全球人工智慧驅動的預測毒理學市場：規模、佔有率、趨勢和成長分析報告（2026-2034）

人工智慧在預測毒理學領域的市場預計將從 2025 年的 6.5 億美元成長到 2034 年的 69.1 億美元，2026 年至 2034 年的複合年成長率為 30.04%。

隨著製藥和生物技術公司擴大採用人工智慧來評估化學品的毒性和藥物的安全性，全球人工智慧在預測毒理學領域的市場正經歷著快速成長。人工智慧驅動的預測模型能夠加速識別有害化合物，從而減少對傳統動物試驗和冗長實驗室實驗的依賴。這種轉變有助於企業改善安全性評估，同時加速藥物研發進程。隨著監管機構推薦替代測試方法，製藥、化學和環境研究領域對人工智慧毒理學平台的需求持續成長。

推動市場發展的關鍵因素之一是對高效能藥物研發流程日益成長的需求。人工智慧演算法能夠分析來自基因組、分子和臨床研究的大量資料集，從而更準確地預測毒理學反應。這顯著降低了研發成本，並最大限度地減少了藥物研發後期階段的失敗。此外，監管機構對化學品安全性和環境影響的審查日益嚴格，也促使業界採用預測毒理學工具，以便在研發過程的早期階段評估毒性風險。

隨著機器學習模型日益複雜，資料集日益完善，市場預計將迎來強勁成長。雲端運算和巨量資料分析技術的進步將進一步提升預測能力。製藥公司、研究機構和人工智慧技術提供者之間的合作將推動該領域的創新。隨著產業不斷優先考慮更安全、更快速的產品開發，人工智慧驅動的預測毒理學解決方案將在塑造毒性評估的未來中發揮關鍵作用。

目錄

第1章：引言

第2章執行摘要

第3章 市場變數、趨勢與框架

• 市場譜系展望
• 滲透率和成長前景分析
• 價值鏈分析
• 法律規範
  • 標準與合規性
  • 監管影響分析
• 市場動態
  • 市場促進因素
  • 市場限制因素
  • 市場機遇
  • 市場挑戰
• 波特五力分析
• PESTLE分析

第4章：全球人工智慧驅動的預測毒理學市場：按組件分類

• 市場分析、洞察與預測
• 解決方案
• 服務

第5章：全球人工智慧驅動的預測毒理學市場：按技術分類

• 市場分析、洞察與預測
• 機器學習
• 自然語言處理
• 電腦視覺
• 其他

第6章：全球人工智慧驅動的預測毒理學市場：依毒理學終點分類

• 市場分析、洞察與預測
• 基因毒性
• 肝毒性
• 神經毒性
• 心臟毒性
• 其他

第7章：全球人工智慧驅動的預測毒理學市場：按最終用戶分類

• 市場分析、洞察與預測
• 製藥和生物技術公司
• 化學物質和化妝品
• 受託研究機構
• 其他

第8章：全球人工智慧驅動的預測毒理學市場：按地區分類

• 區域分析
• 北美市場分析、洞察與預測
  • 美國
  • 加拿大
  • 墨西哥
• 歐洲市場分析、洞察與預測
  • 英國
  • 法國
  • 德國
  • 義大利
  • 俄羅斯
  • 其他歐洲國家
• 亞太市場分析、洞察與預測
  • 印度
  • 日本
  • 韓國
  • 澳洲
  • 東南亞
  • 其他亞太國家
• 拉丁美洲市場分析、洞察與預測
  • 巴西
  • 阿根廷
  • 秘魯
  • 智利
  • 其他拉丁美洲國家
• 中東和非洲市場分析、洞察與預測
  • 沙烏地阿拉伯
  • UAE
  • 以色列
  • 南非
  • 其他中東和非洲國家

第9章 競爭情勢

• 最新趨勢
• 公司分類
• 供應鏈和銷售管道合作夥伴（根據現有資訊）
• 市場佔有率和市場定位分析（基於現有資訊）
• 供應商情況（基於現有資訊）
• 策略規劃

第10章：公司簡介

• 主要公司的市佔率分析
• 公司簡介
  • Benevolent AI
  • Berg Health
  • Biovista
  • Celsius Therapeutics
  • Chemaxon Ltd
  • Cyclica
  • Exscientia PLC
  • Insilico Medicine
  • Instem Plc
  • Lhasa Limited
  • Recursion Pharmaceuticals

The AI In Predictive Toxicology Market size is expected to reach USD 6.91 Billion in 2034 from USD 0.65 Billion (2025) growing at a CAGR of 30.04% during 2026-2034.

