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Abstract

A method of measuring efficacy of test treatment of an autoimmune disease in an animal in a vivarium is described. Animal activity data is collected at multiple times during the night. Sequential time regions of the night are identified as high-activity, activity-drop, or low-activity regions. Embodiments are described to quantify a drop, during the night, of an animal's activity level. These quantified activity-drop scalars for consecutive nights are accumulated in an animal health dataset. This dataset is compared to healthy animals, a standard of care or a reference treatment for the first disease to determine efficacy of the test treatment. One embodiment quantifies an activity-drop by fitting straight-line curves through the data in the three nightly regions. Other embodiment uses a Fourier transform on a circle, LASSO, RANSAC or regression analyses for curve fitting. Another embodiment compares areas under data curves in the regions. Animals may be housed in cages with other animals.

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First Claim