Artificial intelligence (AI) may one day revolutionize the field of medical testing by eliminating the need for animals to be subjected to scientific experiments. Researchers are increasingly turning to AI systems to accelerate their work in finding non-animal alternatives for testing the safety of drugs and other substances.
One key application of AI in this area is the ability to analyze existing global animal testing results to prevent the need for unnecessary new tests. Joseph Manuppello, a senior research analyst at the Physicians Committee of Responsible Medicine, highlights the potential of AI models like ChatGPT to extract and synthesize available data effectively.
Thomas Hartung, a toxicology professor at Johns Hopkins University, emphasizes the role of AI in extracting information from scientific papers, stating that AI is as good as or even better than humans in this task. With over 1,000 new chemical compounds entering the market each year, AI systems are becoming increasingly capable of determining a new chemical’s toxicity, providing valuable insights for researchers.
Despite the progress made by AI in toxicity testing, challenges such as data bias still exist. However, Prof. Hartung notes that AI has already shown to be more accurate than animal testing in certain cases. Projects like AnimalGAN and Virtual Second Species are being developed to replace the need for future animal testing by creating AI-powered models that can predict how animals would react to different chemicals.
While some experts believe that AI could eventually lead to the end of animal testing, others like Kerstin Kleinschmidt-Dorr from Merck pharmaceutical company argue that animal testing is still necessary in many aspects. The debate continues on whether AI-powered alternatives can completely replace animal testing or if a transition away from using animals in experiments is possible in the future.