The Global AI in Predictive Toxicology Market is experiencing rapid growth as pharmaceutical and biotechnology companies increasingly adopt artificial intelligence to evaluate chemical toxicity and drug safety. AI-driven predictive models enable faster identification of harmful compounds, reducing reliance on traditional animal testing and lengthy laboratory experiments. This shift helps companies accelerate drug discovery while improving safety assessments. As regulatory agencies encourage alternative testing methods, the demand for AI-powered toxicology platforms continues to expand across pharmaceutical, chemical, and environmental research sectors.

One of the key drivers of the market is the growing need for efficient drug development processes. AI algorithms can analyze vast datasets from genomic, molecular, and clinical studies to predict toxic responses more accurately. This significantly reduces development costs and minimizes late-stage drug failures. Additionally, increased regulatory scrutiny for chemical safety and environmental impact is encouraging industries to adopt predictive toxicology tools that can assess toxicity risks early in the development process.

Looking ahead, the market is expected to witness strong expansion as machine learning models become more sophisticated and datasets grow more comprehensive. Advancements in cloud computing and big data analytics will further enhance predictive capabilities. Collaboration between pharmaceutical companies, research institutions, and AI technology providers will drive innovation in the field. As industries continue to prioritize safer and faster product development, AI-powered predictive toxicology solutions will play a critical role in shaping the future of toxicological assessment.

Our reports are meticulously crafted to provide clients with comprehensive and actionable insights into various industries and markets. Each report encompasses several critical components to ensure a thorough understanding of the market landscape:

Market Overview: A detailed introduction to the market, including definitions, classifications, and an overview of the industry's current state.

Market Dynamics: In-depth analysis of key drivers, restraints, opportunities, and challenges influencing market growth. This section examines factors such as technological advancements, regulatory changes, and emerging trends.

Segmentation Analysis: Breakdown of the market into distinct segments based on criteria like product type, application, end-user, and geography. This analysis highlights the performance and potential of each segment.

Competitive Landscape: Comprehensive assessment of major market players, including their market share, product portfolio, strategic initiatives, and financial performance. This section provides insights into the competitive dynamics and key strategies adopted by leading companies.

Market Forecast: Projections of market size and growth trends over a specified period, based on historical data and current market conditions. This includes quantitative analyses and graphical representations to illustrate future market trajectories.

Regional Analysis: Evaluation of market performance across different geographical regions, identifying key markets and regional trends. This helps in understanding regional market dynamics and opportunities.

Emerging Trends and Opportunities: Identification of current and emerging market trends, technological innovations, and potential areas for investment. This section offers insights into future market developments and growth prospects.

MARKET SEGMENTATION

By Component

• Solution
• Services

By Technology

• Machine Learning
• Natural Language Processing
• Computer Vision
• Others

By Toxicity Endpoints

• Genotoxicity
• Hepatotoxicity
• Neurotoxicity
• Cardiotoxicity
• Others

By End User

• Pharmaceutical & Biotechnology Companies
• Chemical & Cosmetics
• Contract Research Organizations
• Others

COMPANIES PROFILED

• Benevolent AI, Berg Health, Biovista, Celsius Therapeutics, Chemaxon Ltd, Cyclica, Exscientia PLC, Insilico Medicine, Instem plc, Lhasa Limited, Recursion Pharmaceuticals
• We can customise the report as per your requirements.

TABLE OF CONTENTS

Chapter 1. PREFACE

• 1.1. Market Segmentation & Scope
• 1.2. Market Definition
• 1.3. Information Procurement
  • 1.3.1 Information Analysis
  • 1.3.2 Market Formulation & Data Visualization
  • 1.3.3 Data Validation & Publishing
• 1.4. Research Scope and Assumptions
  • 1.4.1 List of Data Sources

Chapter 2. EXECUTIVE SUMMARY

• 2.1. Market Snapshot
• 2.2. Segmental Outlook
• 2.3. Competitive Outlook

Chapter 3. MARKET VARIABLES, TRENDS, FRAMEWORK

• 3.1. Market Lineage Outlook
• 3.2. Penetration & Growth Prospect Mapping
• 3.3. Value Chain Analysis
• 3.4. Regulatory Framework
  • 3.4.1 Standards & Compliance
  • 3.4.2 Regulatory Impact Analysis
• 3.5. Market Dynamics
  • 3.5.1 Market Drivers
  • 3.5.2 Market Restraints
  • 3.5.3 Market Opportunities
  • 3.5.4 Market Challenges
• 3.6. Porter's Five Forces Analysis
• 3.7. PESTLE Analysis

