AI in Predictive Toxicology Market to Grow at 29.6% CAGR Through 2031, Driven by In Silico Drug Safety, Machine Learning Advances, and Reduced Animal Testing | QY Research

Market Overview -

The global AI in Predictive Toxicology market was valued at US$ 170 million in 2024 and is projected to expand rapidly to US$ 1,083 million by 2031, registering a remarkable CAGR of 29.6% during the forecast period 2025-2031.

According to the latest study released by QY Research, titled "AI in Predictive Toxicology Market Share and Ranking, Overall Sales and Demand Forecast 2025-2031", the market is entering a high-growth phase as artificial intelligence transforms how chemical safety and toxicity risks are evaluated across pharmaceuticals, biotechnology, chemicals, cosmetics, and environmental applications.

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Industry Definition and Technology Background -

Predictive toxicology is an emerging scientific discipline that leverages artificial intelligence (AI), data analytics, and computational modeling to predict the potential adverse effects of chemical compounds on biological systems. By replacing or complementing traditional in vivo animal testing with in silico and in vitro approaches, AI-driven predictive toxicology significantly accelerates risk assessment while improving accuracy and ethical compliance.

Modern predictive toxicology platforms integrate machine learning algorithms, quantitative structure-activity relationship (QSAR) models, and ADME (absorption, distribution, metabolism, and excretion) calculations to assess toxicity profiles early in product development. This convergence of AI and toxicology is reshaping safety evaluation workflows across multiple industries.

Key Market Drivers -

The rapid expansion of the AI in predictive toxicology market is driven by several structural and technological factors:

Rising demand for faster and more accurate toxicity assessment in drug discovery and chemical safety

Shift from animal-based testing to in silico and in vitro methods, aligned with regulatory and ethical guidelines

Advancements in machine learning techniques, including Support Vector Machines (SVMs), Random Forests (RF), and Decision Trees (DTs), which are well suited to toxicology datasets

Growing regulatory pressure to improve safety evaluation efficiency and transparency

Expanding applications beyond pharmaceuticals, including cosmetics, agriculture, chemicals, and environmental toxicity assessment

These drivers are enabling AI-based toxicology tools to move from experimental use to core components of R&D and regulatory workflows.

Role of Natural Language Processing (NLP) -

In addition to machine learning, Natural Language Processing (NLP) is emerging as a critical AI domain within predictive toxicology. NLP technologies extract structured insights from scientific literature, regulatory documents, clinical reports, and adverse event databases.

Recent advancements in biomedical NLP allow automated mining of toxicity relationships from millions of publications, dramatically expanding the knowledge base available for predictive models. This capability enhances model robustness, supports regulatory submissions, and improves decision-making accuracy across the safety assessment lifecycle.

Market Scope and Research Coverage -

This report provides a comprehensive and data-driven analysis of the global AI in Predictive Toxicology market, focusing on:

Total sales revenue (US$ millions)

Company market share and competitive ranking

Regional and country-level market analysis

Segmentation by AI type and application

Market estimates and forecasts use 2024 as the base year, include historical data from 2020-2024, and project trends through 2031. The study combines quantitative modeling with qualitative insights to support strategic planning and investment decisions.

Regional Market Insights -

North America leads the market, supported by strong pharmaceutical R&D activity, advanced AI adoption, and favorable regulatory environments.

Europe follows closely, driven by regulatory initiatives to reduce animal testing and strong presence of computational toxicology platforms.

Asia Pacific is the fastest-growing region, fueled by expanding biotech ecosystems, increasing chemical production, and growing investments in AI-driven drug discovery.

South America and the Middle East & Africa represent emerging opportunities as regulatory frameworks and digital research capabilities continue to develop.

Competitive Landscape -

The AI in predictive toxicology market is moderately fragmented, with a mix of AI-native startups, computational chemistry specialists, and life science technology providers focusing on innovation and platform scalability.

Key companies profiled in the report include:

► BenevolentAI
► Exscientia
► Instem
► Dassault Systèmes
► Evotec
► Simulations Plus
► Schrödinger
► Insilico Medicine
► Chemcopilot
► Inotiv

These companies are actively investing in advanced algorithms, data integration, and partnerships with pharmaceutical and regulatory stakeholders.

