Artificial Intelligence (AI) In Predictive Toxicology Market Forecast To 2033 : Trends, Segmentation, Product Type, Technology And Key Players

Overview and Scope
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.

Sizing and Forecast
The artificial intelligence (AI) in predictive toxicology market size has grown exponentially in recent years. It will grow from $0.38 billion in 2023 to $0.50 billion in 2024 at a compound annual growth rate (CAGR) of 30.3%. The growth in the historic period can be attributed to increasing regulatory pressure for toxicity assessment, growing concerns about chemical safety, availability of large datasets for model training, rising costs and ethical concerns associated with animal testing, demand for faster and more cost-effective toxicity screening methods.

The artificial intelligence (AI) in predictive toxicology market size is expected to see exponential growth in the next few years. It will grow to $1.41 billion in 2028 at a compound annual growth rate (CAGR) of 29.9%. The growth in the forecast period can be attributed to emergence of explainable artificial intelligence (AI) in toxicology predictions, demand for personalized toxicity assessments, regulatory acceptance and standardization of AI-based toxicity predictions, rise in predictive toxicology outsourcing services, expansion of AI applications in drug discovery and development. Major trends in the forecast period include shift towards 3D cell culture models for toxicity testing, rise of federated learning approaches for collaborative toxicity prediction, application of generative models for predicting chemical toxicity pathways, incorporation of natural language processing for extracting toxicity data from literature, growth of virtual screening platforms for prioritizing chemical testing.

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The artificial intelligence (AI) in predictive toxicology market covered in this report is segmented –

1) By Component: Solution, Services
2) By Technology: Machine Learning, Natural Language Processing, Computer Vision, 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

North America was the largest region in the artificial intelligence (AI) in predictive toxicology market in 2023. 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, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

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Major Driver Impacting Market Growth
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 June 2023, according to the European Federation of Pharmaceutical Industries and Associations (EFPIA), a Belgium-based trade association representing the pharmaceutical industry, the total pharmaceutical R&D expenditure in Europe accounted for $49,500 million (€44,500 million) in 2022, an increase of approximately 6.45% from $46,500 million (€42,533 million) in 2021. Therefore, the increasing demand for efficient and ethical drug discovery processes is driving the growth of the artificial intelligence (AI) in predictive toxicology market.

Key Industry Players
Major companies operating in the artificial intelligence (AI) in predictive toxicology market are Laboratory Corporation of America Holdings (LabCorp), Eurofins Scientific SE, Wuxi AppTec, Charles River Laboratories International, Medidata Solutions Inc., Certara Inc., Schrödinger, Merative L.P., Molecular Devices LLC, Envigo (Inotiv Inc.), Instem plc, Simulations Plus, Cyprotex, Recursion Pharmaceuticals, Exscientia PLC, BIOVIA Corporation, Lhasa Limited, Chemaxon Ltd., Insilico Medicine Inc., Algorithme Pharma, CiToxLAB, ArisGlobal, Benevolent AI, Berg Health, Cyclica Therapeutics Inc., Celsius Therapeutics, Biovista Inc., BioTeam Inc.

The artificial intelligence (ai) in predictive toxicology market report table of contents includes:

1. Executive Summary

2. Artificial Intelligence (AI) In Predictive Toxicology Market Characteristics

3. Artificial Intelligence (AI) In Predictive Toxicology Market Trends And Strategies

4. Artificial Intelligence (AI) In Predictive Toxicology Market – Macro Economic Scenario

5. Global Artificial Intelligence (AI) In Predictive Toxicology Market Size and Growth
……….

32. Global Artificial Intelligence (AI) In Predictive Toxicology Market Competitive Benchmarking

33. Global Artificial Intelligence (AI) In Predictive Toxicology Market Competitive Dashboard

34. Key Mergers And Acquisitions In The Artificial Intelligence (AI) In Predictive Toxicology Market

35. Artificial Intelligence (AI) In Predictive Toxicology Market Future Outlook and Potential Analysis

36. Appendix

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