Abstract 1947: Modelling of lipid-based nanoparticle pharmacokinetics and tumor accumulation using preclinical models of ovarian cancer
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».