Market Segmentation Highlights

By Type:

Machine Learning
Natural Language Processing
Computer Vision

By Application:

Pharmaceutical & Biotechnology
Chemical & Cosmetics
Others

Each segment is analyzed in terms of adoption drivers, revenue contribution, and long-term growth potential.

Reasons to Procure this Report: -

►The research would help top administration/policymakers/professionals/product advancements/sales managers and stakeholders in this market in the following ways.

►The report provides AI In Predictive Toxicology market revenues at the worldwide, regional, and country-level with a complete analysis to 2028 permitting companies to analyze their market share and analyze projections, and find new markets to aim.

►The research includes the AI In Predictive Toxicology market split by different types, applications, technologies, and end-uses. This segmentation helps leaders plan their products and finances based on the upcoming development rates of each segment.

►AI In Predictive Toxicology market analysis benefits investors by knowing the scope and position of the market giving them information on key drivers, challenges, restraints, and expansion chances of the market and moderate threats.

►This report would help to understand competition better with a detailed analysis and key strategies of their competitors and plan their position in the business.

►The study helps evaluate AI In Predictive Toxicology business predictions by region, key countries, and top companies' information to channel their investments.

Key questions answered in the report include:

►This AI In Predictive Toxicology report gives all the information about the industry analysis, revenue, and overview, of this market.

►What will be the rate of increase in AI In Predictive Toxicology market size and growth rate by the end of the forecast period?

►What are the major global AI In Predictive Toxicology market trends influencing the development of the market?

►What are the vital results of SWOT analysis of the major players operating in the AI In Predictive Toxicology market?

►What are the potential growth opportunities and threats faced by Major competitors in the AI In Predictive Toxicology market?

►What are the market opportunities and threats faced by vendors in the Global AI In Predictive Toxicology market?

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Table of Contents - Major Key Points:

