Africa, Saudi Arabia, Egypt, rest of Middle East and Africa, Brazil, Argentina and rest of South America

Market Players Covered

NVIDIA Corporation (U.S.), IBM Corp. (U.S.), Atomwise Inc. (U.S.), Microsoft (U.S.), Benevolent AI (U.K.), Aria Pharmaceuticals, Inc. (U.S.), DEEP GENOMICS (Canada), Exscientia (U.K.), Cloud (U.S.), Insilico Medicine (U.S.), Cyclica (Canada), NuMedii, Inc. (U.S.), Envisagenics (U.S.), Owkin Inc. (U.S.), BERG LLC (U.S.), Schrödinger, Inc. (U.S.), XtalPi Inc. (China) and BIOAGE Inc. (Canada)

Market Opportunities

  • Increasing strategic initiatives
  • Increasing investments in research and development activities

Market Definition

AI has caught the attention and minds of medical technology practitioners in the past few years, as several companies and major research laboratories have worked to perfect these technologies for clinical use. The first commercialized demonstrations of how AI (also known as Deep Learning (DL), Machine Learning (ML), or Artificial Neural Networks (ANNs)) could assist clinicians are now available. These systems could lead to a paradigm shift in clinician workflow and increase productivity while simultaneously enhancing treatment and patient throughput. AI for drug discovery is a technology that uses machines to simulate human intelligence to solve complicated challenges in the drug development procedure. The adoption of AI solutions in the clinical trial process eliminates possible obstacles, reduces clinical trial cycle time and increases the productivity and accuracy of the clinical trial process. Therefore, the adoption of these advanced AI solutions in drug discovery processes is gaining popularity amongst life science industry stakeholders. In the pharmaceutical sector, it aids in the discovery of novel compounds, therapeutic target identification and the development of customized medications. AI platforms used for drug discovery can prove to be a feasible option for deriving insights into the discovery of drugs to treat and minimize the severity of various chronic diseases.

Global Artificial Intelligence (AI) in Drug Discovery Market Dynamics

Drivers

  • Rising Prevalence of Chronic Diseases

Chronic diseases, such as heart disease, diabetes, cancer, and neurological disorders, have been on the rise globally. These diseases often require long-term treatment and management, leading to a significant healthcare burden. Drug discovery plays a crucial role in finding effective treatments and therapies for chronic diseases. Artificial intelligence, including machine learning and deep learning, has made significant inroads in drug discovery. AI can analyze vast amounts of biological data, including genomics, proteomics, and clinical data, to identify potential drug candidates, predict their efficacy, and optimize drug development processes.

  • Rising Technological Advancements

The field of Artificial Intelligence (AI) in Drug Discovery is rapidly evolving, with continuous technological advancements that are revolutionizing how drugs are discovered and developed. Generative models, such as generative adversarial networks (GANs) and variational autoencoders (VAEs), are being used to generate novel molecular structures, which can be potential drug candidates. Machine learning algorithms, including deep learning, have become the backbone of AI applications in drug discovery. These algorithms can analyze large datasets and predict potential drug candidates, target identification, and patient responses.

Opportunities

  • Increasing Investments in Research and Development Activities

The rise in R&D activities and increasing adoption of cloud-based services and applications will provide beneficial opportunities for market growth. The industry of AI in biopharma continues to grow after a long period of sepsis. This is reflected in the ongoing flow of investments and the increase in the number of collaborations between pharmaceutical corporations and AI companies in 2021 compared to the previous years. The Biopharma industry’s growth is largely influenced by the active engagement of leading pharmaceutical corporations in AI-related investments. The number of scientific publications in the field of AI in Biopharma and research collaborations between pharma companies and AI-expertise vendors are rapidly increasing, yet some pharma corporations are still critical of AI applications. ML and AI applications in the pharmaceutical and healthcare industries led to the formation of a new interdisciplinary field of data-driven drug discovery in healthcare. Thus, a rise in investment in R&D activities is acting as an opportunity for market growth.

  • Increasing Strategic Initiatives

Strategic collaborations and partnerships are becoming increasingly important in global Artificial Intelligence (AI) in drug discovery market. These collaborations bring together diverse expertise and resources to address the complex challenges associated with drug discovery and development. Partnerships often involve the sharing of AI technologies, algorithms, and expertise. Pharmaceutical companies may collaborate with AI startups or established AI companies to leverage their advanced machine learning and data analysis capabilities.

Restrains

  • Strict Regulations and Guidelines

Regulatory guidelines and frameworks are crucial in the field of Artificial Intelligence (AI) in Drug Discovery to ensure patient safety, data integrity, and the efficacy of AI-driven solutions. The handling of patient data and sensitive medical information is subject to strict regulations, such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States and the General Data Protection Regulation (GDPR) in the European Union. Companies involved in AI drug discovery must ensure compliance with these regulations when collecting, storing, and processing healthcare data.

