AI in Predictive Toxicology Market Size - By Technology (Machine Learning, Natural Language Processing, Computer Vision), Toxicity Endpoints (Genotoxicity, Hepatotoxicity, Neurotoxicity, Cardiotoxicity), Component, End User & Global Forecast, 2023 – 2032
Published Date: March - 2025 | Publisher: MIR | No of Pages: 240 | Industry: Media and IT | Format: Report available in PDF / Excel Format
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AI in Predictive Toxicology Market was USD 281 million in 2022 and is expected to achieve a CAGR of over 29.5% from 2023-2032. The increasing investments in pharma AI startups are driving the market growth. These investments enable the development and implementation of advanced technologies, such as Machine Learning (ML) and predictive modeling, to enhance toxicological assessment of chemical compounds.
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For example, in December 2022, Israeli pharmaceutical AI startup Quris Technologies Ltd. received an additional USD 9 million in seed funding, taking the total amount raised to USD 37 million. The round was led by SoftBank Vision Fund 2, with participation from existing investors such as GlenRock Capital, iAngels, Welltech Ventures, and Richter Group.
| Report Attribute | Details |
|---|---|
| Base Year | 2022 |
| AI in Predictive Toxicology Market Size in 2022 | USD 281 Million |
| Forecast Period | 2023 to 2032 |
| Forecast Period 2023 to 2032 CAGR | 29.5% |
| 2032 Value Projection | USD 3.67 Billion |
| Historical Data for | 2018 – 2022 |
| No. of Pages | 210 |
| Tables, Charts & Figures | 347 |
| Segments covered | Component, Technology, Toxicity Endpoints, and End User |
| Growth Drivers |
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| Pitfalls & Challenges |
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What are the growth opportunities in this market?
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Improvements in AI technologies, specifically in deep learning and ML, are crucial to driving the AI in predictive toxicology market. These technologies improve the ability to process sophisticated data sets, identify complex patterns, and provide more precise predictions on the toxicological characteristics of chemical compounds. The ongoing improvement of AI algorithms and the application of advanced computational methods are sources of developing strong & stable models and hence AI plays a significant role in accelerating predictive toxicology.
Data quality and availability are a major hindrance to the growth of the predictive toxicology market using AI. Poor or non-optimal datasets may invalidate the training and validation of ML models, which may yield erroneous predictions. Problems, for example, data incompleteness, bias, or variability, can jeopardize the accuracy of AI applications. Having access to high-quality, diverse, and representative data sets is vital for building strong prediction models in toxicology, yet it is often a complicated and resource-demanding process.
COVID-19 Impact
The pandemic of COVID-19 positively impacted the market for predictive toxicology AI. The increased focus on drug development and the demand for efficient solutions encouraged a greater interest in the application of AI in predictive toxicology. The pandemic accelerated the incorporation of new technologies, pushing pharma companies to invest in cutting-edge approaches. There has been a boom in the demand for faster & more accurate toxicity assessment, facilitated by the incorporation of AI. This has contributed to market size and has become an essential tool for the pharmaceutical research & development industry.
AI in Predictive Toxicology Market Trends
The use of AI operating systems to speed up drug development is fueling profitable growth for the AI in predictive toxicology market.
Through quick detection and design of suitable drug candidates, these systems automate the drug development process.
For instance, in November 2023, BioPhy launched its AI operating system to accelerate the discovery and development of effective drug candidates by many times. By merging clinical, scientific, and regulatory expertise with a proprietary operational assessment model, BioPhy's AI platform assesses biological feasibility and forecasts the probability of a successful clinical trial. In all, this trend is propelling the application of AI in predictive toxicology, developing a robust & profitable marketplace. The increased need for lean drug development processes is driving the AI in predictive toxicology market. With more effective processes demanded by pharma companies, AI becomes instrumental in streamlining toxicological evaluations. With ML and predictive modeling, AI facilitates quick identification of promising drug candidates, cutting time and expenses. This increased efficiency in drug development aligns with industry needs, boosting the adoption of AI technologies for predictive toxicology and contributing to the market's growth.
