System and method for digital therapeutics implementing a digital deep layer patient profile

Abstract

A system, method, and computer-readable medium are disclosed for digital therapeutics directed to patient care specific to a disease for digital therapeutics that implement digital deep layer patient profile. Patient related information is presented by receiving data that includes patient data, lab result data, machine learning calculation data related to the patient, and physician result data. The data is mapped as to intensities, multiple dimensions and time. The mapping is converted to create an unstructured binary data with binary correlations as a digital deep layer patient profile. The digital deep layer patient profile can be processed with machine learning and image processing algorithms.

1 .- 20 . (canceled) 
     
     
         21 . A method of providing a treatment to a cancer patient, comprising
 (i) obtaining a deep layer patient profile (DLPP), wherein the DLPP comprises patient data and clinical data;   (ii) analyzing the DLPP, wherein analyzing comprises comparing the DLPP to a population of DLPPs from cancer patients;   (iii) determining a treatment based on (ii), wherein the treatment comprises initiating treatment, discontinuing treatment, or continuing treatment, wherein the treatment is selected from immunotherapy, chemotherapy, radiation therapy, surgery, targeted therapy, hormone therapy or a combination thereof; and   (iv) providing the treatment determined in (iii) to the cancer patient.   
     
     
         22 . The method of  claim 21 , wherein step (ii) analyzing the DLPP comprises using machine learning and image processing algorithms. 
     
     
         23 . The method of  claim 21 , wherein step (iii) determining treatment comprises using machine learning and image processing algorithms. 
     
     
         24 . The method of  claim 21 , wherein step (iii) determining treatment comprises using artificial intelligence. 
     
     
         25 . The method of  claim 21 , wherein step (iii) determining treatment comprises determining the presence or absence of at least one immune related adverse event (irAE) in the patient. 
     
     
         26 . The method of  claim 21 , wherein initiating treatment comprises administering an immunotherapy. 
     
     
         27 . The method of  claim 21 , wherein discontinuing treatment comprises altering dosage of treatment or ceasing treatment. 
     
     
         28 . The method of  claim 21 , wherein continuing treatment comprises administering or performing a new treatment. 
     
     
         29 . The method of  claim 21 , further comprising step (v) monitoring response by the patient to treatment. 
     
     
         30 . The method of  claim 21 , wherein the DLPP is updated over time. 
     
     
         31 . The method of  claim 30 , wherein the DLPP is updated using artificial intelligence. 
     
     
         32 . The method of any one of  claim 29 , wherein steps (ii)-(iv) or steps (ii)-(v) are repeated as the DLPP is updated. 
     
     
         33 . The method of  claim 21 , wherein the DLPP comprises data generated from genomic sequencing of blood, tissue, stool, urine, or combinations thereof. 
     
     
         34 . The method of  claim 21 , wherein clinical data comprises electronic health records (EHR). 
     
     
         35 . The method of  claim 21 , wherein patient data comprises data collected from patients measured with connected devices via mobile, phone or internet. 
     
     
         36 . The method of  claim 21 , wherein the DLPP comprises scientific and/or expert evidence of the cancer and/or treatment. 
     
     
         37 . The method of  claim 21 , wherein step (ii) analyzing the DLPP comprises assigning weight variables to the patient data and the clinical data. 
     
     
         38 . The method of  claim 37 , wherein the weight variables are assigned based on organization preference, expert opinion, artificial intelligence, a machine learning algorithm, or any combination thereof. 
     
     
         39 . The method of  claim 21 , wherein the population of DLPPs comprises at least one data set where the treatment was successful. 
     
     
         40 . A computer-implementable method of presenting patient related information comprising:
 receiving data that includes patient data, lab result data, machine learning calculation data related to the patient, and physician result data;   mapping the data as to intensities, multiple dimensions and time;   converting the mapping to create an unstructured binary data with binary correlations as a digital deep layer patient profile; and   processing the digital deep layer patient profile with machine learning and image processing algorithms.