Chapter 4. GLOBAL AI IN PREDICTIVE TOXICOLOGY MARKET: BY COMPONENT 2022-2034 (USD MN)

• 4.1. Market Analysis, Insights and Forecast Component
• 4.2. Solution Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 4.3. Services Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 5. GLOBAL AI IN PREDICTIVE TOXICOLOGY MARKET: BY TECHNOLOGY 2022-2034 (USD MN)

• 5.1. Market Analysis, Insights and Forecast Technology
• 5.2. Machine Learning Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 5.3. Natural Language Processing Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 5.4. Computer Vision Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 5.5. Others Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 6. GLOBAL AI IN PREDICTIVE TOXICOLOGY MARKET: BY TOXICITY ENDPOINTS 2022-2034 (USD MN)

• 6.1. Market Analysis, Insights and Forecast Toxicity Endpoints
• 6.2. Genotoxicity Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.3. Hepatotoxicity Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.4. Neurotoxicity Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.5. Cardiotoxicity Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.6. Others Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 7. GLOBAL AI IN PREDICTIVE TOXICOLOGY MARKET: BY END USER 2022-2034 (USD MN)

• 7.1. Market Analysis, Insights and Forecast End User
• 7.2. Pharmaceutical & Biotechnology Companies Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 7.3. Chemical & Cosmetics Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 7.4. Contract Research Organizations Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 7.5. Others Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 8. GLOBAL AI IN PREDICTIVE TOXICOLOGY MARKET: BY REGION 2022-2034 (USD MN)

• 8.1. Regional Outlook
• 8.2. North America Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 8.2.1 By Component
  • 8.2.2 By Technology
  • 8.2.3 By Toxicity Endpoints
  • 8.2.4 By End User
  • 8.2.5 United States
  • 8.2.6 Canada
  • 8.2.7 Mexico
• 8.3. Europe Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 8.3.1 By Component
  • 8.3.2 By Technology
  • 8.3.3 By Toxicity Endpoints
  • 8.3.4 By End User
  • 8.3.5 United Kingdom
  • 8.3.6 France
  • 8.3.7 Germany
  • 8.3.8 Italy
  • 8.3.9 Russia
  • 8.3.10 Rest Of Europe
• 8.4. Asia-Pacific Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 8.4.1 By Component
  • 8.4.2 By Technology
  • 8.4.3 By Toxicity Endpoints
  • 8.4.4 By End User
  • 8.4.5 India
  • 8.4.6 Japan
  • 8.4.7 South Korea
  • 8.4.8 Australia
  • 8.4.9 South East Asia
  • 8.4.10 Rest Of Asia Pacific
• 8.5. Latin America Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 8.5.1 By Component
  • 8.5.2 By Technology
  • 8.5.3 By Toxicity Endpoints
  • 8.5.4 By End User
  • 8.5.5 Brazil
  • 8.5.6 Argentina
  • 8.5.7 Peru
  • 8.5.8 Chile
  • 8.5.9 Rest of Latin America
• 8.6. Middle East & Africa Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 8.6.1 By Component
  • 8.6.2 By Technology
  • 8.6.3 By Toxicity Endpoints
  • 8.6.4 By End User
  • 8.6.5 Saudi Arabia
  • 8.6.6 UAE
  • 8.6.7 Israel
  • 8.6.8 South Africa
  • 8.6.9 Rest of the Middle East And Africa

Chapter 9. COMPETITIVE LANDSCAPE

• 9.1. Recent Developments
• 9.2. Company Categorization
• 9.3. Supply Chain & Channel Partners (based on availability)
• 9.4. Market Share & Positioning Analysis (based on availability)
• 9.5. Vendor Landscape (based on availability)
• 9.6. Strategy Mapping

Chapter 10. COMPANY PROFILES OF GLOBAL AI IN PREDICTIVE TOXICOLOGY INDUSTRY

• 10.1. Top Companies Market Share Analysis
• 10.2. Company Profiles
  • 10.2.1 Benevolent AI
  • 10.2.2 Berg Health
  • 10.2.3 Biovista
  • 10.2.4 Celsius Therapeutics
  • 10.2.5 Chemaxon Ltd
  • 10.2.6 Cyclica
  • 10.2.7 Exscientia PLC
  • 10.2.8 Insilico Medicine
  • 10.2.9 Instem Plc
  • 10.2.10 Lhasa Limited
  • 10.2.11 Recursion Pharmaceuticals