Artificial Intelligence (AI) In Predictive Toxicology Market Report 2026

Artificial Intelligence (AI) In Predictive Toxicology Market Overview

• Artificial Intelligence (AI) In Predictive Toxicology market size has reached to $0.64 billion in 2025 • Expected to grow to $2.29 billion in 2030 at a compound annual growth rate (CAGR) of 28.9% • Growth Driver: Increasing Demand For Efficient And Ethical Drug Discovery Processes Driving AI In Predictive Toxicology Market Growth • Market Trend: Key Players Driving Innovation Through Strategic Collaborations In The Pharmaceutical Industry • North America was the largest region in 2025 and Asia-Pacific is the fastest growing region.

What Is Covered Under Artificial Intelligence (AI) In Predictive Toxicology Market?

Artificial intelligence (AI) in predictive toxicology refers to the use of artificial intelligence techniques to analyze biological, chemical, and environmental data to predict the potential toxicity of chemicals and compounds. It is used to expedite chemical safety assessments, predict drug toxicity, and prioritize chemicals for further testing. The main components of artificial intelligence (AI) in predictive toxicology include solutions and services. Solutions refer to software platforms or systems designed to analyze data and predict toxicological outcomes and also utilize advanced algorithms and models to assess the potential risks of chemical compounds, offering comprehensive tools for toxicity prediction and risk assessment and aiding in drug development and chemical safety evaluation. It includes several types of technologies, such as machine learning, natural language processing, computer vision, and others, which are used in several toxicity endpoint applications, including genotoxicity, hepatotoxicity, neurotoxicity, cardiotoxicity, and others. These are used by various end users, such as pharmaceutical and biotechnology companies, chemical and cosmetics companies, contract research organizations, and others.

What Is The Artificial Intelligence (AI) In Predictive Toxicology Market Growth Forecast?

The artificial intelligence (ai) in predictive toxicology market size is expected to see exponential growth in the next few years. It will grow to $2.29 billion in 2030 at a compound annual growth rate (CAGR) of 28.9%. The growth in the forecast period can be attributed to increasing adoption of ai-driven predictive models, expansion of cloud-based toxicology platforms, integration of genomics and chemical data, growing collaborations between pharma and biotech companies, rising demand for rapid chemical safety assessment. Major trends in the forecast period include integration of multi-omics data for toxicity prediction, in silico drug toxicity modeling, high-throughput toxicological screening, ai-driven chemical prioritization, cloud-based toxicology data management.

Global Artificial Intelligence (AI) In Predictive Toxicology Market Segmentation

1) By Component: Solution, Services 2) By Technology: Machine Learning, Other Technologies 3) By Toxicity Endpoints: Genotoxicity, Hepatotoxicity, Neurotoxicity, Cardiotoxicity, Other Toxicity Endpoints 4) By End User: Pharmaceutical And Biotechnology Companies, Chemical And Cosmetics, Contract Research Organizations, Other End Users Subsegments: 1) By Solution: Software Platforms, Data Analysis Tools, Predictive Modeling Solutions, Database And Information Systems 2) By Services: Consulting Services, Training And Support Services, Data Management And Integration Services, Research And Development Services

What Is The Driver Of The Artificial Intelligence (AI) In Predictive Toxicology Market?

The increasing demand for efficient and ethical drug discovery processes is expected to propel the growth of artificial intelligence (AI) in predictive toxicology market going forward. Drug discovery is an intricate and dynamic process that involves the systematic exploration, synthesis, and evaluation of chemical compounds to discover potential therapeutic agents to alleviate diseases and enhance overall well-being, while efficient and ethical drug discovery processes involve leveraging advanced technologies and prioritizing responsible research practices to develop new therapeutic agents. The demand for efficient and ethical drug discovery processes is driven by rising chronic diseases, growing trend towards personalized medicine, and an increased prevalence of age-related diseases. Artificial intelligence (AI) in predictive toxicology enhances drug discovery processes by efficiently analyzing vast datasets to predict potential toxicological outcomes, thereby accelerating drug development while ensuring ethical standards are met. For instance, in 2023, according to Office for National Statistics, a UK-based, government agency, the UK government’s net spending on research and development (R&D) increased to £17.4 ($22.1 billion) billion in 2023, up from £16.1 billion ($20.45 billion) in 2022, marking an 8.2% rise. Therefore, the increasing demand for efficient and ethical drug discovery processes is driving the growth of the artificial intelligence (AI) in predictive toxicology industry.

