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:

Factors Influencing Magnitude and Duration of Target Inhibition Following Antibody Therapy: Implications in Drug Discovery and Development. Antibodies or antibody-related fusion proteins binding to soluble antigens in plasma form an important subclass of approved therapeutics. Pharmaceutical companies are constantly trying to accelerate the pace of drug discovery and development of these antibodies and identify superior candidates in face of significant attrition rates. Understanding the interplay between drug- and target-related factors on magnitude and duration of target inhibition is imperative for successful advancement of these therapeutics. Simulations using a target-mediated drug disposition model were performed to evaluate the influence of antibody-target binding affinity, baseline target concentration, and target turnover on magnitude and duration of soluble target inhibition. These simulations assumed intravenous dosing of the antibody and evaluated multiple parameters over a wide range. These simulations reveal that improvement in affinity reaches a point of diminishing returns following which further improvement in affinity does not alter the magnitude and more importantly the duration of target inhibition. Evaluation of unbound antibody and target kinetics indicated that point of diminishing returns in duration of inhibition was due to target-mediated binding and subsequent elimination of antibody at later time points. Similarly, influence of baseline target concentration and target turnover on magnitude and duration of target inhibition in plasma is shown. Additionally, the fraction of dose eliminated via target mediated elimination (Fel(™)) can be a useful tool to enable selection of strategies to increase duration of target inhibition. The implications of these simulations in drug discovery and development with regard to target identification, antibody optimization, and backup candidate selection are discussed.
{"Chemical": []}