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市场调查报告书
商品编码
1573876

生命科学分析市场中的人工智慧、机会、成长动力、产业趋势分析与预测，2024-2032

AI in Life Science Analytics Market, Opportunity, Growth Drivers, Industry Trend Analysis and Forecast, 2024-2032
出版日期: | 出版商: Global Market Insights Inc. | 英文 100 Pages | 商品交期: 2-3个工作天内

价格
简介目录

2023资料，全球人工智慧在生命科学分析市场的价值为13亿美元，预计2024年至2032年复合年增长率为11.5%。市场正在不断增长。

人工智慧驱动的分析透过促进精确的资料解释、简化药物发现和完善临床试验，彻底改变了生命科学领域。自动化机器学习演算法可以预测患者的治疗结果并识别潜在的候选药物。自然语言处理 (NLP) 工具分析科学文献和电子健康记录中的非结构化资料，发现新的生物标记和治疗标靶。

生命科学领域人工智慧应用的激增是由基因组学、蛋白质组学和其他组学技术的资料量不断增加所推动的，因此需要先进的分析工具来获得可行的见解。製药公司大力投资人工智慧，以加速药物开发并降低临床试验成本。

人工智慧透过预测患者对治疗的反应、改善治疗效果并最大程度地减少不良反应来实现个人化医疗。包括 FDA 在内的监管机构透过发布使用指南、加速技术采用来促进人工智慧在药物开发中的整合。

生命科学分析产业的整体人工智慧根据组件、应用程式、部署、最终用途和区域进行分类。

2023 年，销售和行销支援部门以 5.164 亿美元的收入领先。这一成长归功于人工智慧驱动的解决方案的采用，这些解决方案提高了生命科学领域的销售效率、客户参与度和市场情报。人工智慧使公司能够根据个人偏好、行为和历史资料自订互动和策略。透过分析广泛的资料集（从客户资料、购买模式到市场趋势），人工智慧演算法和进阶分析可以实现精确的受众细分和有针对性的行销活动。

基于云端的细分市场在 2023 年处于领先地位，预计到 2032 年将达到 20 亿美元。云端服务供应商提供以人工智慧为中心的工具和服务，简化生命科学领域机器学习模型的开发、培训和部署。这些平台提供预先建置的人工智慧演算法、模型开发框架和自动化工作流程，简化人工智慧生命週期管理。例如，微软 Azure 为生命科学提供经济实惠的人工智慧解决方案，包括由人工智慧驱动的分析和机器学习工具。 Azure 灵活的定价和全面的云端服务可协助组织透过可扩展的 AI 实施最大限度地提高研究预算并提高营运效率。

2023 年，北美生命科学分析市场中的人工智慧将达到4.9 亿美元，预计2024 年至2032 年复合年增长率为10.8%。方面的人工智慧采用率的提高。公司使用人工智慧来分析大量资料集、获取见解并加快研发速度。例如，辉瑞公司使用人工智慧来预测药物交互作用并完善临床试验设计，从而减少时间和成本。 IBM Watson Health 与辉瑞之间的合作凸显了科技与製药合作关係的趋势，进一步推动了该地区的市场成长。

目录

第 1 章：方法与范围

第 2 章：执行摘要

第 3 章：产业洞察

  • 产业生态系统分析
  • 产业影响力
    • 成长动力
      • 对高效药物发现的需求不断增长
      • 个性化医疗解决方案
      • 人工智慧演算法和运算能力的进步
      • 复杂的医疗资料量不断增加
    • 产业陷阱与挑战
      • 资料隐私和安全问题
      • 初始投资成本高
  • 成长潜力分析
  • 监管环境
  • 创新格局
  • 波特的分析
  • PESTEL分析
  • 未来市场趋势
  • 差距分析
  • 人工智慧对生命科学的影响