  • High Cost Associated with Technology

The current healthcare sector is facing several complex challenges, such as the increased cost of drugs and therapies, and society needs specific significant changes in this area. The entire success of AI depends on the availability of a substantial amount of data because these data are used for the subsequent training provided to the system. Access to data from various database providers can incur extra costs for a company. Clinical trials are directed towards establishing the safety and efficacy of a drug product in humans for a particular disease condition and require six to seven years, along with a substantial financial investment. However, only one out of ten molecules entering these trials gain successful clearance, which is a massive loss for the industry. These failures can result from inappropriate patient selection, shortage of technical requirements and poor infrastructure. Thus, increasing costs with the technology are acting as a restraint for the market growth.

Challenges

  • Shortage of Skilled Professional

The shortage of skilled professionals is expected to hamper the market growth. The employees have to re-train or learn new skill sets to work efficiently on complex AI machines to get the desired results for the drug. This challenge that prevents full-fledged adoption of AI in the pharmaceutical industry includes the lack of skilled personnel to operate AI-based platforms, limited budget for small organizations, apprehension of replacing humans leading to job loss, skepticism about the data generated by AI and the black box phenomenon (that is, how the AI platform reaches the conclusions). The shortage of skills acts as a major hindrance to drug discovery through AI, discouraging companies from adopting AI-based machines for drug discovery.

This Artificial Intelligence (AI) in drug discovery market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on the global Artificial Intelligence (AI) in drug discovery market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.

Recent Development

  • In March 2022, NVIDIA Corporation launched Clara Holoscan MGX to develop and deploy real-time AI applications. Clara Holoscan MGX expands the Clara Holoscan platform to provide an all-in-one, medical-grade reference architecture, as well as long-term software support, to accelerate innovation in the medical device industry. This will help the company for better AI performance in the health sector for surgery, diagnostics and drug discovery.

Global Artificial Intelligence (AI) in Drug Discovery Market Scope

Global Artificial Intelligence (AI) in drug discovery market is segmented into application, technology, drug type, offering, indication and end use. The growth among segments helps you analyze niche pockets of growth and strategies to approach the market and determine your core application areas and the differences in your target markets.

Application

  • Novel Drug Candidates
  • Drug Optimization and Repurposing Preclinical Testing and Approval
  •  Drug Monitoring
  •  Finding New Diseases Associated Targets and Pathways
  •  Understanding Disease Mechanisms
  •  Aggregating and Synthesizing Information
  •  Formation & Qualification of Hypotheses
  •  De Novo Drug Design
  •  Finding Drug Targets of an Old Drug
  • Others

Technology

Drug Type

  • Small Molecule
  • Large Molecule

Offering

  • Software
  • Services

Indication

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

END USE

  • Pharmaceutical & Biotechnology Companies
  • Contract Research Organizations (CROs)
  • Research Centres And Academic Institutes
  • Others

Global Artificial Intelligence (AI) in Drug Discovery Market Regional Analysis/Insights

The global Artificial Intelligence (AI) in drug discovery market is analyzed, and market size information is provided by the application, technology, drug type, offering, indication and end use.

The countries covered in this market report are U.S., Canada, Mexico, Germany, France, U.K., Italy, Spain, Russia, Turkey, Belgium, Netherlands, Switzerland, rest of Europe, China, Japan, India, South Korea, Singapore, Thailand, Malaysia, Australia & New Zealand, Philippines, Indonesia, rest of Asia-Pacific, U.A.E, Israel, South Africa, Saudi Arabia, Egypt, rest of Middle East and Africa, Brazil, Argentina and rest of South America.

North America is expected to dominate the market due to the increasing investment in R&D and adoption of AI technology in medicine discovery and development in the North America region over the past few years is expected to boost the market growth. The North America is expected to dominate the market due to the strong presence of AI technology providers such as IBM, Google, Microsoft and others. Asia-Pacific is expected to be the fastest-growing region during the forecast period of 2023-2030 due to increasing investment in innovative R&D in this region. Also, the development of healthcare infrastructure will further propel the market's growth rate in this region.

The country section of the report also provides individual market impacting factors and changes in regulation in the market domestically that impact the current and future trends of the market. Data points such as new sales, replacement sales, country demographics, regulatory acts and import-export tariffs are some of the major pointers used to forecast the market scenario for individual countries. Also, the presence and availability of global brands and their challenges faced due to large or scarce competition from local and domestic brands and the impact of sales channels are considered while providing forecast analysis of the country data.   

