Meta-Analysis of Nanoparticle Delivery to Tumors Using a Physiologically Based Pharmacokinetic Modeling and Simulation Approach

Abstract

Numerous studies have engineered nanoparticles with different physicochemical properties to enhance the delivery efficiency to solid tumors, yet the mean and median delivery efficiencies are only 1.48% and 0.70% of the injected dose (%ID), respectively, according to a study using a nonphysiologically based modeling approach based on published data from 2005 to 2015. In this study, we used physiologically based pharmacokinetic (PBPK) models to analyze 376 data sets covering a wide range of nanomedicines published from 2005 to 2018 and found mean and median delivery efficiencies at the last sampling time point of 2.23% and 0.76%ID, respectively. Also, the mean and median delivery efficiencies were 2.24% and 0.76%ID at 24 h and were decreased to 1.23% and 0.35%ID at 168 h, respectively, after intravenous administration. While these delivery efficiencies appear to be higher than previous findings, they are still quite low and represent a critical barrier in the clinical translation of nanomedicines. We explored the potential causes of this poor delivery efficiency using the more mechanistic PBPK perspective applied to a subset of gold nanoparticles and found that low delivery efficiency was associated with low distribution and permeability coefficients at the tumor site (P < 0.01). We also demonstrate how PBPK modeling and simulation can be used as an effective tool to investigate tumor delivery efficiency of nanomedicines.

Flow Rate Affects Nanoparticle Uptake into Endothelial Cells

“…Nanoparticles are a promising platform for delivering anticancer drugs directly to tumors and sparing the body from off‐target organ toxicity. [ 1,2 ] Upon systemic administration, nanoparticles will enter the bloodstream, circulate throughout the body and extravasate out of the blood vessel into the tumor to deliver their drug cargo. [ 3,4 ] However, many of the in vitro studies performed to characterize therapeutic nanoparticles do not recapitulate the dynamic environment of the bloodstream.…”

PBPK Modeling of Slightly Soluble Silver Nanomaterials and Regulatory Acceptance

“…The selection of organs to be incorporated into a PBPK model is based primarily on the exposure route, which for IV injection might not even include the lungs, stomach, and intestines. [ 4 ] For oral ingestion, generic PBPK models from drug development may recognize that the liver receives much of its blood supply from the spleen, pancreas, stomach, and intestines (see page 155 of ref. [ 3 ] ), which differs from the schematic in Figure 1, and there are some that explicitly include the stomach and intestines to account for GI tract dissolution (see Supporting Information of ref.…”

“…More specific to endocytic uptake of nanoparticles from therapeutic studies, Cheng et al utilize Hill functions in their analysis of 376 data sets. [ 4 ] Hill functions (see page 72 of ref. [ 31 ] ) describe processes that involve cooperative binding events that, like Langmuir adsorption, lead to fractional saturation and nonlinear behaviors.…”

“…The same concepts can be applied to pharmacological drug entities with appropriate changes in acronyms (P for pharmacological replaces T for toxicant), [ 2,3 ] and it should be noted that nanoparticle‐based therapeutics are known to pose distinctive modeling challenges. [ 4 ] PBTK and PBPK models connect exposure (nominal, administered, or applied) to doses at the organ level, thereby providing a basis for extrapolating animal results to human physiology.…”

Molecular Mechanisms, Characterization Methods, and Utilities of Nanoparticle Biotransformation in Nanosafety Assessments

“…[97][98][99][100][101][102] Therefore, the interactions at nano-macrophage interfaces may determine the capability of nanocarriers to reach their destinations in biomedical applications. A recent meta-analysis of published nanocarrier data from 2005 to 2015 using physiologically based pharmacokinetic model (PBPK) reported very low delivery efficiencies of current nanocarriers with mean value of 2.24% at 24 h and 1.23% at 168 h. [103] Since it is very time-and labor-consuming to explore nanocarriers with high delivery efficiency from thousands ENMs with different physicochemical properties, PBPK modeling and simulation are effective tools to identify the key factors responsible for tumor delivery kinetics.…”