1 Market Overview
1.1 AI In Predictive Toxicology Product Introduction
1.2 Global AI In Predictive Toxicology Market Size Forecast (2020-2031)
1.3 AI In Predictive Toxicology Market Trends & Drivers
1.3.1 AI In Predictive Toxicology Industry Trends
1.3.2 AI In Predictive Toxicology Market Drivers & Opportunity
1.3.3 AI In Predictive Toxicology Market Challenges
1.3.4 AI In Predictive Toxicology Market Restraints
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Competitive Analysis by Company
2.1 Global AI In Predictive Toxicology Players Revenue Ranking (2024)
2.2 Global AI In Predictive Toxicology Revenue by Company (2020-2025)
2.3 Key Companies AI In Predictive Toxicology Manufacturing Base Distribution and Headquarters
2.4 Key Companies AI In Predictive Toxicology Product Offered
2.5 Key Companies Time to Begin Mass Production of AI In Predictive Toxicology
2.6 AI In Predictive Toxicology Market Competitive Analysis
2.6.1 AI In Predictive Toxicology Market Concentration Rate (2020-2025)
2.6.2 Global 5 and 10 Largest Companies by AI In Predictive Toxicology Revenue in 2024
2.6.3 Global Top Companies by Company Type (Tier 1, Tier 2, and Tier 3) & (based on the Revenue in AI In Predictive Toxicology as of 2024)
2.7 Mergers & Acquisitions, Expansion
3 Segmentation by Type
3.1 Introduction by Type
3.1.1 Machine Learning
3.1.2 Natural Language Processing
3.1.3 Computer Vision
3.2 Global AI In Predictive Toxicology Sales Value by Type
3.2.1 Global AI In Predictive Toxicology Sales Value by Type (2020 VS 2024 VS 2031)
3.2.2 Global AI In Predictive Toxicology Sales Value, by Type (2020-2031)
3.2.3 Global AI In Predictive Toxicology Sales Value, by Type (%) (2020-2031)
4 Segmentation by Application
4.1 Introduction by Application
4.1.1 Pharmaceutical & Biotechnology
4.1.2 Chemical & Cosmetics
4.1.3 Others
4.2 Global AI In Predictive Toxicology Sales Value by Application
4.2.1 Global AI In Predictive Toxicology Sales Value by Application (2020 VS 2024 VS 2031)
4.2.2 Global AI In Predictive Toxicology Sales Value, by Application (2020-2031)
4.2.3 Global AI In Predictive Toxicology Sales Value, by Application (%) (2020-2031)
5 Segmentation by Region
5.1 Global AI In Predictive Toxicology Sales Value by Region
5.1.1 Global AI In Predictive Toxicology Sales Value by Region: 2020 VS 2024 VS 2031
5.1.2 Global AI In Predictive Toxicology Sales Value by Region (2020-2025)
5.1.3 Global AI In Predictive Toxicology Sales Value by Region (2026-2031)
5.1.4 Global AI In Predictive Toxicology Sales Value by Region (%), (2020-2031)
5.2 North America
5.2.1 North America AI In Predictive Toxicology Sales Value, 2020-2031
5.2.2 North America AI In Predictive Toxicology Sales Value by Country (%), 2024 VS 2031
5.3 Europe
5.3.1 Europe AI In Predictive Toxicology Sales Value, 2020-2031
5.3.2 Europe AI In Predictive Toxicology Sales Value by Country (%), 2024 VS 2031
5.4 Asia Pacific
5.4.1 Asia Pacific AI In Predictive Toxicology Sales Value, 2020-2031
5.4.2 Asia Pacific AI In Predictive Toxicology Sales Value by Region (%), 2024 VS 2031
5.5 South America
5.5.1 South America AI In Predictive Toxicology Sales Value, 2020-2031
5.5.2 South America AI In Predictive Toxicology Sales Value by Country (%), 2024 VS 2031
5.6 Middle East & Africa
5.6.1 Middle East & Africa AI In Predictive Toxicology Sales Value, 2020-2031
5.6.2 Middle East & Africa AI In Predictive Toxicology Sales Value by Country (%), 2024 VS 2031
6 Segmentation by Key Countries/Regions
6.1 Key Countries/Regions AI In Predictive Toxicology Sales Value Growth Trends, 2020 VS 2024 VS 2031
6.2 Key Countries/Regions AI In Predictive Toxicology Sales Value, 2020-2031
6.3 United States
6.3.1 United States AI In Predictive Toxicology Sales Value, 2020-2031
6.3.2 United States AI In Predictive Toxicology Sales Value by Type (%), 2024 VS 2031
6.3.3 United States AI In Predictive Toxicology Sales Value by Application, 2024 VS 2031
6.4 Europe
6.4.1 Europe AI In Predictive Toxicology Sales Value, 2020-2031
6.4.2 Europe AI In Predictive Toxicology Sales Value by Type (%), 2024 VS 2031
6.4.3 Europe AI In Predictive Toxicology Sales Value by Application, 2024 VS 2031
6.5 China
6.5.1 China AI In Predictive Toxicology Sales Value, 2020-2031
6.5.2 China AI In Predictive Toxicology Sales Value by Type (%), 2024 VS 2031
6.5.3 China AI In Predictive Toxicology Sales Value by Application, 2024 VS 2031
6.6 Japan
6.6.1 Japan AI In Predictive Toxicology Sales Value, 2020-2031
