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: ["Protein", "Chemical"].

Please return the output as a JSON object of the format: {"Chemical" : ["Dexamethasone", ...], "Protein" : ["BRCA-1", ...]}. 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:

A Physiologically-Based Pharmacokinetic Modelling Approach to Predict Disease-Drug Interactions: Suppression of CYP3A by IL-6.
Elevated cytokine levels can down-regulate expression of cytochrome P450 enzymes (CYPs) and suppress their activity. Treatment of inflammation or infection with cytokine-modulating therapeutic proteins (TP) could reverse suppression manifesting as therapeutic protein-drug drug interactions (TP-DDI). A physiologically-based pharmacokinetic model was used to quantitatively predict the impact of IL-6 on sensitive CYP3A4 substrates. Elevated simvastatin AUC in virtual rheumatoid arthritis patients, following 100 pg/mL of IL-6 was comparable to observed clinical data (59% versus 58%). In virtual bone marrow transplant (BMT) patients, 500 pg/ml of IL-6 resulted in increase in cyclosporine AUC that was in good agreement with the observed data (45% versus 39%). In a different group of BMT patients treated with cyclosporine, the magnitude of interaction with IL-6 was under predicted ~3-fold. The complexity of TP-DDI highlights underlying pathophysiological factors to be considered but these simulations provide valuable first steps towards predictions of TP-DDI risk.Clinical Pharmacology & Therapeutics (2013); accepted article preview online 10 April 2013 doi:10.1038/clpt.2013.79.
{"Chemical": ["cyclosporine", "simvastatin"], "Protein": ["CYP3A4", "IL-6", "CYP3A", "cytochrome P450", "cytokine", "CYPs"]}