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Introduction: Intravenous general anesthetic agents are among the most important and widely used anesthetic drugs in the clinical practice. Many pharmacological studies have shown that potentiation of GABA and glycine on their receptors is the most plausible mechanism. Nevertheless, there is limited information on the effects of co-administration of two or more of these agents. However, experimental models for investigation of optimized drug combinations to have maximum effects on the receptors, have certain limitations and are both time consuming and expensive. One method to optimize drug combinations is the use of artificial neural network, in which the response optimization is performed by using experimental results. Methods: In this research, artificial neural network has been used to model a function with seven input and one output variants. Each input variant represents one of the intravenous general anesthetics including thiopentone, methohexitone, pentobarbitone, propofol, etomidate, saffan and ketamine and the output variant is the effectiveness of these drugs on glycine receptors. Results: Results of the present study show that maximum potentiation of the tested drugs on glycine receptor are around 1500%, which can be achieved under certain drug concentrations, while maximum potentiation that has been obtained in experimental models by combination of propofol or saffan and by combination of thiopentone and pentobarbitone has been around 600% and 640%, respectively. Conclusion: In order to evaluate and validate the calculated results, experiments are recommended to be performed with the proposed combinations and concentrations.

Keywords: Artificial neural network, optimization, intravenous anesthetic drugs

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