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:

In vitro, ex vivo and in vivo examination of buccal absorption of metoprolol with varying pH in TR146 cell culture, porcine buccal mucosa and Göttingen minipigs. This work studied the buccal absorption of metoprolol in vitro, ex vivo and in vivo as a function of buffered pH at 7.4, 8.5, 9.0 and 9.5. Permeability studies showed a correlation (r(2)=0.92) between in vitro TR146 cell culture and ex vivo porcine buccal mucosa in a modified Ussing chamber. A higher apparent permeability was observed at higher pH values, i.e. the more compound that was unionised the higher the permeability. In vivo studies were conducted in anaesthetised Göttingen mini-pigs. A clear influence of pH on the absorption was seen and a significant higher absolute bioavailability was obtained after buccal dosing (58-107%) compared to oral (3%) administration, ranging 58-107% and 3%, respectively. Macroscopically, no local toxic effects were observed by visual inspection of mini-pig cheeks. A very clear level C in vitro in vivo correlation (r(2)=0.98) was obtained between the observed in vitro permeabilities and the bioavailability observed in vivo, suggesting that the two in vitro models have good predictive power for drug delivery, which could be a useful tool for future formulation developments intended for buccal delivery.
{"Chemical": ["metoprolol"]}