第 4 章：竞争格局

  • 介绍
  • 公司矩阵分析
  • 主要参与者竞争分析
  • 竞争定位矩阵
  • 战略仪表板

第 5 章：市场估计与预测：按组成部分，2021 - 2032 年

  • 主要趋势
  • 服务
  • 软体
  • 硬体

第 6 章：市场估计与预测：按应用分类，2021 - 2032

  • 主要趋势
  • 销售和行销支持
  • 供应链分析
  • 研究与开发
  • 其他应用

第 7 章：市场估计与预测：按部署划分，2021 - 2032 年

  • 主要趋势
  • 基于云端
  • 本地

第 8 章：市场估计与预测：按最终用途，2021 - 2032 年

  • 主要趋势
  • 製药和生物技术公司
  • 医疗器材製造商
  • 合约研究组织
  • 其他最终用户

第 9 章：市场估计与预测：按地区，2021 - 2032

  • 主要趋势
  • 北美洲
    • 我们
    • 加拿大
  • 欧洲
    • 德国
    • 英国
    • 法国
    • 西班牙
    • 义大利
    • 荷兰
    • 欧洲其他地区
  • 亚太地区
    • 中国
    • 日本
    • 印度
    • 澳洲
    • 韩国
    • 亚太地区其他地区
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 阿根廷
    • 拉丁美洲其他地区
  • 中东和非洲
    • 南非
    • 沙乌地阿拉伯
    • 阿联酋
    • 中东和非洲其他地区

第 10 章：公司简介

  • AiCure LLC
  • Atomwise
  • Axtria
  • Databricks
  • IBM Corporation
  • Indegene
  • Lexalytics
  • Nuance communications
  • NuMedii
  • Oracle Corporation
  • Saama
  • SAS Institute, Inc.
  • Sisense
  • Sorcero
  • Tempus AI
简介目录
Product Code: 11104

The Global AI in Life Science Analytics Market was valued at USD 1.3 billion in 2023 and is projected to grow at a CAGR of 11.5% from 2024 to 2032. The market, driven by AI technologies, is growing due to the rising demand for advanced data analytics to enhance pharmaceutical and biotechnology R&D processes.

AI-driven analytics revolutionize the life sciences sector by facilitating precise data interpretation, streamlining drug discovery, and refining clinical trials. Automated machine learning algorithms predict patient outcomes and identify potential drug candidates. Natural language processing (NLP) tools analyze unstructured data from scientific literature and electronic health records, discovering novel biomarkers and therapeutic targets.

The surge in AI adoption within life sciences is driven by the escalating data volumes from genomics, proteomics, and other omics technologies, necessitating advanced analytical tools for actionable insights. Pharmaceutical firms invest heavily in AI to hasten drug development and reduce clinical trial costs.

AI personalizes medicine by forecasting patient responses to treatments, enhancing outcomes, and minimizing adverse effects. Regulatory bodies, including the FDA, promote AI's integration in drug development by issuing usage guidelines, accelerating technology adoption.

The overall AI in life science analytics industry is classified based on component, application, deployment, end-use, and region.

In 2023, the sales and marketing support segment led with a revenue of USD 516.4 million. This growth is due to the adoption of AI-driven solutions that enhance sales effectiveness, customer engagement, and market intelligence in life sciences. AI enables companies to customize interactions and strategies based on individual preferences, behaviors, and historical data. By analyzing extensive datasets-ranging from customer profiles and purchasing patterns to market trends-AI algorithms and advanced analytics enable precise audience segmentation and targeted marketing campaigns.

The cloud-based segment led in 2023 and is projected to reach USD 2 billion by 2032. This growth is driven by the cloud's scalability, flexibility, and cost benefits. Cloud service providers offer AI-centric tools and services, streamlining the development, training, and deployment of machine learning models in life sciences. These platforms provide pre-built AI algorithms, model development frameworks, and automated workflows, streamlining AI lifecycle management. For instance, Microsoft Azure offers budget-friendly AI solutions for life sciences, including AI-driven analytics and machine learning tools. Azure's adaptable pricing and comprehensive cloud services help organizations maximize research budgets and enhance operational efficiency through scalable AI implementations.