Key Players In The Global Artificial Intelligence (AI) In Predictive Toxicology Market

Major companies operating in the artificial intelligence (ai) in predictive toxicology market are Certara Inc, Schrödinger Inc, Instem plc, Simulations Plus Inc, Lhasa Limited, Chemaxon Ltd, Algorithme Pharma, Benevolent AI, Berg Health, Biovista Inc, Recursion Pharmaceuticals Inc, Exscientia plc, Insilico Medicine Inc, Celsius Therapeutics Inc, ArisGlobal, Merative L.P., BioTeam Inc, Leadscope Inc, MultiCASE Inc, ACD Labs, Optibrium Ltd, Chemotargets SL, Toxys BV

Global Artificial Intelligence (AI) In Predictive Toxicology Market Trends and Insights

Major companies operating in the artificial intelligence (AI) predictive toxicology market are adopting a strategic collaboration approaches to enhance market presence and innovation. These collaborations aim to leverage AI and machine learning techniques to improve the prediction and assessment of the toxicity of chemical compounds and pharmaceuticals. For instance, in January 2024, SyntheticGestalt, a UK-based AI research and development company offering AI drug discovery solutions, partnered with Enamine, a Ukraine-based provider of chemical building blocks, screening compounds, and integrated drug discovery services, to develop a set of AI models facilitating the generation of synthetically accessible biologically active compounds, optimizing their physicochemical and ADME or Tox (Absorption, Distribution, Metabolism, and Excretion or Toxicity) properties. These models will find application in SyntheticGestalt's compound discovery endeavors, catering to both academic users and pharmaceutical companies through their services. Enamine has made its extensive Enamine REAL database, containing 38 billion molecules, available for access. SyntheticGestalt will integrate this database into its Drug Discovery Service, utilizing proprietary AI models to predict the physicochemical and ADME or Tox properties of compounds. The service will promptly suggest improved alternative compounds for those with issues.

What Are Latest Mergers And Acquisitions In The Artificial Intelligence (AI) In Predictive Toxicology Market?

In October 2024, Certara, Inc., a US-based pharmaceutical company that provides drug development software and services, acquired Chemaxon Ltd. for an undisclosed amount. With this acquisition, Certara Inc. aims to enhance its drug development capabilities by integrating advanced cheminformatics software to improve predictive accuracy and streamline the drug discovery process. Chemaxon Ltd. is a Hungary-based IT company that specializes in cheminformatics solutions, which are critical for drug discovery and predictive toxicology.

Regional Insights

North America was the largest region in the artificial intelligence (AI) in predictive toxicology market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in this market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in this market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

What Defines the Artificial Intelligence (AI) In Predictive Toxicology Market?

Artificial intelligence (AI) in predictive toxicology market includes revenues earned by entities by providing services such as toxicity prediction modeling, risk assessment, chemical prioritization, and toxicity data analysis. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included.

How is Market Value Defined and Measured?

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified). The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

What Key Data and Analysis Are Included in the Artificial Intelligence (AI) In Predictive Toxicology Market Report 2026?

The artificial intelligence (ai) in predictive toxicology market research report is one of a series of new reports from The Business Research Company that provides market statistics, including industry global market size, regional shares, competitors with the market share, detailed market segments, market trends and opportunities, and any further data you may need to thrive in the artificial intelligence (ai) in predictive toxicology industry. The market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future state of the industry.