Human metabolic condition management

1. A method comprising:

receiving, at a computing device comprising a processor, an indication of a food; a medication, or a combination of food and medication to be ingested by a user;

identifying, by the computing device, a metabolic rate for the food, the medication, or the combination of food and medication to be ingested;

formulating, by the computing device, a model for predicting a metabolite level change based on the metabolic rate for the food, the medication, or the combination of food and medication to be ingested, the model including variables corresponding to the food, the medication, or the combination of food and medication to be ingested;

validating the model against a subsample of temporal data not used to formulate the model;

storing the model on a data storage device;

receiving, at the computing device, a behavior input from a user, the behavior input including an indication of an ingestion of the food, the medication, or the combination of food and medication to be ingested;

determining, by the computing device, a metabolite level change based at least in part on the model;

selecting, by the computing device, a recommended behavior;

outputting the recommended behavior to a display associated with the computing device; and

performing the recommended behavior by the user.

2. The method of claim 1 , wherein the metabolic rate for the food, the medication, or the combination of food and medication to be ingested includes an absolute value for glucose.

3. The method of claim 1 , wherein the metabolic rate for the food, the medication, or the combination of food and medication to be ingested includes an increase in a blood glucose level.

4. The method of claim 1 , wherein the metabolic rate for the food, the medication, or the combination of food and medication to be ingested includes a decrease in a blood glucose level.

5. The method of claim 1 , wherein the temporal data includes exercise activities engaged in by the user that result in a change in a blood glucose level.

6. The method of claim 1 , wherein the temporal data includes the metabolite levels recorded over a time interval.

7. The method of claim 1 , wherein the model is formulated according to at least one of a statistical analysis, a Monte Carlo simulation, a single variable regression analysis, and a multivariable regression analysis.

8. The method of claim 1 , wherein receiving the temporal data includes receiving updated temporal data, the method further comprising:

identifying an updated metabolic rate based on metabolite levels extracted from the updated temporal data; and

wherein validating the model includes validating the model against the updated metabolic rate.

9. The method of claim 8 , further comprising formulating a new model when the model does not validate against the updated metabolic rate.

10. The method of claim 1 , wherein the recommended behavior includes two or more coupled metabolic effects.

11. A system comprising:

a display;

a processor in electrical communication with the display; and

a memory that store instructions that, when executed by the processor, cause the processor to perform operations comprising:

receiving an indication of a food, a medication, or a combination of food and medication to be ingested by a user,

identifying a metabolic rate for the food, the medication, or the combination of food and medication to be ingested,

formulating a model for predicting a metabolite level change based on the metabolic rate for the food, the medication, or the combination of food and medication to be ingested, the model including variables corresponding to the food, the medication, or the combination of food and medication to be ingested,

validating the model against a subsample of temporal data not used to formulate the model,

storing, to the memory, the model,

receiving a behavior input from a user, the behavior input including an indication of an ingestion of the food, the medication, or the combination of food and medication to be ingested,

determining a metabolite level change based at least in part on the model,

selecting a recommended behavior,

outputting the recommended behavior to a display associated with the computing device, and

receiving an indication the user accepted the recommendation.

12. The system of claim 1 , wherein the metabolic rate for the food, the medication, or the combination of food and medication to be ingested includes an absolute value for glucose and an increase in a blood glucose level.

13. The system of claim 11 , wherein the metabolic rate for the food, the medication, or the combination of food and medication to be ingested includes a decrease in a blood glucose level.

14. The system of claim 11 , wherein the temporal data includes exercise activities engaged in by the user that result in a change in a blood glucose level.

15. The system of claim 11 , wherein the temporal data includes the metabolite levels recorded over a time interval.

16. The system of claim 11 , wherein the model is formulated according to at least one of a statistical analysis, a Monte Carlo simulation, a single variable regression analysis, and a multivariable regression analysis.

17. The system of claim 11 , wherein receiving the temporal data includes receiving updated temporal data, the method further comprising:

identifying an updated metabolic rate based on metabolite levels extracted from the updated temporal data; and

wherein validating the model includes validating the model against the updated metabolic rate.

18. The system of claim 17 , further comprising formulating anew model when the model does not validate against the updated metabolic rate.

19. The system of claim 11 , wherein the recommended behavior includes two or more coupled metabolic effects.

20. The system of claim 11 , wherein the system is one of a blood glucose meter, an infusion pump, and a smartphone.