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:

Population pharmacokinetics of atorvastatin and its active metabolites in children and adolescents with heterozygous familial hypercholesterolemia: selective use of informative prior distributions from adults. The population pharmacokinetics (PPK) of atorvastatin and its principal active metabolite, o-hydroxyatorvastatin, were described in 6-17 years old pediatric hypercholesterolemia patients with a 2-compartment model for both parent and metabolite. Informative prior distributions on selected parameters, based on adult data, were required to stabilize the model and were implemented using a Bayesian penalty term on the likelihood function in the nonlinear mixed effects model (NONMEM VI with PRIOR). Concentrations below the limit of quantitation were treated as censored data using a conditional likelihood function. Atorvastatin apparent oral clearance (CL/F) was described as a function of body weight using an allometric equation. Based on the final model, the typical CL/F estimates for a Tanner Stage 1 patient (35 kg weight) and Tanner Stage ≥2 (50 kg weight), would be 553 and 543 L/hour, respectively. When scaled allometrically, CL/F was similar to values reported for adults. Variability in atorvastatin PK was primarily affected by weight.
{"Chemical": ["o-hydroxyatorvastatin", "Atorvastatin", "atorvastatin"]}