System, method and computer simulation environment for in silico trials in pre-diabetes and type 2 diabetes

• US 11,238,990 B2
• Filed: 06/25/2010
• Issued: 02/01/2022
• Est. Priority Date: 06/26/2009
• Status: Active Grant

• Current Assignee: University of Virginia Patent Foundation (University of Virginia)
• Original Assignee: University of Virginia Patent Foundation (University of Virginia)
• Inventors: Kovatchev, Boris P., Cobelli, Claudio, Dalla Man, Chiara
• Primary Examiner(s): Clow, Lori A.
• Assistant Examiner(s): Archer, Marie
• Application Number:
  US13/380,839
• Publication Number:
  US 20120130698A1
• Time in Patent Office: 4,239 Days
• CPC Class Codes: A61B 5/4842 Monitoring progression or stage of a disease
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G06N 5/00 Computing arrangements using knowledge-based models
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

An electronic system is provided that simulates a glucose-insulin metabolic system of a T2DM or prediabetic subject, wherein the system includes a subsystem that models dynamic glucose concentration in a T2DM or prediabetic subject, including an electronic module that models endogenous glucose production (EGP(t)), or meal glucose rate of appearance (Ra(t>>, or glucose utilization (U(t)), or renal excretion of glucose (B(t)), a subsystem that models dynamic insulin concentration in said T2DM or prediabetic subject, including an electronic module that models insulin secretion (S(t)), an electronic database containing a population of virtual T2DM or prediabetic subjects, each virtual subject having a plurality of metabolic parameters, and a processing module that calculates an effect of variation of at least one metabolic parameter value on the glucose insulin metabolic system of a virtual subject by inputting the plurality of metabolic parameter values.

Claims

1. An electronic system that simulates a glucose-insulin metabolic system of a T2DM or prediabetic subject, comprising:

a subsystem that models dynamic glucose concentration in a T2DM or prediabetic subject, including;

an electronic module that models endogenous glucose production (EGP(t)) of a T2DM or prediabetic subject,

an electronic module that models meal glucose rate of appearance (Ra(t)) of a T2DM or prediabetic subject,

an electronic module that models glucose utilization (U(t)) of a T2DM or prediabetic subject,

an electronic module that models renal excretion of glucose (E(t)) of a T2DM or prediabetic subject;

a subsystem that models dynamic insulin concentration in said T2DM or prediabetic subject, including;

an electronic module that models insulin secretion (S(t)) of a T2DM or prediabetic subject;

an electronic database containing a population of virtual T2DM or prediabetic subjects representative of the T2DM and prediabetic population, each virtual subject having a plurality of metabolic parameters with values encompassing a distribution of parameters observed in vivo across the population of T2DM or prediabetic subjects; and

a processor that calculates an effect of variation of at least one metabolic parameter value on the glucose-insulin metabolic system of a virtual T2DM or prediabetic subject by inputting said plurality of metabolic parameter values of said T2DM or prediabetic subject into said glucose concentration and insulin concentration subsystems and varying at least one of said metabolic parameter values to determine its effect on the glucose-insulin metabolic system of said T2DM or prediabetic subject.

2. An electronic system as set forth in claim 1, wherein said glucose concentration subsystem models T2DM or prediabetic glucose concentration G(t) in accordance with the following equations:

3. An electronic system as set forth in claim 2, wherein said EGP electronic module models EGP(t) according to the equation:

EGP(t)=k_p1−

k_p2−

G_p(t)−

k_p3·

I_d(t)−

k_p4·

_po(t) EGP(0)=EGP_b.

4. An electronic system as set forth in claim 3, wherein i_d(pmol/l) is a delayed insulin signal realized with a chain of two compartments:

5. An electronic system as set forth in claim 3, wherein at basal steady state

k_p1=EGP_b+k_p2·

G_pb+k_p3·

I_b+k_p4·

I_pob.

6. An electronic system as set forth in claim 2, wherein said glucose rate of appearance electronic module models Ra(t) according to the equations:

7. An electronic system as set forth in claim 2, wherein said glucose utilization electronic module models U(t) as the sum of insulin-independent utilization U_ii(t)=F_cns, and insulin-dependent utilization

8. An electronic system as set forth in claim 7, wherein Vm(X(t)) is assumed to be linearly dependent from a remote insulin, X(t):

V_m(X(t))=V_m0+V_mx·

X(t).

9. An electronic system as set forth in claim 8, wherein X (pmol/L) is insulin in the interstitial fluid described by:

{dot over (X)}(t)=−

p_2U·

X(t)+p_2U[I(t)−

I_b] X(0)=0.

