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:

Identifying the correlation between drug/stabilizer properties and critical quality attributes (CQAs) of nanosuspension formulation prepared by wet media milling technology. Wet media milling by top down method has proved to be an effective method to prepare nanosuspension of poorly soluble drugs/APIs. Few or no attempts have been made so far to understand the feasibility of nanosuspension formulation in terms of the mechanism of stabilization as a function of drug properties. The objective of this study was to understand the effect of drug substance and stabilizer properties to form a successful nanosuspension product. From this study, logP and enthalpy were concluded to have a direct correlation on the feasibility of formation of a stable nanosuspension. The most likely candidate for media milling was a drug substance with a high enthalpy and hydrophobicity which can be stabilized either electrostatically or sterically. The least likely candidate will be one that is hydrophilic and having a very low enthalpy value. Also the choice of an ideal stabilizer/surfactant was found to be influenced by the degree of hydrophobicity of the drug itself. Finally the morphology of the starting drug was found to significantly affect the milling time required to produce submicron particles.
{"Chemical": []}