Healthcare Infrastructure Growth Installed Base and New Technology Penetration

The global Artificial Intelligence (AI) in drug discovery market also provides you with detailed market analysis for every country growth in healthcare expenditure for capital equipment, installed base of different kind of products for global Artificial Intelligence (AI) in drug discovery market, impact of technology using life line curves and changes in healthcare regulatory scenarios and their impact on the global Artificial Intelligence (AI) in drug discovery market. The data is available for historic period 2010-2021.

Competitive Landscape and Global Artificial Intelligence (AI) in Drug Discovery Market Share Analysis

Global Artificial Intelligence (AI) in drug discovery market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in R&D, new market initiatives, production sites and facilities, company strengths and weaknesses, product launch, product trials pipelines, product approvals, patents, product width and breath, application dominance, technology lifeline curve. The above data points provided are only related to the company’s focus on the global Artificial Intelligence (AI) in drug discovery market.   

Some of the major players operating in the global Artificial Intelligence (AI) in drug discovery market are:

  • NVIDIA Corporation (U.S.)
  • IBM Corp. (U.S.)
  • Atomwise Inc. (U.S.)
  • Microsoft (U.S.)
  • Benevolent AI (U.K.)
  • Aria Pharmaceuticals, Inc. (U.S.)
  • DEEP GENOMICS (Canada)
  • Exscientia (U.K.)
  • Cloud (U.S.)
  • Insilico Medicine (U.S.)
  • Cyclica (Canada)
  • NuMedii, Inc. (U.S.)
  • Envisagenics (U.S.)
  • Owkin Inc. (U.S.)
  • BERG LLC (U.S.)
  • Schrödinger, Inc. (U.S.)
  • XtalPi Inc. (China)
  • BIOAGE Inc. (Canada) 


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Research Methodology:

Data collection and base year analysis are done using data collection modules with large sample sizes. The stage includes obtaining market information or related data through various sources and strategies. It includes examining and planning all the data acquired from the past in advance. It likewise envelops the examination of information inconsistencies seen across different information sources. The market data is analysed and estimated using market statistical and coherent models. Also, market share analysis and key trend analysis are the major success factors in the market report. To know more, please request an analyst call or drop down your inquiry.

The key research methodology used by DBMR research team is data triangulation which involves data mining, analysis of the impact of data variables on the market and primary (industry expert) validation. Data models include Vendor Positioning Grid, Market Time Line Analysis, Market Overview and Guide, Company Positioning Grid, Patent Analysis, Pricing Analysis, Company Market Share Analysis, Standards of Measurement, Global versus Regional and Vendor Share Analysis. To know more about the research methodology, drop in an inquiry to speak to our industry experts.

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Customization Available:

Data Bridge Market Research is a leader in advanced formative research. We take pride in servicing our existing and new customers with data and analysis that match and suits their goal. The report can be customized to include price trend analysis of target brands understanding the market for additional countries (ask for the list of countries), clinical trial results data, literature review, refurbished market and product base analysis. Market analysis of target competitors can be analyzed from technology-based analysis to market portfolio strategies. We can add as many competitors that you require data about in the format and data style you are looking for. Our team of analysts can also provide you data in crude raw excel files pivot tables (Fact book) or can assist you in creating presentations from the data sets available in the report.

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FREQUENTLY ASK QUESTIONS

The Artificial Intelligence (AI) in drug discovery market will be worth USD 13,998.71 billion by 2030.
The Artificial Intelligence (AI) in drug discovery market growth rate is 5.3% during the forecast period.
The field of Artificial Intelligence (AI) in Drug Discovery is rapidly evolving, with continuous technological advancements & Chronic diseases, such as heart disease, diabetes, cancer, and neurological disorders, have been on the rise globally are the growth drivers of the Artificial Intelligence (AI) in drug discovery market.
The application, technology, drug type, offering, indication and end use are the factors on which the Artificial Intelligence (AI) in drug discovery market research is based.
The major companies in the Artificial Intelligence (AI) in Drug Discovery Market are NVIDIA Corporation (U.S.), IBM Corp. (U.S.), Atomwise Inc. (U.S.), Microsoft (U.S.), Benevolent AI (U.K.), Aria Pharmaceuticals, Inc. (U.S.), DEEP GENOMICS (Canada), Exscientia (U.K.), Cloud (U.S.), Insilico Medicine (U.S.), Cyclica (Canada), NuMedii, Inc. (U.S.), Envisagenics (U.S.), Owkin Inc. (U.S.), BERG LLC (U.S.), Schrödinger, Inc. (U.S.), XtalPi Inc. (China) and BIOAGE Inc. (Canada).
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