6.6.2 Japan AI In Predictive Toxicology Sales Value by Type (%), 2024 VS 2031
6.6.3 Japan AI In Predictive Toxicology Sales Value by Application, 2024 VS 2031
6.7 South Korea
6.7.1 South Korea AI In Predictive Toxicology Sales Value, 2020-2031
6.7.2 South Korea AI In Predictive Toxicology Sales Value by Type (%), 2024 VS 2031
6.7.3 South Korea AI In Predictive Toxicology Sales Value by Application, 2024 VS 2031
6.8 Southeast Asia
6.8.1 Southeast Asia AI In Predictive Toxicology Sales Value, 2020-2031
6.8.2 Southeast Asia AI In Predictive Toxicology Sales Value by Type (%), 2024 VS 2031
6.8.3 Southeast Asia AI In Predictive Toxicology Sales Value by Application, 2024 VS 2031
6.9 India
6.9.1 India AI In Predictive Toxicology Sales Value, 2020-2031
6.9.2 India AI In Predictive Toxicology Sales Value by Type (%), 2024 VS 2031
6.9.3 India AI In Predictive Toxicology Sales Value by Application, 2024 VS 2031
7 Company Profiles
7.1 BenevolentAI
7.1.1 BenevolentAI Profile
7.1.2 BenevolentAI Main Business
7.1.3 BenevolentAI AI In Predictive Toxicology Products, Services and Solutions
7.1.4 BenevolentAI AI In Predictive Toxicology Revenue (US$ Million) & (2020-2025)
7.1.5 BenevolentAI Recent Developments
7.2 Exscientia
7.2.1 Exscientia Profile
7.2.2 Exscientia Main Business
7.2.3 Exscientia AI In Predictive Toxicology Products, Services and Solutions
7.2.4 Exscientia AI In Predictive Toxicology Revenue (US$ Million) & (2020-2025)
7.2.5 Exscientia Recent Developments
7.3 Instem
7.3.1 Instem Profile
7.3.2 Instem Main Business
7.3.3 Instem AI In Predictive Toxicology Products, Services and Solutions
7.3.4 Instem AI In Predictive Toxicology Revenue (US$ Million) & (2020-2025)
7.3.5 Instem Recent Developments
7.4 Dassault Systèmes
7.4.1 Dassault Systèmes Profile
7.4.2 Dassault Systèmes Main Business
7.4.3 Dassault Systèmes AI In Predictive Toxicology Products, Services and Solutions
7.4.4 Dassault Systèmes AI In Predictive Toxicology Revenue (US$ Million) & (2020-2025)
7.4.5 Dassault Systèmes Recent Developments
7.5 Evotec
7.5.1 Evotec Profile
7.5.2 Evotec Main Business
7.5.3 Evotec AI In Predictive Toxicology Products, Services and Solutions
7.5.4 Evotec AI In Predictive Toxicology Revenue (US$ Million) & (2020-2025)
7.5.5 Evotec Recent Developments
7.6 Simulations Plus
7.6.1 Simulations Plus Profile
7.6.2 Simulations Plus Main Business
7.6.3 Simulations Plus AI In Predictive Toxicology Products, Services and Solutions
7.6.4 Simulations Plus AI In Predictive Toxicology Revenue (US$ Million) & (2020-2025)
7.6.5 Simulations Plus Recent Developments
7.7 Schrodinger
7.7.1 Schrodinger Profile
7.7.2 Schrodinger Main Business
7.7.3 Schrodinger AI In Predictive Toxicology Products, Services and Solutions
7.7.4 Schrodinger AI In Predictive Toxicology Revenue (US$ Million) & (2020-2025)
7.7.5 Schrodinger Recent Developments
7.8 Insilico Medicine
7.8.1 Insilico Medicine Profile
7.8.2 Insilico Medicine Main Business
7.8.3 Insilico Medicine AI In Predictive Toxicology Products, Services and Solutions
7.8.4 Insilico Medicine AI In Predictive Toxicology Revenue (US$ Million) & (2020-2025)
7.8.5 Insilico Medicine Recent Developments
7.9 Chemcopilot
7.9.1 Chemcopilot Profile
7.9.2 Chemcopilot Main Business
7.9.3 Chemcopilot AI In Predictive Toxicology Products, Services and Solutions
7.9.4 Chemcopilot AI In Predictive Toxicology Revenue (US$ Million) & (2020-2025)
7.9.5 Chemcopilot Recent Developments
7.10 Inotiv
7.10.1 Inotiv Profile
7.10.2 Inotiv Main Business
7.10.3 Inotiv AI In Predictive Toxicology Products, Services and Solutions
7.10.4 Inotiv AI In Predictive Toxicology Revenue (US$ Million) & (2020-2025)
7.10.5 Inotiv Recent Developments
8 Industry Chain Analysis
8.1 AI In Predictive Toxicology Industrial Chain
8.2 AI In Predictive Toxicology Upstream Analysis
8.2.1 Key Raw Materials
8.2.2 Raw Materials Key Suppliers
8.2.3 Manufacturing Cost Structure
8.3 Midstream Analysis
8.4 Downstream Analysis (Customers Analysis)
8.5 Sales Model and Sales Channels
8.5.1 AI In Predictive Toxicology Sales Model
8.5.2 Sales Channel
8.5.3 AI In Predictive Toxicology Distributors
9 Research Findings and Conclusion
10 Appendix
10.1 Research Methodology
10.1.1 Methodology/Research Approach
10.1.1.1 Research Programs/Design
10.1.1.2 Market Size Estimation
10.1.1.3 Market Breakdown and Data Triangulation
10.1.2 Data Source
10.1.2.1 Secondary Sources
10.1.2.2 Primary Sources
10.2 Author Details
10.3 Disclaimer

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