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:

Production of dosage forms for oral drug delivery by laminar extrusion of wet masses. Laminar extrusion of wet masses was studied as a novel technology for the production of dosage forms for oral drug delivery. Extrusion was carried out with a ram extruder. Formulations contained either microcrystalline cellulose (MCC) or dicalcium phosphate (DCP) as diluent, hydroxypropyl methylcellulose (HPMC), lactose, and water. Extrudates were characterized for their tensile strength, Young's modulus of elasticity, water absorption, gel forming capacity, and release of two model drugs, coumarin (COU) and propranolol hydrochloride (PRO). Cohesive extrudates could be produced with both filling materials (MCC and DCP) when HPMC was included as a binder at low amounts (3.3-4.5% w/w dry weight). Employing more HPMC, the elasticity of the wet masses increased which resulted in distinct surface defects. For MCC, the maximum HPMC amount that could be included in the formulations (15% w/w dry weight) did not affect the mechanical properties or decrease the drug release significantly. For DCP extrudates, the maximally effective HPMC amount was 30% (w/w dry weight) with influence on both the mechanical properties and drug release. This study suggests that laminar extrusion of wet masses is a feasible technique for the production of dosage forms for oral drug delivery.
{"Chemical": ["dicalcium phosphate", "propranolol hydrochloride", "PRO", "COU", "DCP", "coumarin", "lactose"]}