Document Type : Letter to Editor
Author
1 Department of Physiology, Biochemistry and Pharmacology, College of Veterinary Medicine, University of Mosul, Mosul, Iraq
2 College of Nursing, The American University of Kurdistan, Duhok, Kurdistan Region, Iraq
Abstract
Traditional toxicity studies rely on laboratory animal experimentations to estimate the median lethal dose (LD50) of chemicals such as pesticides and medications. This scientific letter highlights the importance of using artificial intelligence (AI) tools (ChatGPT, Deep Seek and Perplexity) to calculate the LD50 values of diazinon in chicks and cadmium chloride in mice. The data of diazinon and cadmium LD50 experiments in animals were separately presented to each of the three AI tools to estimate LD50 values of both toxicants, which were then compared to those of already published results. By following optimal instructions and providing experimental data, the three AI tools (ChatGPT, Deep Seek and Perplexity) accurately determined the LD50 values of diazinon (6.32 mg/kg, orally) in chicks and cadmium chloride (8.6 mg/kg, intraperitoneally) in mice using the up-and-down method. However, when the AI tools were provided with limited information but the same data, inaccuracies arose in calculating the LD50 values for both diazinon and cadmium. A word of caution is, therefore in place herewith, when AI tools are used for estimation of toxicity output (LD50) that might simulate an in silico approach, even in case of availability of some experimental data, as presented currently in the form of doses used and animal survival and death.
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