Method for predicting treatment classes using behavior informatics
A system and method used to assess animal behavior includes a module having sensors that collects a variety of physical and biological data from a test subject. Interpretation of the data is provided to assess the test subject's behavior, neurology, biochemistry and physiology. The module is useful in observing the effects of a drug on the test animal and providing information on the drug's signature. Another advantage is the module's portability that allows it to be used in standard laboratory cages. This portability allows the animal to be tested in its own habitat, that can reduce any erroneous data due to stressing the animal when removed to a test cage. Additionally, the module's design allows for parallel data collection and interpretation from several laboratory animals undergoing different experiments. Multi-dimensional modeling of the test subject based the system's interpretation of the data allows pattern recognition of the drug signature, and predictive drug analysis.
1. A method of predicting whether a test treatment belongs to a class of test treatments having a pattern of animal behavior associated with said class of test treatments, said method comprising:
(a) administering a test treatment to at least one animal;
(b) using a computer to capture behavioral data of said at least one animal administered said test treatment;
(c) using a computer to compare information derived from an analysis of the captured data from (b) with stored class signature information from a database comprising signatures associated with treatment classes to predict a probability that the test treatment is a member of at least one treatment class represented in the stored class signature information, wherein said stored signature information was obtained by:
(i) collecting behavioral data from animals administered at least one known treatment which is a member of a class of treatments; and (ii) using a computer to define said signatures for said treatment class by correlating features of said behavioral data with said known treatment class member; and (iii) storing said signature information in a computer; and
(d) outputting a result from (c) that is indicative of whether said test treatment is a member of at least one treatment class.
2. The method of claim 1 wherein the captured data comprises information from one or more video cameras.
3. The method of claim 1 wherein the captured data comprises information from one or more video cameras and generates three-dimensional positions, orientations, and/or imaging characteristics of said at least one animal.