Constant optimization of oral drug absorption kinetics in the compartment absorption and transit models using particle swarm optimization algorithm

Workshop and International Seminar on Science of Complex Natural Systems

Prabowo, K.^1 ; Sumaryada, T.^2,3 ; Kartono, A.^3

Department of Physics, Bogor Agricultural University, Jalan Meranti Kampus Dramaga IPB, 16880, Indonesia^1

Biopharmaca Research Center, Bogor Agricultural University, Jalan Taman Kencana No.3, Bogor

16128, Indonesia^2

Computational Biophysics and Molecular Research Group (CBMoRG), Department of Physics, Bogor Agricultural University, Jalan Meranti Kampus Dramaga IPB, 16880, Indonesia^3

关键词: Coefficient of determination;    Constant optimizations;    Dependent variables;    Explanatory variables;    Oral drug absorption;    Particle swarm optimization algorithm;    Plasma drug concentration;    Rate of absorptions;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/31/1/012007/pdf
DOI  :  10.1088/1755-1315/31/1/012007

来源: IOP

【 摘 要 】

Simulation of predictive modeling oral drug namely Compartment Absorption and Transit (CAT) using Particle Swarm Optimization (PSO) algorithm has been performed. This research will be carried out optimization of kinetic constant value oral drug use PSO algorithm to obtain the best global transport constant values for CAT equation that can predict drug concentration in plasma. The value of drug absorption rate constant for drug atenolol 25 mg is k10, k12, k21, k13and k31with each value is 0.8562, 0.3736, 0.2191, 0.4334 and 1.000 have been obtained thus raising the value of the coefficient of determination of a model CAT. From the experimental data plasma drug concentrations used are Atenolol, the coefficient of determination (R2) obtained from simulations atenolol 25 mg (PSO) was 81.72% and 99.46%. Better correlation between the dependent variable as the drug concentration and explanatory variables such as mass medication, plasma volume, and rate of absorption of the drug has increased in CAT models using PSO algorithm. Based on the results of CAT models fit charts can predict drug concentration in plasma.