Pharmacokinetics of PEGylated Gold Nanoparticles: In Vitro—In Vivo Correlation

Abstract

Data suitable for assembling a physiologically-based pharmacokinetic (PBPK) model for nanoparticles (NPs) remain relatively scarce. Therefore, there is a trend in extrapolating the results of in vitro and in silico studies to in vivo nanoparticle hazard and risk assessment. To evaluate the reliability of such approach, a pharmacokinetic study was performed using the same polyethylene glycol-coated gold nanoparticles (PEG-AuNPs) in vitro and in vivo. As in vitro models, human cell lines TH1, A549, Hep G2, and 16HBE were employed. The in vivo PEG-AuNP biodistribution was assessed in rats. The internalization and exclusion of PEG-AuNPs in vitro were modeled as first-order rate processes with the partition coefficient describing the equilibrium distribution. The pharmacokinetic parameters were obtained by fitting the model to the in vitro data and subsequently used for PBPK simulation in vivo. Notable differences were observed in the internalized amount of Au in individual cell lines compared to the corresponding tissues in vivo, with the highest found for renal TH1 cells and kidneys. The main reason for these discrepancies is the absence of natural barriers in the in vitro conditions. Therefore, caution should be exercised when extrapolating in vitro data to predict the in vivo NP burden and response to exposure.

Toxicologic Concerns with Current Medical Nanoparticles

“…The NP size is an important parameter that determines the pharmacokinetics of NPs [ 20 ]. Their optical properties have been reported to be size-dependent, giving them different colors due to absorption in the visible region [ 21 ]. Due to their large surface area and nanoscale size, NPs have unique physical and chemical properties [ 18 , 22 ].…”

Physiologically Based Pharmacokinetic Modeling of Nanoparticle Biodistribution: A Review of Existing Models, Simulation Software, and Data Analysis Tools

“…MATLAB provides a range of mathematical and numerical methods for solving PBPK model equations, parameter estimation, and sensitivity analysis [ 53 , 54 , 55 , 56 , 61 , 70 , 71 , 72 , 73 , 74 , 75 , 76 ]. In particular, several MATLAB toolkits can be used for modeling, simulating, and analyzing PBPK systems, namely SimBiology [ 57 , 77 , 78 , 79 , 80 ], PottersWheel [ 81 , 82 ], and IntiQuan IQM Tools [ 70 ]. MATLAB was used to simulate the biodistribution of NPs of different sizes in the range from 46 to 162 nm after intravenous injection into the plasma compartment of rats [ 54 ] ( Figure 2 B).…”

“…OriginPro [ 154 ] is a data analysis and graphing software that includes tools for peak fitting, surface fitting, statistics, and signal processing [ 155 ]. It can be utilized for parameter estimation of PBPK models [ 80 ].…”

Analyzing the metabolic fate of oral administration drugs: A review and state-of-the-art roadmap

“…Currently, PBPK models are usually utilized as a prominent tool to use in silico (distribution) and CL and provide a predictable process of the overall PK profile, which applies in the pharmaceutical industry constantly (Kostewicz et al, 2014). PBPK integrates information such as system properties, drug properties, formulation properties, and anatomical structures of tissues or organs through mathematical models, which can provide a comprehensive description of the in vivo PK behavior of drugs (Dubaj et al, 2022). The model can accurately reflect the drug concentration vs time in vivo, as well as the effects of disease and physiological factors on PK behavior.…”