Complex Factors and Challenges that Affect the Pharmacology, Safety and Efficacy of Nanocarrier Drug Delivery Systems

Abstract

Major developments in nanomedicines, such as nanoparticles (NPs), nanosomes, and conjugates, have revolutionized drug delivery capabilities over the past four decades. Although nanocarrier agents provide numerous advantages (e.g., greater solubility and duration of systemic exposure) compared to their small-molecule counterparts, there is considerable inter-patient variability seen in the systemic disposition, tumor delivery and overall pharmacological effects (i.e., anti-tumor efficacy and unwanted toxicity) of NP agents. This review aims to provide a summary of fundamental factors that affect the disposition of NPs in the treatment of cancer and why they should be evaluated during preclinical and clinical development. Furthermore, this chapter will highlight some of the translational challenges associated with elements of NPs and how these issues can only be addressed by detailed and novel pharmacology studies.

Keywords: mononuclear phagocyte system (MPS); nanomedicines; nanoparticles; pharmacodynamics; pharmacokinetics; pharmacology; tumor microenvironment.

Figure 1

A brief history of the development of nanomedicines and other carrier-mediated agents.

Figure 2

Complexity of the tumor microenvironment. The tumor microenvironment includes extracellular matrix (ECM), which poses multi-faceted barriers to drugs’ transport. The dense tumor stromal tissue, which is composed of collagens, fibronectin and hyaluronan, an abundance of cancer-associated fibroblasts, and aberrant interactions between infiltrating tumor-associated immune cells, cancer cells, and cancer-associated fibroblasts (CAF). Reproduced with permission from Lucas et al. [23]. Copyright Future Medicine Ltd., 2017.

Figure 3

Activity of the MPS (phagocytosis and production of reactive oxygen species [ROS]) in monocytes from blood compared to the clearance of PEGylated liposomal nanocarriers in mice, rats, dogs, and patients. The ability to more accurately convert preclinical data into human patients may best be performed by measuring the factors responsible for NP uptake and clearance, such as the cellular function of the MPS. The mean values for three species are represented by individual symbols, with ◊ as PLD, □ as S-CKD602, and X as SPI-077. The exponential line of best fit for each group is represented by the lines. Overall, a positive association can be seen between cellular function and clearance of PEGylated liposomal nanocarrier agents. Reproduced with permission from Caron et al. J Pharmacol Exp Ther. 2013, 347, 599–606.

Figure 4

Calculating nanoparticle delivery efficiency using standard percent injected dose (%ID) calculation versus relative distribution index-over time (RDI-OT). The conventional calculation of tissue %ID represents the amount of drug in the target tissue at a single time point in time. However, RDI-OT is calculated for each time point within the profile, providing a new profile of the delivery efficiency of the nanoparticle over time compared to a single point in time.

Figure 5

Correlation plots for all data sets between %ID in Tumor (per Wilhelm et al.) and AUCtumor/AUCblood ratio (%) (A), RDI-OT AUCtumor (B), and tumor Cmax (C). Plots are shown with all data sets (outliers shown as □) and with outliers excluded. There was no relationship between %ID in Tumor and AUCtumor/AUCblood ratio (%) [ρ = 0.183 all data (AD); ρ = 0.151 excluding outliers (EO)] and a weak relationship between %ID in Tumor and RDI-OT AUCtumor (ρ = 0.319 AD; ρ = 0.289 EO). There was a moderate relationship between %ID in Tumor and the tumor Cmax (ρ = 0.562 AD; ρ = 0.572 EO). Reproduced and modified under Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC) from Price et al. Sci Adv. 2020;6(29):eaay9249.