Optimal Weibull Distribution I for Dose-Response Modelling of Theophylline Drug

Dose-response model for complex systems is crucial for the treatment of diseases and drug discovery. Understanding the mechanism of drug action has become increasingly important due to the growth of large-scale biological data obtained through computational modelling. This study compared four Dose-response models namely, four parameters log-logistic model, Brain-Cousens hormesis model, Cedergreen-Ritz-Streibig modified log-logistic model, and Weibull distribution I to predict the best model for theophylline dosage and its corresponding physiological properties through sensitivity analysis and Bayesian Information Criteria (BIC). The findings revealed that Weibull distribution 1 outperformed other models with the least BIC value of 294.4214. Therefore, Weibull distribution 1 is the best model for modelling theophylline drug. Also, a sensitivity analysis was carried out that shows the robustness and optimality of the model. Weibull, I model shows a significant variation of the model fit with a sharp decline at high dose. Therefore, Weibull I model is more sensitive to model Theophylline drug data.

Keywords:Dose-Response model; theophylline drug; sensitivity analysis; four parameters log-logistic model; brain-cousens hormesis model; cedergreen-ritz-streibig modified log-logistic model; and weibull distribution 1