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:

Statistical modeling, optimization and characterization of spray-dried solid self-microemulsifying drug delivery system using design of experiments. The present study systematically and simultaneously investigates the influence of process variables of spray-drying on the properties of solid self-microemulsifying drug delivery system (SMEDDS) using design of experiment (DOE) and optimizes them in order to produce solid-SMEDDS satisfying pre-defined powder quality attributes. Flurbiprofen-loaded liquid-SMEDDS was dispersed in dextran and spray-dried. After preliminary screening, the independent factors selected according to three-factor, three-level Box-Behnken design were inlet temperature (X(1)), feed rate (X(2)) and carrier concentration (X(3)). The responses used to compute the effects of independent factors were moisture content (Y(1)), yield (Y(2)), drug content (Y(3)) and droplet size (Y(4)) of the micro-emulsion. SMEDDS powder characteristics such as morphology, thermal behavior, crystallinity and flowability were also considered. Models were developed and model fitting analysis showed an adequate fit for all responses, indicating good predictability. Significant effects of processing parameters on powder characteristics were observed. The spray-drying process parameters were optimized as inlet temperature (134°C), feed rate (5%) and carrier concentration (0.6%) to produce solid-SMEDDS with acceptable moisture content (0.72±0.02%), yield (58.5±2.9%), drug content (70.1±2.7 mg/g) and droplet size (166.8±13.8 nm). Validation of the optimization process in five batches showed experimental value very close to the predicted one, ensuring the reproducibility of the developed models. Furthermore, optimized parameters resulted a highly crystalline flurbiprofen changed to an amorphous form. In conclusion, this study demonstrated the applicability of the DOE approach for optimizing the process parameters to manufacture solid-SMEDDS with desired quality attributes.
{"Chemical": ["Flurbiprofen", "flurbiprofen"]}