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Being the fourth most fatal malignancy worldwide, pancreatic cancer is on track to become the second leading cause of cancer-related deaths in the United States by 2030. Gemcitabine is a first-line chemotherapeutic agent for pancreatic ductal adenocarcinoma (PDAC). Gemcitabine Elaidate (Gem Elaidate) is a lipophilic derivative which allows hENT1-independent intracellular delivery of gemcitabine and better pharmacokinetics and entrapment in a nanocarrier. Cancer cells and neovasculature are negatively charged compared to healthy cells. Palmitoyl-DL-carnitine chloride (PC) is a Protein kinase C (PKC) inhibitor which also provides a cationic surface charge to nanoliposomes for targeting tumor neovasculature and augmented anticancer potency. The objectives of our study are: (a) to develop and characterize a PKC inhibitor-anchored Gem Elaidate-loaded PEGylated nanoliposome (PGPLs) and (b) to investigate the anticancer activity of Gem Elaidate and PGPLs in 2D and 3D models of pancreatic cancer. The optimized PGPLs resulted in a particle size of 80 ± 2.31 nm, a polydispersity index of 0.15 ± 0.05 and a ζ-potential of +31.6 ± 3.54 mV, with a 93.25% encapsulation efficiency of Gem Elaidate in PGPLs. Our results demonstrate higher cellular uptake, inhibition in migration, as well as angiogenesis potential and significant apoptosis induced by PGPLs in 3D multicellular tumor spheroids of pancreatic cancer cells. Hence, PGPLs could be an effective and novel nanoformulation for the neovasculature-specific delivery of Gemcitabine Elaidate to treat PDAC.

The self-nano/microemulsifying drug delivery system is one of the well-established techniques for enhancing the solubility of poorly water-soluble drug molecules. The ratio of oil:surfactant:cosolvent plays a key role in globule size on dispersion into water, but there is very limited information on how a drug molecule affects the size. The rationale of this project was to illustrate the correlation between the particle size of nanoemulsion droplets and molecular descriptors of a drug. In the study, a self-nanoemulsifying preconcentrate containing drug with medium chain triglycerides (oil), dimethylacetamide (DMA, cosolvent), and Kolliphor EL (surfactant) was prepared for 40 drug molecules with diverse physicochemical properties. The selfnanoemulsifying preconcentrate was dispersed in water, and dynamic light scattering particle size was analyzed. A majority of drugs showed a significant increase in globule size compared to blank formulation, while few drugs showed a stark reduction in globule size. It is interesting to understand the attributes of molecules driving the self-emulsification and the diameter of nanoglobules. A systematic correlation of resultant particle size with 1D, 2D, and 3D molecular descriptors (overall more than 700 descriptors) was carried out for the data set using the PaDEL tool kit. The data compilation, curation, and analysis were performed using the SIMCA14 software. In the process of molecular descriptors screening, thereafter curation, 50 descriptors were selected using the genetic algorithm screening. The PLS-DA statistical method was employed for conversion of data into binomial systems. Final group of 5 descriptors: SpMiSpMin2_Bhe, RNCS, TDB9i, JG17, and ETA_Shape showed the correlation with particle size and classifying the drug molecules facilitating increase or decrease in particle size.

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