The AI In Predictive Toxicology Market is being driven by Economic and operational imperative to mitigate late stage attrition and expedite drug development cycles
The AI In Predictive Toxicology Market is expected to grow at a CAGR of 37.4% during 2024 and 2029. During this period, the market is also expected to show a growth of USD 647.7 million. The global AI in predictive toxicology market is experiencing a significant shift as generative artificial intelligence (AI) and advanced machine learning architectures, including large language models and graph neural networks, are increasingly integrated. This evolution goes beyond traditional quantitative structure-activity relationship (QSAR) models, moving towards more dynamic, multifaceted predictive systems. Generative AI, specifically generative adversarial networks (GANs) and transformers, enable the creation of new chemical compounds with predefined low-toxicity profiles. This capability fundamentally transforms the drug discovery and chemical development pipeline from a reactive screening process to a proactive design process. Instead of testing thousands of existing compounds for toxicity, organizations can now generate a smaller, more promising set of candidates that have undergone computational pre-validation for safety.
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The market is segmented based on
According to Technavio, There are several factors that are causing the market to flourish during the forecast period, which are as follows:
However, the market also witnesses some limitations, which are as follows:
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Market Scope |
|
Report Coverage |
Details |
Page number |
234 |
Base year |
2024 |
Historic period |
2019-2023 |
Forecast period |
2025-2029 |
Growth momentum & CAGR |
Accelerate at a CAGR of 37.4% |
Market growth 2025-2029 |
USD 647.7 million |
Market structure |
fragmentation |
YoY growth 2024-2025(%) |
34.8 |
Key countries |
US, UK, Germany, China, Canada, Japan, India, France, Australia, and Brazil |
Competitive landscape |
Leading Companies, Market Positioning of Companies, Competitive Strategies, and Industry Risks |
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In the realm of predictive toxicology, advanced AI technologies are revolutionizing the field with solutions like toxicity pathway prediction, AI-powered risk assessment, and chemical safety prediction. Virtual toxicology testing, a part of next-generation toxicology, employs in silico ADME-tox, pharmacokinetic modeling, toxicological data mining, and biological target identification for compound prioritization. AI applications also extend to drug metabolism prediction, pharmacodynamics modeling, target engagement prediction, toxicological database integration, mechanism of action, toxicity profiling, and admet prediction. Furthermore, AI assists in drug-drug interaction prediction, chemical design optimization, data integration techniques, model validation techniques, and statistical modeling techniques for regulatory submission support and safety data analysis.
The predictive toxicology market encompasses innovative IT solutions leveraging in silico toxicology, QSAR modeling, machine learning, and deep learning models. These advanced technologies enable the prediction of potential toxicological risks, streamlining regulatory compliance, and reducing animal testing. Technavio's market analysis covers businesses specializing in these solutions, contributing to the global application software market. This segment focuses on developing software for niche applications, including predictive toxicology, and excludes companies producing database management software or interactive home entertainment software. The market size is determined by the consolidated revenue generated by these companies.. Industries are leveraging the products belonging to the market for customer engagement, transactional notifications, and promotional offers.
Technavio Research
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