Identifying and quantifying individualized variability-patterns and implementing them for improved efficacy of systems

Abstract

The disclosure provides methods for improving the function of systems regimens, devices by identifying, quantifying, and implementing at least one inherent variability pattern which is based on patterns learned from a specific subject or from other subjects including subject's variability patterns, such as, DNA, genes, nucleic acids, RNA, proteins, cells, organs, biological pathway(s), or whole body variability. There are provided herein devices, systems, and methods for real time or delayed altering of the parameters of system's regimens, for improving biological systems functions. Any system used by humans, or affect human function, wherein the parameters are updated using inherent variabilities signatures with and without other individualized patterns from a subject or from other subjects, can increase the accuracy and efficacy of the system for achieving the desired goal. Output parameters are continuously, semi continuously, or conditionally being updated based on measurements and inputs provided to a compute circuitry configured to facilitate closed loop machine learning capabilities.