Method of measuring efficacy of treatment for multiple sclerosis

A method of measuring efficacy of a first treatment of multiple sclerosis (MS) in an animal in a vivarium comprising the steps of:

• (a) placing a study animal in a cage in the vivarium and enrolling the study animal in a study;
• (b) electronically observing one or more animal activities in real-time of the study animal using a combination of electronic cameras, infrared (IR) lighting of the study animals, and electronic hardware including computation and communication hardware;
• (c) selecting a single “LASSO metric” with an associated scalar “activity-drop value”;
• (d) selecting an “MS health detection function,” wherein an input to the MS health detection function comprises an animal health dataset;
• and wherein an output of the MS health detection function comprises an animal health severity scalar for the animal;
• (e) collecting a set of nightly activity data for the animal comprising a plurality of activity scalars for the animal each night, wherein the nightly activity scalars are collected repeatedly and continually throughout a night;
• (f) computing a LASSO best-fit of a first piece-wise linear function to the nightly activity data, generating a LASSO L0, L1 and L2;
• (g) applying the LASSO metric to the generated LASSO L0, L1 and L2, generating a nightly activity-drop value;
• (h) adding the nightly activity-drop value into the “animal health dataset,” wherein the animal health dataset comprises the nightly activity-drop values;
• (i) applying the MS health detection function to the animal health dataset;
• (j) iterating steps (f) through (h) for sequential nights until a terminating condition is reached;
• wherein a first measured efficacy of the first treatment comprises
• comparing the animal health severity scalars from step (i) to animal health severity scalars from a reference treatment;
• (k) removing the study animal from the study when the terminating condition is reached.