Computer systems for treating diseases
The present invention relates to computer-implemented methods and system for analyzing a biomarker which cycles in a subject. In some other aspects, the present invention relates to analyzing a biomarker which at least initially increases or decreases in amount in a subject following a treatment for a disease. In further aspects, the present invention relates to computer-implemented methods and systems for determining a preferred time to administer a therapy to treat a disease in a subject. The present invention also relates to computer program product to implement the methods. Further, the present invention relates to methods of determining the timing of treating a disease in a subject in which the immune system is cycling.
1. A non-transitory computer-readable information storage medium having stored thereon instructions, that if executed by one or more processors, perform a method comprising:
i) obtaining from a first memory measurements of an acute phase inflammatory marker in samples from a subject having a disease characterized by production of regulator cells and cycling immune system markers;
ii) obtaining from a second memory a model of cycling of the acute phase inflammatory marker;
iii) fitting the measurements to the model;
iv) obtaining a best-fit curve of the measurements to the model to estimate a periodicity of the cycling of the acute phase inflammatory marker;
v) projecting the obtained best-fit curve into the future; and
vi) outputting a preferred time in the future, based on the projected best-fit curve, to administer a therapy to treat the disease;
wherein the preferred time is a time period in the cycling of the acute phase inflammatory marker where the level of the acute phase inflammatory marker is increasing, between halfway between a minimum in the cycle and a maximum in the cycle, but before the level of the acute phase inflammatory marker has peaked; and
wherein the therapy is selected from the group consisting of an anti-proliferative drug and radiation.
2. The computer-readable information storage medium of claim 1 , wherein the best-fit curve is a fit to a harmonic model of the cycling of the acute phase inflammatory marker, and obtaining the best-fit curve further comprises fitting the harmonic model to the measurements multiple times using different initial conditions for each fit.
3. The computer-readable information storage medium of claim 1 , wherein the method further comprises generating a confidence measure by comparing a similarity in a fit result produced by each fitting.
4. The computer-readable information storage medium of claim 1 , wherein obtaining the best-fit curve further comprises imposing a box constraint on at least some parameters of the model to guide optimization to biologically realistic regions.
5. The computer-readable information storage medium of claim 1 , wherein the model has a heavy tail to allow for noisy nature of the measurements.
6. The computer-readable information storage medium of claim 1 , wherein the method further comprises determining a variance-stabilizing transformation of the measurements prior to determining the periodicity based on the transformed measurements.
7. The computer-readable information storage medium of claim 6 , wherein the variance-stabilizing transformation of measurements is logarithm of the measurements.
8. The computer-readable information storage medium of claim 1 , wherein the measurements are for two or more different acute phase inflammatory markers which are cycling in the subject.
9. A computer system for determining a preferred time to administer a therapy to treat a disease characterized by cycling immune system markers, the computer system comprising:
a first memory for storing measurements of an acute phase inflammatory marker in samples from a subject having a disease characterized by production of regulator cells and cycling immune system markers;
a second memory for storing a model of cycling of the acute phase inflammatory marker; and
one or more processors to:
i) fit the measurements to the model;
ii) obtain a best-fit curve of the measurements to the model to estimate a periodicity of the cycling of the acute phase inflammatory marker;
iii) project the obtained best-fit curve into the future;
iv) output a preferred time in the future, based on the projected best-fit curve, to administer a therapy to treat the disease;
wherein the preferred time is a time period in the cycling of the acute phase inflammatory marker where the level of the acute phase inflammatory marker is increasing, between halfway between a minimum in the cycle and a maximum in the cycle, but before the level of the acute phase inflammatory marker has peaked; and
wherein the therapy is selected from the group consisting of an anti-proliferative drug and radiation.