AI in Predictive Toxicology Market Analysis
Learn more about the key segments shaping this market
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Based on the component, the solution segment held over 70% of the market share in 2022. Advanced precision medicine solutions are fueling the market. These solutions, with their sophisticated capabilities, play a crucial role in tailoring treatments by interpreting genomic data swiftly and accurately.
For instance, in May 2023, Google Cloud introduced two innovative AI-driven life sciences solutions, aiming to expedite drug discovery and enhance precision medicine across the healthcare sector. The Target & Lead Identification Suite aids researchers in improved identification of amino acid functions and the prediction of protein structures. The Multiomics Suite accelerates the discovery and interpretation of genomic data, assisting companies in the development of precision treatments.
Learn more about the key segments shaping this market
Based on the end user, the pharmaceutical & biotechnology companies segment accounted for 52% of the AI in predictive toxicology market share in 2022, owing to their substantial investments in research & development while prioritizing the need for streamlined drug development. Faced with intense competition, these firms leverage AI technologies to accelerate the drug discovery process, optimizing efficiency and reducing time-to-market. Their financial resources and in-house expertise enable seamless integration of AI, empowering data-driven decision making and compliance with rigorous regulatory standards, ultimately providing a competitive edge in the dynamic landscape of pharmaceutical innovations.
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North America AI in predictive toxicology market recorded around 44% of the revenue share in 2022. The strong presence of the pharmaceutical industry in the region is a key factor propelling the market. The region's pharmaceutical companies are witnessing the need for more efficient drug development processes. Embracing AI technologies in predictive toxicology allows these companies to accelerate drug discovery, optimize research & development efforts, and reduce the overall costs. The competitive landscape and the constant pursuit of innovative solutions in the pharmaceutical sector contribute significantly to the demand for advanced AI applications in predictive toxicology in North America.
AI in Predictive Toxicology Market Share
Major companies operating in the AI in predictive toxicology industry are
- Benevolent AI
- Berg Health
- Biovista
- Celsius Therapeutics
- Chemaxon Ltd.
- Cyclica
- Exscientia PLC
- Insilico Medicine
- Instem plc
- Lhasa Limited
- Recursion Pharmaceuticals
Major companies in the AI in predictive toxicology market are fiercely competing for a share through substantial investments in R&D along with technological advancements. This strategy is aimed at developing cutting-edge solutions, stay ahead in innovations, and capture a significant share of the rapidly evolving predictive toxicology market.
AI in Predictive Toxicology Industry News
- In September 2023, Charles River Laboratories International, Inc. and Related Sciences (RS), a drug discovery firm driven by data science, entered into a collaborative agreement encompassing multiple programs. This collaboration aims to deploy Logica, an AI-powered drug solution, on various targets within the RS portfolio that were previously unexplored. Logica specializes in translating biological insights into optimized assets for more effective drug discovery.
The AI in predictive toxicology market research report includes in-depth coverage of the industry with estimates & forecast in terms of revenue (USD Million) from 2018 to 2032, for the following segments
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Market, By Component
- Solution
- Services
Market, By Technology
- Machine learning
- Natural language processing
- Computer vision
- Others
Market, By Toxicity Endpoints
- Genotoxicity
- Hepatotoxicity
- Neurotoxicity
- Cardiotoxicity
- Others
Market, By End User
- Pharmaceutical & biotechnology companies
- Chemical & cosmetics
- Contract research organizations
- Others
The above information has been provided for the following regions and countries
- North America
- U.S.
- Canada
- Europe
- UK
- Germany
- France
- Italy
- Spain
- Russia
- Nordics
- Asia Pacific
- China
- India
- Japan
- South Korea
- Southeast Asia
- ANZ
- Latin America
- Brazil
- Mexico
- Argentina
- MEA
- UAE
- Saudi Arabia
- South Africa
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