You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["Chemical"].

Please return the output as a JSON object of the format: {"Chemical": ["Arsenic", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Development of solid lipid nanoparticles (SLNs) of lopinavir using hot self nano-emulsification (SNE) technique. Solid lipid nanoparticles (SLNs) of poor orally bioavailable drug lopinavir were prepared using hot self nano-emulsification (SNE) technique. Hot isotropic mixture of stearic acid, poloxamer and polyethylene glycol was spontaneously self nano-emulsify in hot water and SLNs were formed with subsequent rapid cooling. Self nano-emulsification ability of stearic acid, poloxamer and polyethylene glycol mixture was assessed by ternary phase diagram study. Optimized SLNs were having particle size of 180.6 ± 2.32 nm (PDI=0.133 ± 0.001), 91.5 ± 1.3% entrapment efficiency and zeta potential of -13.4 ± 0.56 mV. SLNs were evaluated by transmission electron microscopy (TEM) and atomic force microscopy (AFM) for morphological study. Further, Differential scanning calorimetry (DSC) and X-ray diffraction (XRD) of SLNs were also performed for checking solid state characterization. Higher oral bioavailability was found for lopinavir loaded SLNs in comparison to bulk lopinavir due to higher lymphatic drug transport (p<0.05). Results indicate that SLNs of higher fatty acids can be successfully prepared by hot SNE technique.
{"Chemical": ["lopinavir", "fatty acids", "polyethylene glycol", "stearic acid", "poloxamer"]}