AI in Predictive Toxicology Market Report 2026

The artificial intelligence (ai) in predictive toxicology market size has grown exponentially in recent years. It will grow from $0.64 billion in 2025 to $0.83 billion in 2026 at a compound annual growth rate (CAGR) of 29.3%. The growth in the historic period can be attributed to growing demand for safer chemicals, increasing pharmaceutical research and development, rising regulatory pressure for chemical safety, early adoption of computational toxicology, advancements in bioinformatics tools.

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.

The rising demand for efficient and ethical drug discovery processes is expected to drive the growth of the artificial intelligence (AI) in predictive toxicology market in the coming years. Drug discovery is a complex and dynamic process involving the systematic exploration, synthesis, and evaluation of chemical compounds to identify potential therapeutic agents that can treat diseases and improve overall health. Efficient and ethical drug discovery processes leverage advanced technologies and prioritize responsible research practices to develop new therapies. This demand is fueled by the increasing prevalence of chronic diseases, the growing trend toward personalized medicine, and a rise in age-related conditions. AI in predictive toxicology enhances drug discovery by analyzing large datasets to predict potential toxicological outcomes, thereby accelerating drug development while maintaining ethical standards. For instance, in 2023, the Office for National Statistics, a UK-based government agency, reported that the UK government’s net spending on research and development (R&D) increased to £17.4 billion ($22.1 billion), up from £16.1 billion ($20.45 billion) in 2022, representing an 8.2% rise. Therefore, the increasing demand for efficient and ethical drug discovery processes is driving growth in the artificial intelligence (AI) in predictive toxicology market.

Major companies in the artificial intelligence (AI) in predictive toxicology market are adopting strategic collaborations to enhance innovation and strengthen market presence. These partnerships aim to leverage AI and machine learning to improve the prediction and assessment of chemical and pharmaceutical toxicity. For instance, in January 2024, SyntheticGestalt, a UK-based AI research and development company offering AI-driven drug discovery solutions, partnered with Enamine, a Ukraine-based provider of chemical building blocks, screening compounds, and integrated drug discovery services, to develop AI models for generating synthetically accessible biologically active compounds while optimizing their physicochemical and ADME or Tox (Absorption, Distribution, Metabolism, Excretion, or Toxicity) properties. These models will support SyntheticGestalt’s compound discovery services for both academic and pharmaceutical clients. Enamine provided access to its extensive Enamine REAL database, containing 38 billion molecules, which SyntheticGestalt will integrate into its Drug Discovery Service to predict physicochemical and ADME or Tox properties and suggest improved alternative compounds when issues arise.

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

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.

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 the artificial intelligence (ai) in predictive toxicology market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the artificial intelligence (ai) in predictive toxicology market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Tariffs have posed challenges for the AI in predictive toxicology market by increasing the cost of importing high-performance computing hardware and specialized laboratory equipment. This has particularly affected software platforms and data analysis tool segments in regions like North America and Europe, which rely on imported components. Contract research organizations and pharmaceutical companies face higher operational costs, slowing deployment of predictive toxicology solutions. However, tariffs have encouraged local manufacturing of AI tools and computational resources, potentially boosting domestic innovation and reducing reliance on foreign suppliers.

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

Artificial intelligence (AI) in predictive toxicology refers to the application of AI techniques to analyze biological, chemical, and environmental data in order to predict the potential toxicity of chemicals and compounds. It is used to accelerate chemical safety assessments, forecast drug toxicity, and prioritize chemicals for further testing.

The main components of AI in predictive toxicology include solutions and services. Solutions are software platforms or systems designed to analyze data and predict toxicological outcomes, utilizing advanced algorithms and models to evaluate the potential risks of chemical compounds. They provide comprehensive tools for toxicity prediction and risk assessment, supporting drug development and chemical safety evaluations. These solutions incorporate technologies such as machine learning, natural language processing, computer vision, and others, and are applied across multiple toxicity endpoints, including genotoxicity, hepatotoxicity, neurotoxicity, cardiotoxicity, and more. End users include pharmaceutical and biotechnology companies, chemical and cosmetics companies, contract research organizations, and others.

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.

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.

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