Abstract 1947: Modelling of lipid-based nanoparticle pharmacokinetics and tumor accumulation using preclinical models of ovarian cancer
Bibliographic record
Abstract
Background: The development of lipid-based nanoparticles for the delivery of drugs, imaging agents, ect. to solid tumors continues to yield promising candidates for clinical testing. However, concerns have been raised over the poor translation of preclinical datasets with nanoparticle-enabled therapies into clinical outcomes. In an effort to support the utility of preclinical tumors models for predicting nanoparticle accumulation, we have created a multi-compartmental pharmacokinetic model for lipid-based nanoparticles using experimental data in two prevalent xenograft models of ovarian cancer.Methods: Two ovarian cancer xenograft models, SK-OV-3 and OV-90, were orthotopically established in a single ovary of athymic nude mice. Once the tumors had reached a volume of 0.5-0.7 mm2, the mice were intra-venously administered equivalent doses of radio-labelled nanoparticles, either porphyrin-lipid-containing PEGylated nanovesicles (Porphysomes) and PEGylated liposomes. At six timepoints post administration (6, 12, 18, 24, 36, and 48 hours) a full necropsy was preformed, and the organs measured for radio-activity. The concentrations of nanoparticles in tumors and major organs were calculated and plotted versus time. A multi-compartmental pharmacokinetic model was constructed using the time-dependent concentration of nanoparticles for either xenograft model.Results: The pathology of the orthotopic SK-OV-3 and OV-90 models were remarkably different in their vascular-permeability and cellular density, and these differences contributed to diverging nanoparticle biokinetics. Porphysome accumulation (%I.D./g), exposure (A.U.C.), and delivery efficiency (%) were significantly greater in the SK-OV-3 tumors compared with control organs (e.g., healthy ovary, muscle, etc.). Liposomes, however, did not exhibit this trend in SK-OV-3 tumors. In the OV-90 tumors, both nanoparticles exhibited increased but statistically insignificant accumulation and exposure compared with control organs. Only Porphysomes demonstrated improved delivery efficiency in the OV-90 tumors. Modelling the pharmacokinetics of the nanoparticles in a multi-compartmental model revealed distinctive kinetic parameters specific to each nanoparticle type and tumor pathology. In particular, differences were observed in the clearance rates of Porphysomes and liposomes, providing a possible explanation for their dissimilar tumor accumulations and exposures.Conclusions: Differences in the accumulation of lipid-based nanoparticles in preclinical models of ovarian cancer appear most sensitive to vascular permeability and cellular density of the xenograft. Adjusting for xenograft-dependent kinetic parameters, the Porphysome demonstrated improved but statistically insignificant tumor exposure and delivery efficiency compared with liposomes.Citation Format: Michael S. Valic, Wenlei Jiang, Lili Ding, Juan Chen, Stéphanie Lheureux, Amit M. Oza, Gang Zheng. Modelling of lipid-based nanoparticle pharmacokinetics and tumor accumulation using preclinical models of ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1947.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".