In silico algorithm for optimization of pharmacokinetic studies of [25Mg2+]porphyrin-fullerene nanoparticles
The search for effective pharmacophores to treat ischemic stroke is precipitated by the prevalence and high mortality of the condition. Optimization of preclinical scenarios for promising neuroprotectants by mathematical modeling using up-to-date computational platforms is a well-defined and urgent task. This study aimed to develop a drug-oriented model represented by an ordinary differential equation system to study pharmacokinetics of 25Mg2+-releasing porphyrin-fullerene nanocationite PMC16 in silico using MATLAB and adjust computating model's adequatness using in vivo rat model. The developed five-compartment model predicts the distribution of nanoparticles in organs and tissues (e.g. the brain, the heart and the liver) for the purpose of experimental parameters optimization. The in silico produced pharmacokinetic curves show good agreement with the data obtained using in vivo rat model of ischemic stroke. The in silico and in vivo results indicate that PMC16 nanoparticles effectively cross the blood-brain barrier.