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

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

AI in Predictive Toxicology Market Size

AI in Predictive Toxicology Market size was valued at USD 281 million in 2022 and is estimated to register a CAGR of over 29.5% between 2023 and 2032. The increasing investments in pharmaceutical AI startups are driving the market growth. These funds enable the development and implementation of advanced technologies, such as Machine Learning (ML) and predictive modeling, to enhance toxicological assessments of chemical compounds.

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For instance, in December 2022, Quris Technologies Ltd., an Israeli pharmaceutical AI startup, gained an extra USD 9 million in seed funding, bringing the total raised amount to USD 37 million. The funding round was spearheaded by SoftBank Vision Fund 2, with contributions from current investors including GlenRock Capital, iAngels, Welltech Ventures, and Richter Group.
 

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Advancements in AI technologies, particularly in ML and deep learning, play a pivotal role in propelling the AI in predictive toxicology market. These technologies enhance the capability to analyze complex data sets, recognize intricate patterns, and generate more accurate predictions regarding the toxicological properties of chemical compounds. The continuous refinement of AI algorithms and the integration of sophisticated computational techniques contribute to the development of robust & reliable models, making AI a key factor in advancing the field of predictive toxicology.

The quality and availability of data pose a significant barrier to the AI in predictive toxicology market growth. Inadequate or suboptimal datasets can compromise the training and validation of ML models, potentially leading to inaccurate predictions. Issues, such as data incompleteness, biases, or variability, can undermine the reliability of AI applications. Ensuring access to high-quality, diverse, and representative datasets is crucial for developing robust predictive models in toxicology, but acquiring such data can be a complex and resource-intensive task.

COVID-19 Impact

The COVID-19 pandemic positively impacted the AI in predictive toxicology market. The increased focus on drug development and the urgency for efficient solutions prompted a heightened interest in AI applications for predictive toxicology. The pandemic accelerated the adoption of advanced technologies, encouraging pharmaceutical companies to invest in innovative approaches. There has been a surge in the demand for faster & more accurate toxicity assessments, facilitated by the integration of AI. This has contributed to market size, establishing it as a crucial tool in the pharmaceutical research & development landscape.   

AI in Predictive Toxicology Market Trends

The utilization of AI operating systems to accelerate drug development is fostering lucrative growth in the AI in predictive toxicology industry. By swiftly identifying and developing promising drug candidates, these systems streamline the drug development process. For instance, in November 2023, BioPhy unveiled its AI operating system, aiming to significantly expedite the discovery and development of promising drug candidates. Integrating clinical, scientific, and regulatory insights with a unique operational assessment model, BioPhy's AI platform evaluates biological feasibility and forecasts the probability of a positive outcome in clinical trials. Overall, this approach is spurring the adoption of AI in predictive toxicology, fostering a robust & profitable market landscape.

The heightened demand for streamlined drug development processes is propelling the AI in predictive toxicology industry. As pharmaceutical companies seek more efficient approaches, AI plays a pivotal role in expediting toxicological assessments. By leveraging ML and predictive modeling, AI enables rapid identification of potential drug candidates, reducing time and costs. 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

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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.

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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

Frequently Asked Questions (FAQ)

What is the size of the AI in predictive toxicology market?

The market size of AI in predictive toxicology reached USD 281 million in 2022 and is set to expand at over 29.5% CAGR from 2023 to 2032, attributed to the increasing investments in pharmaceutical AI startups.

Why is the demand for AI in predictive toxicology solutions gaining traction?

The solution segment accounted for more than 70% of the market share in 2022, owing to the ongoing development of advanced precision medicine and treatment solutions.

How big is the North America AI in predictive toxicology industry?

North America held more than 44% of the market share in 2022, driven by the robust presence of the pharmaceutical sector in the region.

Who are the major AI in predictive toxicology market participants?

Some of the leading companies engaged in industry are Benevolent AI, Berg Health, Celsius Therapeutics, Chemaxon Ltd., Insilico Medicine, Instem plc, Lhasa Limited, and, Recursion Pharmaceuticals.