Systems, methods, and apparatus for modeling and optimizing dialysis effects

A dialysis treatment simulation system for determining an amount of a drug removed by a dialysis treatment comprising:

• a dialysis filter including a blood side (arterial) chamber and a dialysate side (venous) chamber;
• a plasma container containing plasma or blood spiked with the drug;
• a first sampling port for removing a first series of samples over time of the plasma or blood spiked with the drug and measuring at least one of drug concentration, drug removal rate, drug ratio in the blood or plasma, and an amount of the drug removed of each of the first series of samples over time of the plasma or blood spiked with the drug;
• a plasma or blood pump for moving the plasma or blood to an input of the blood side (arterial) chamber of the dialysis filter;
• a second sampling port at the input of the blood side (arterial) chamber of the dialysis filter for removing a second series of samples over time of the plasma or blood spiked with the drug and measuring at least one of drug concentration, drug removal rate, drug ratio in the blood or plasma, and an amount of the drug removed of each of the second series of samples over time of the plasma or blood spiked with the drug;
• a membrane for separating the blood side (arterial) chamber of the dialysis filter from the dialysate side (venous) chamber of the dialysis filter and for removing waste products from the plasma or blood spiked with the drug;
• a third sampling port at the output of the blood side (arterial) chamber of the dialysis filter for removing a third series of samples over time of the plasma or blood spiked with the drug passed through the blood side (arterial) chamber of the dialysis filter and measuring at least one of drug concentration, drug removal rate, drug ratio in the blood or plasma, and an amount of the drug removed of each of the third series of samples over time of the plasma or blood spiked with the drug passed through the blood side (arterial) chamber of the dialysis filter;
• a dialysate reservoir container containing dialysate;
• a dialysate pump for moving the dialysate from the dialysate reservoir container to an input of the dialysate side (venous) chamber, wherein the dialysate carries the waste products from the plasma or blood spiked with the drug to an output of the dialysate side (venous) chamber;
• an effluent pump for receiving the dialysate with the waste products in the form of effluent fluid and for moving the effluent fluid from the output of the dialysate side (venous) chamber to an effluent container;
• and
• a fourth sampling port for removing a series of samples over time of the effluent fluid from the effluent container and for removing a fourth series of samples over time of the plasma or blood spiked with the drug from the effluent fluid and measuring at least one of drug concentration, drug removal rate, drug ratio in the blood or plasma, and an amount of the drug removed of each of the fourth series of samples over time of the plasma or blood spiked with the drug,
• wherein the amount of the drug removed by the dialysis treatment is determined by comparing measurements of a change in the first series of samples, the second series of samples, the third series of samples, and the fourth series of samples.

A computer system for determining an efficacy of a therapy comprising:

• a processor configured to:
• a) perform a dialysis treatment simulation for determining at least one of a total amount of or a rate of a drug removed by a dialysis treatment;
• wherein the dialysis treatment simulation includes:
• taking a series of blood or plasma samples over time from an arterial port, a venous port, an effluent container, and a blood or plasma reservoir of a dialysis treatment simulation system;
• and
• determining at least one of a drug concentration, drug removal rate, drug ratio in blood or plasma, and an amount of the drug removed at each of the arterial port, the venous port, the effluent container, and the blood or plasma reservoir;
• b) generate in silico a plurality of virtual patients for modeling a health condition based on data collected from a population of previously treated patients having the health condition,
• wherein the collected data represents at least one measured biological response of the previously treated patients to a previously administered therapeutic regimen of the drug,
• wherein each virtual patient includes at least one mathematical model representing a physiological system and exhibiting a one-to-one correspondence with one previously treated patient of the population of previously treated patients, and
• wherein the at least one mathematical model for each virtual patient is fitted to data of the corresponding one previously treated patient;
• c) apply the dialysis treatment simulation to the plurality of virtual patients over a simulated time period to simulate dialysis therapy;
• d) determine one or more physiological parameters in the plurality of virtual patients in response to the applied dialysis treatment simulation over the simulated time period;
• e) apply at least one adjusted simulated dialysis therapy to the plurality of virtual patients over the simulated time period based on the determined one or more physiological parameters of the plurality of virtual patients;
• f) determine an optimal simulated dialysis therapy from among the simulated dialysis therapy and the at least one adjusted simulated dialysis therapy by iteratively performing the following steps until the determined one or more physiological parameters in the plurality of virtual patients are within a desired range:
• applying the at least one adjusted simulated dialysis therapy to the plurality of virtual patients over the simulated time period based on the determined one or more physiological parameters of the plurality of virtual patients;
• and
• determining one or more physiological parameters in the plurality of virtual patients in response to the at least one adjusted simulated dialysis therapy over the simulated period of time;
• and
• g) recommend the optimal simulated therapy for application to a plurality of actual patients.