Systems And Methods For Full Body Circulation And Drug Concentration Prediction
A method for predicting drug concentration levels includes receiving at least one subject characteristic of the subject, and executing a full body circulation model by: determining a first concentration of the drug in a first blood flow entering a first organ determining a second concentration of the drug in the first organ, determining a third concentration of a drug in a third blood flow entering a second organ, the third blood flow downstream of the first organ, and determining, using the second organ model a fourth concentration of the drug in the second organ.
Claim CLM-00001. 1. A system for predicting drug concentration levels as a function of time in one or more organs of a subject, comprising:
a subject database including at least one subject characteristic of the subject; a drug database including at least one drug characteristic of a drug to be administered to the subject; and a drug concentration prediction engine, the drug concentration engine configured to:
execute a full body circulation engine using the at least one subject characteristic to determine a plurality of blood flow rates to the one or more organs of the subject;determine a first concentration of the drug in a first blood flow entering a first organ based on an initial drug dosage and the blood flow rate to the first organ;modify, using the at least one subject characteristic, a first drug concentration prediction model of the first organ;determine a second concentration of the drug in the first organ using the modified first drug concentration prediction model;determine a third concentration of the drug in a second blood flow entering a second organ downstream of the first organ based on the second concentration and the blood flow rate to the second organ;modify, using the at least one subject characteristic, a second drug concentration prediction model of the second organ; anddetermine a fourth concentration of the drug in the second organ using the modified second drug concentration prediction model.
Claim CLM-00010. 10. A method for predicting drug concentration levels as a function of time in one or more organs of a subject, comprising:
receiving at least one subject characteristic of the subject; receiving at least one drug characteristic of a drug to be administered to the subject; executing a full body circulation engine using the at least one subject characteristic to determine a plurality of blood flow rates to the one or more organs of the subject; determining a first concentration of the drug in a first blood flow entering a first organ based on an initial drug dosage and the blood flow rate to the first organ; modifying a first drug concentration prediction model of the first organ using the at least one subject characteristic; determining a second concentration of the drug in the first organ using the modified first drug concentration prediction model; determining a third concentration of the drug in a second blood flow entering a second organ downstream of the first organ based on the second concentration and the blood flow rate to the second organ; modifying a second drug concentration prediction model of the second organ using the at least one subject characteristic; and determining a fourth concentration of the drug in the second organ using the modified second drug concentration prediction model.
Claim CLM-00018. 18. A system for training a drug concentration prediction model, comprising:
a training database storing a plurality of subject profiles, each subject profile including a known drug concentration and a corresponding at least one subject characteristic; and a machine learning engine including a plurality of drug concentration prediction models and at least one machine learning engine, the machine learning engine configured to:
execute the plurality of drug concentration prediction models to generate a plurality of predicted drug concentrations;compare the plurality of predicted drug concentrations to a corresponding plurality of known drug concentrations to generate a comparison result;compare the comparison result to a comparison condition;responsive to the comparison result satisfying the comparison condition, output the plurality of drug concentration prediction models; andresponsive to the comparison result not satisfying the comparison condition, adjust at least one parameter of the drug concentration prediction models.
Claim CLM-00026. 26. A method for training a drug concentration prediction model, comprising:
receiving a plurality of subject profiles, each subject profile including a known drug concentration and a corresponding at least one subject characteristic; executing, by a machine learning engine including a plurality of drug concentration prediction models and at least one machine learning engine, the plurality of drug concentration prediction models to generate a plurality of predicted drug concentrations; comparing the plurality of predicted drug concentrations to a corresponding plurality of known drug concentrations to generate a comparison result; comparing the comparison result to a comparison condition; responsive to the comparison result satisfying the comparison condition, outputting the plurality of drug concentration prediction models; and responsive to the comparison result not satisfying the comparison condition, adjusting at least one parameter of the drug concentration prediction models.
