(untitled) (Asian Journal of Pharmaceutics (AJP), 2019)
Aim: The maintenance of mean arterial pressure (MAP) is a critical parameter which needs to be continuously maintained in patients in trauma or recuperating from surgery. The effective means of maintaining it is through intravenous infusions like potent vasoactive drugs like sodium nitroprusside (SNP) and nitro glycerine (NTG). Materials and Methods: Maintenance of MAP is critical, and to keep it control many drug delivery and control strategies powered by fuzzy logic, artificial neural network, and internal model control are used. In this work a modeling and simulation study was attempted to develop and validate a viable computational therapeutic model of the patient infused with the drug. Results and Discussion: The model developed helps us to study and predict the patient’s response to the drug during simulation stages. This work considers the modeling of patients based on based on an open source dataset of MAP in response to the drug administered (NTG) collected from a critical care unit. Conclusion: The data obtained was used to develop a therapeutic model based the first order–dead time using the linear time domain system identification method. The obtained models were classified into fast responders, normal responders and slow responders based on the model parameters.