세계의 Drug Discovery 분야 인공지능(AI) 시장, 시장 동향, 성장 촉진요인, 산업 동향 분석 및 예측(2024-2032년)

The Global Artificial Intelligence In Drug Discovery Market was valued at USD 1.9 billion in 2023 and is projected to grow at a CAGR of 29.6% during the forecast period. This growth is driven by increased investments from venture capital firms, pharmaceutical companies, and government agencies, reflecting confidence in AI technologies to expedite drug discovery and address medical needs. Collaboration is rising as companies leverage complementary expertise and resources. The availability of healthcare data, such as genomics and clinical trial data, fuels AI adoption in drug discovery. The prevalence of chronic diseases and the need for innovative therapies push pharmaceutical companies to invest in AI technologies.

The overall artificial intelligence in drug discovery industry is classified based on the component, technology, application type, therapeutic area, end use , and region.

By component, the market is segmented into software and services. The software segment held a 68.3% revenue share in 2023 and is expected to grow at a 29.4% CAGR. The demand for advanced analytics and machine learning tools in the pharmaceutical industry drives this growth. AI software enhances efficiency and automates drug discovery stages, reducing time and resources. Advancements in cloud and high-performance computing also boost AI software adoption.

By technology, the market is classified into machine learning and other technologies. The machine learning segment is expected to reach USD 15.9 billion during the analysis period. Machine learning revolutionizes drug development by analyzing vast datasets to identify drug candidates, predict efficacy and safety, and optimize clinical trials. Growth is supported by advancements in computational power, data availability, and algorithm development. Additionally, machine learning's ability to personalize medicine and tailor treatments to individual patients' genetic profiles further drives its adoption in the pharmaceutical industry.

North America held a 47.4% market share in 2023 and is set for substantial growth. The region's strong pharmaceutical industry, leading AI technology providers, and supportive regulatory environment drive this dominance. Collaborations between academia, industry, and tech providers further bolster North America's position in AI drug discovery. The U.S. market was valued at USD 823.6 million in 2023 and is projected to grow at a 29.1% CAGR. Increased government initiatives promoting precision medicine, research funding, and the adoption of AI tools in R&D by major pharmaceutical companies propel growth. The advanced healthcare infrastructure in the U.S. supports early AI technology adoption, ensuring a significant market presence.

Table of Contents

Chapter 1 Methodology and Scope

• 1.1 Market scope and definitions
• 1.2 Research design
  • 1.2.1 Research approach
  • 1.2.2 Data collection methods
• 1.3 Base estimates and calculations
  • 1.3.1 Base year calculation
  • 1.3.2 Key trends for market estimation
• 1.4 Forecast model
• 1.5 Primary research and validation
  • 1.5.1 Primary sources
  • 1.5.2 Data mining sources

Chapter 2 Executive Summary

• 2.1 Industry 360° synopsis

Chapter 3 Industry Insights

• 3.1 Industry ecosystem analysis
• 3.2 Industry impact forces
  • 3.2.1 Growth drivers
    • 3.2.1.1 Growing number of cross industry collaboration and partnership
    • 3.2.1.2 Artificial intelligence reduces cost and time utilized in the drug discovery and development process
    • 3.2.1.3 Rising prevalence of chronic and infectious diseases
  • 3.2.2 Industry pitfalls and challenges
    • 3.2.2.1 Lack of data sets in the field of drug discovery
    • 3.2.2.2 Limited understanding and expertise
• 3.3 Growth potential analysis
• 3.4 Regulatory landscape
• 3.5 AI in drug discovery - drugs by stage and therapeutic area
• 3.6 Funding received for AI in drug discovery, 2018-2020
• 3.7 Porter's analysis
• 3.8 PESTEL analysis

Chapter 4 Competitive Landscape, 2023

• 4.1 Introduction
• 4.2 Investment and partnership landscape
  • 4.2.1 Investment landscape
  • 4.2.2 Partnership landscape
• 4.3 Company matrix analysis
• 4.4 Competitive analysis of major market players
• 4.5 Competitive positioning matrix
• 4.6 Strategy dashboard

Chapter 5 Market Estimates and Forecast, By Component, 2018 - 2032 ($ Mn)

• 5.1 Key trends
• 5.2 Software
• 5.3 Services

Chapter 6 Market Estimates and Forecast, By Technology, 2018 - 2032 ($ Mn)

• 6.1 Key trends
• 6.2 Machine learning
  • 6.2.1 Deep learning
  • 6.2.2 Supervised learning
  • 6.2.3 Unsupervised learning
  • 6.2.4 Other machine learning technologies
• 6.3 Other technologies

Chapter 7 Market Estimates and Forecast, By Application Type, 2018 - 2032 ($ Mn)

• 7.1 Key trends
• 7.2 Molecular library screening
• 7.3 Target identification
• 7.4 Drug optimization and repurposing
• 7.5 De novo drug designing
• 7.6 Preclinical testing

Chapter 8 Market Estimates and Forecast, By Therapeutic Area, 2018 - 2032 ($ Mn)

• 8.1 Key trends
• 8.2 Oncology
• 8.3 Neurodegenerative diseases
• 8.4 Inflammatory diseases
• 8.5 Infectious diseases
• 8.6 Metabolic diseases
• 8.7 Rare diseases
• 8.8 Cardiovascular diseases
• 8.9 Other therapeutic areas

Chapter 9 Market Estimates and Forecast, By End-Use, 2018 - 2032 ($ Mn)

• 9.1 Key trends
• 9.2 Pharmaceutical and biotechnology companies
• 9.3 Contract research organization (CROs)
• 9.4 Other end-users

Chapter 10 Market Estimates and Forecast, By Region, 2018 - 2032 ($ Mn)

• 10.1 Key trends
• 10.2 North America
  • 10.2.1 U.S.
  • 10.2.2 Canada
• 10.3 Europe
  • 10.3.1 Germany
  • 10.3.2 UK
  • 10.3.3 France
  • 10.3.4 Spain
  • 10.3.5 Italy
  • 10.3.6 Rest of Europe
• 10.4 Asia Pacific
  • 10.4.1 China
  • 10.4.2 Japan
  • 10.4.3 India
  • 10.4.4 Australia
  • 10.4.5 South Korea
  • 10.4.6 Rest of Asia Pacific
• 10.5 Latin America
  • 10.5.1 Brazil
  • 10.5.2 Mexico
  • 10.5.3 Rest of Latin America
• 10.6 Middle East and Africa
  • 10.6.1 South Africa
  • 10.6.2 Saudi Arabia
  • 10.6.3 Rest of Middle East and Africa

Chapter 11 Company Profiles

• 11.1 Alphabet Inc. (DeepMind)
• 11.2 Atomwise Inc.
• 11.3 BenevolentAI
• 11.4 Cyclica
• 11.5 Deep Genomic
• 11.6 Deargen Inc.
• 11.7 Exscientia
• 11.8 International Business Machines Corporation
• 11.9 Microsoft Corporation
• 11.10 NVIDIA Corporation