Patent ID: 11881296
Assignee: OBERON SCIENCES ILAN LTD.
Field: Medical technology (Instruments)
Classification: CPC A  G | IPC A  G

Claim 0:
1. A computer implemented method for improving function of one or more biological system of a subject in an individualized way, and/or for overcoming partial or complete loss of effect, non-responsiveness, and/or partial or complete resistance of one or more biological systems to a treatment regimen, by identifying, quantifying, and/or implementing at least one inherent variability pattern, which is based on patterns learned from the subject and/or from other subjects, the method comprising:
identifying intra subject and/or inter subjects variability patterns or parameters, one or more non-variable individualized patterns or parameters and/or nonlinear networks and chaotic parameters;
identifying internal or external triggers, including those from other subjects, the environment, and non-subject related triggers;
quantifying the one or more variability patterns or parameters, and one or more non-variable individualized patterns or parameters nonlinear networks and chaotic parameters;
combining the quantified intra subject and/or inter subjects variability patterns, and internal or external triggers, nonlinear networks and chaotic parameters, and/or non-variable individualized patterns with the subject's own patterns of function in one or more biological systems for providing one or more combined patterns or parameters;
incorporating the one or more of the combined patterns or parameters into treatment regimens by applying a closed-loop machine learning algorithm comprising deep learning capabilities in which the learning on some features is guided or supervised learning, while learning on other features is unguided or unsupervised learning, to the one or more of the combined patterns or parameters;
determining subject-specific output parameters relating to at least one target system function by applying irregularity generating-algorithms, for determining irregularity in dosage and/or in time interval ranges for one or more drugs administration to the subject;
utilizing the subject-specific output parameters to improve the at least one target system function by using the deep machine learning algorithm by applying a subject-tailored continuously or semi continuously inherent variability pattern, thereby facilitating continual improvement of the target system; and
administering to the subject the one or more drugs according to the irregularity in dosage and/or time interval ranges.