North America AI in life science analytics market accounted for USD 490.0 million in 2023, with a projected CAGR of 10.8% from 2024 to 2032. This growth is due to the region's heightened AI adoption for drug discovery, clinical trials, and personalized medicine. Companies use AI to analyze vast datasets, derive insights, and expedite R&D. Pfizer, for example, uses AI to predict drug interactions and refine clinical trial designs, reducing time and costs. Collaborations like the one between IBM Watson Health and Pfizer highlight the trend of tech-pharma partnerships, further driving the region's market growth.

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 Rising demand for efficient drug discovery
      • 3.2.1.2 Personalized medicine solutions
      • 3.2.1.3 Advancements in AI algorithms and computational capabilities
      • 3.2.1.4 Increasing volume of complex healthcare data
    • 3.2.2 Industry pitfalls and challenges
      • 3.2.2.1 Data privacy and security concerns
      • 3.2.2.2 High initial investment costs
  • 3.3 Growth potential analysis
  • 3.4 Regulatory landscape
  • 3.5 Innovation landscape
  • 3.6 Porter's analysis
  • 3.7 PESTEL analysis
  • 3.8 Future market trends
  • 3.9 Gap analysis
  • 3.10 The impact of artificial intelligence in life sciences

Chapter 4 Competitive Landscape, 2023

  • 4.1 Introduction
  • 4.2 Company matrix analysis
  • 4.3 Competitive analysis of major key players
  • 4.4 Competitive positioning matrix
  • 4.5 Strategy dashboard

Chapter 5 Market Estimates and Forecast, By Component, 2021 - 2032 ($ Mn)

  • 5.1 Key trends
  • 5.2 Services
  • 5.3 Software
  • 5.4 Hardware

Chapter 6 Market Estimates and Forecast, By Application, 2021 - 2032 ($ Mn)

  • 6.1 Key trends
  • 6.2 Sales and marketing support
  • 6.3 Supply chain analytics
  • 6.4 Research and development
  • 6.5 Other applications

Chapter 7 Market Estimates and Forecast, By Deployment, 2021 - 2032 ($ Mn)

  • 7.1 Key trends
  • 7.2 Cloud-based
  • 7.3 On-premises

Chapter 8 Market Estimates and Forecast, By End-use, 2021 - 2032 ($ Mn)

  • 8.1 Key trends
  • 8.2 Pharmaceutical and biotech companies
  • 8.3 Medical device manufacturers
  • 8.4 Contract research organizations
  • 8.5 Other end-users

Chapter 9 Market Estimates and Forecast, By Region, 2021 - 2032 ($ Mn)

  • 9.1 Key trends
  • 9.2 North America
    • 9.2.1 U.S.
    • 9.2.2 Canada
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 France
    • 9.3.4 Spain
    • 9.3.5 Italy
    • 9.3.6 Netherlands
    • 9.3.7 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 China
    • 9.4.2 Japan
    • 9.4.3 India
    • 9.4.4 Australia
    • 9.4.5 South Korea
    • 9.4.6 Rest of Asia Pacific
  • 9.5 Latin America
    • 9.5.1 Brazil
    • 9.5.2 Mexico
    • 9.5.3 Argentina
    • 9.5.4 Rest of Latin America
  • 9.6 Middle East and Africa
    • 9.6.1 South Africa
    • 9.6.2 Saudi Arabia
    • 9.6.3 UAE
    • 9.6.4 Rest of Middle East and Africa

Chapter 10 Company Profiles

  • 10.1 AiCure LLC
  • 10.2 Atomwise
  • 10.3 Axtria
  • 10.4 Databricks
  • 10.5 IBM Corporation
  • 10.6 Indegene
  • 10.7 Lexalytics
  • 10.8 Nuance communications
  • 10.9 NuMedii
  • 10.10 Oracle Corporation
  • 10.11 Saama
  • 10.12 SAS Institute, Inc.
  • 10.13 Sisense
  • 10.14 Sorcero
  • 10.15 Tempus AI