A physiologically based pharmacokinetic model to predict the superparamagnetic iron oxide nanoparticles (SPIONs) accumulation in vivo

AbstractSuperparamagnetic iron oxide nanoparticles (SPIONs) have been identified as a promising material for biomedical applications. These include as contrast agents for medical imaging, drug delivery and/or cancer cell treatment. The nanotoxicological profile of SPIONs has been investigated in different studies and the distribution of SPIONs in the human body has not been fully characterized. The aim of this study was to develop a physiologically-based pharmacokinetic (PBPK) model to predict the pharmacokinetics of SPIONs. The distribution and accumulation of SPIONs in organs were simulated taking into consideration their penetration through capillary walls and their active uptake by specialized macrophages in the liver, spleen and lungs. To estimate the kinetics of SPION uptake, a novel experimental approach using primary macrophages was developed. The murine PBPK model was validated against in vivo pharmacokinetic data, and accurately described accumulation in liver, spleen and lungs. After validation of the murine model, a similar PBPK approach was developed to simulate the distribution of SPIONs in humans. These data demonstrate the utility of PBPK modeling for estimating biodistribution of inorganic nanoparticles and represents an initial platform to provide computational prediction of nanoparticle pharmacokinetics.</jats:p

Physiologically based pharmacokinetic modeling for dose optimization of quinine-phenobarbital coadministration in patients with cerebral malaria

Patients with cerebral malaria with polymorphic Cytochrome P450 2C19 (CYP2C19) genotypes who receive concurrent treatment with quinine are at risk of inadequate or toxic therapeutic drug concentrations due to metabolic drug interactions. The study aimed to predict the potential dose regimens of quinine when coadministered with phenobarbital in adult patients with cerebral malaria and complications (e.g., lactic acidosis and acute renal failure) and concurrent with seizures and acute renal failure who carry wild‐type and polymorphic CYP2C19. The whole‐body physiologically based pharmacokinetic (PBPK) models for quinine, phenobarbital, and quinine–phenobarbital coadministration were constructed based on the previously published information using Simbiology®. Four published articles were used for model validation. A total of 100 virtual patients were simulated based on the 14‐day and 3‐day courses of treatment. using the drug–drug interaction approach. The predicted results were within 15% of the observed values. Standard phenobarbital dose, when administered with quinine, is suitable for all groups with single or continuous seizures regardless of CYP2C19 genotype, renal failure, and lactic acidosis. Dose adjustment based on area under the curve ratio provided inappropriate quinine concentrations. The recommended dose of quinine when coadministered with phenobarbital based on the PBPK model for all groups is a loading dose of 2000 mg intravenous (i.v.) infusion rate 250 mg/h followed by 1200 mg i.v. rate 150 mg/h. The developed PBPK models are credible for further simulations. Because the predicted quinine doses in all groups were similar regardless of the CYP2C19 genotype, genotyping may not be required