AND ABSTRACT Nanomedicines have found promising applications in the diagnostics and treatment of cancer in laboratory animals, but the translation of animal results to clinical success is low. The current understanding of the interspecies extrapolation of nanoparticle (NP) pharmacokinetics and the role of physicochemical properties of NPs in the cellular uptake, tissue distribution, and delivery to the tumor tissue remains limited. The objective of this proposal is to identify key physiological and/or physicochemical factors in the tumor delivery efficiency of different NPs using a physiologically based pharmacokinetic (PBPK) modeling approach. The hypothesis is that tissue distribution and tumor delivery of different NPs could be simulated using a recently published PBPK model framework for gold NPs in healthy mice, rats, and humans from the principal investigator?s laboratory by adding a tumor compartment and using species- and NP-specific parameters.
Two specific aims were designed to test whether the hypothesis is true in both inorganic and organic NPs (or in either one of them).
Aim 1 : To identify key physicochemical, physiological, and kinetic rate determinants of tumor delivery efficiency of inorganic NPs.
Aim 2 : To identify key physicochemical, physiological, and kinetic rate determinants of tumor delivery efficiency of organic NP. This design is necessary because the model structure for organic NPs may be different from that of inorganic NPs due to the differences in synthesis methods, stability, biocompatibility, biodegradability, and other physicochemical factors. Experimental data for PBPK model calibration are from a recently published Cancer Nanomedicine Repository (CNR), in which tumor delivery efficiency was evaluated using the time- integrated area under the concentration as a dose metric. This project is novel because the creation of a PBPK model framework with a tumor compartment allows using a time-dependent dosimetry to evaluate delivery efficiency to organ-specific tumors. PBPK model evaluation will be based on the World Health Organization PBPK modeling guidelines. Sensitivity, uncertainty, and multivariate regression analyses will be conducted to comprehensively identify the key physicochemical determinants of tumor delivery efficiency of NPs. The proposed research is significant as the low delivery efficiency of cancer nanomedicines is an important research problem, which has been a critical barrier to advance in the field in the past 10 years. This project has broad impacts because, upon successful completion, it will greatly improve our understanding of the key determinants of tumor delivery of NPs and the results will help design NPs with improved tumor delivery efficiency to accelerate animal-to-human extrapolation of cancer nanomedicines and improve the clinical translation of new existing nanotechnologies. This proposal is highly interdisciplinary, involving materials science, cancer biology, pharmacology, toxicology, and mathematical modeling. The availability of our recently published NP PBPK model framework and the CNR database makes this proposal highly feasible and ideally suitable for the R03 program.
Many nanomaterial-based new drug formulations have been shown to be effective in the diagnostics and treatment of cancer in laboratory animals, but the translation of the animal results to humans has been quite limited. This project is relevant to public health because in the short term the proposed research will improve our fundamental understanding of the key determinants of nanomaterials in the distribution to tumor tissues of animals and humans. In the long term, the proposed research will provide strategies to help design nanomaterials with improved delivery efficiency to tumor tissues.
| Cheng, Yi-Hsien; Riviere, Jim E; Monteiro-Riviere, Nancy A et al. (2018) Probabilistic risk assessment of gold nanoparticles after intravenous administration by integrating in vitro and in vivo toxicity with physiologically based pharmacokinetic modeling. Nanotoxicology 12:453-469 |
| Lin, Zhoumeng (2017) Advance in physiologically based pharmacokinetic modelling: from the organ level to suborgan level based on experimental data. J Physiol 595:7265-7266 |