10. An electronic system as set forth in claim 2, wherein said renal excretion electronic module models renal excretion of glucose E(t) as:

11. An electronic system as set forth in claim 1, wherein said insulin concentration subsystem models T2DM or prediabetic insulin concentration I(t) in accordance with the following equations:

12. An electronic system as set forth in claim 11, wherein said insulin secretion electronic module models insulin secretion S(t) as:

S(t)=γ

·

I_po(t), wherein

13. An electronic system as set forth in claim 1, wherein a prediabetic subject is a subject with impaired fasting glucose (IFG).

14. An electronic system as set forth in claim 1, wherein a prediabetic subject is a subject with impaired glucose tolerance (IGT).

15. An electronic system as set forth in claim 1, wherein said plurality of metabolic parameters for each virtual subject includes at least one of the following parameters:

k_abs=rate constant of glucose absorption by the intestine,

k_max=maximum rate constant of gastric emptying,

k_min=minimum rate constant of gastric emptying,

b=percentage of the dose for which k_empt decreases at (k_max−

k_min)/2,

c=percentage of the dose for which k_empt is back to (k_max−

k_min)/2,

k_i=rate parameter accounting for delay between insulin signal and insulin action on the liver,

k_p2=liver glucose effectiveness,

k_p3=parameter governing amplitude of insulin action on the liver,

k_g=parameter governing amplitude of portal insulin action on the liver,

V_g=distribution volume of glucose,

V_mx=parameter governing amplitude of insulin action on glucose utilization,

k_m0=parameter governing glucose control on glucose utilization,

K₂=rate parameter accounting for glucose transit from tissue to plasma,

K₁=rate parameter accounting for glucose transit from plasma to tissue,

p_2U=rate parameter accounting for delay between insulin signal and insulin action on glucose utilization,

V_i=distribution volume of insulin,

K=beta-cell responsivity to glucose rate of change,

β

=beta-cell responsivity to glucose level,

α

=rate parameter accounting for delay between glucose signal and insulin secretion,

m₁=rate parameter of insulin kinetics,

m_s=coefficient linking insulin hepatic extraction to insulin secretion rate,

G_b=basal plasma glucose concentration,

EGP_b=basal endogenous glucose production,

BW=body weight,

I_b=basal plasma insulin concentration, and

SR_b=basal insulin secretion rate.

16. An electronic system as set forth in claim 1, wherein said subsystems and modules are implemented as computer-executable software stored on a computer-readable storage medium and loaded into an electronic programmable computer.

17. An electronic system as set forth in claim 1, wherein said subsystems and modules are implemented as application specific integrated circuit modules.

18. A computer-executable program product comprising computer executable code stored in a non-transitory computer-readable storage medium, wherein said computer-executable program product simulates a glucose-insulin metabolic system of a T2DM or prediabetic subject, said computer-executable code comprising:

subsystem code that models dynamic glucose concentration in a T2DM or prediabetic subject, including;

an electronic code module that models endogenous glucose production (EGP(t)) of a T2DM or prediabetic subject,

an electronic code module that models meal glucose rate of appearance (Ra(t)) of a T2DM or prediabetic subject,

an electronic code module that models glucose utilization (U(t)) of a T2DM or prediabetic subject,

an electronic code module that models renal excretion of glucose (E(t)) of a T2DM or prediabetic subject;

subsystem code that models dynamic insulin concentration in said T2DM or prediabetic subject, including;

an electronic code module that models insulin secretion (S(t)) of a T2DM or prediabetic subject;

an electronic database containing a population of virtual T2DM or prediabetic subjects representative of the T2DM and prediabetic population, each virtual subject having a plurality of metabolic parameters with values encompassing a distribution of parameters observed in vivo across the population of T2DM or prediabetic subjects; and

computer-executable code that calculates an effect of variation of at least one metabolic parameter value on the glucose-insulin metabolic system of a virtual T2DM or prediabetic subject by inputting said plurality of metabolic parameter values of said T2DM or prediabetic subject into said glucose concentration and insulin concentration subsystems and varying at least one of said metabolic parameter values to determine its effect on the glucose-insulin metabolic system of said T2DM or prediabetic subject.

19. A computer-executable program product as set forth in claim 18, wherein said glucose concentration subsystem code models T2DM or prediabetic glucose concentration G(t) in accordance with the following equations:

20. A computer-executable program product as set forth in claim 19, wherein said EGP code module models EGP(t) according to the equation:

EGP(t)=k_p1−

k_p2·

G_p(t)−

k_p3·

I_d(t)−

k_p4·

I_po(t)EGP(0)=EGP_b.

21. A computer-executable program product as set forth in claim 20, wherein I_d (pmol/l) is a delayed insulin signal realized with a chain of two compartments:

22. A computer-executable program product as set forth in claim 20, wherein at basal steady state

k_p1=EGP_b+k_p2·

G_pb+k_p3·

I_b+k_p4·

I_pob.

23. A computer-executable program product as set forth in claim 19, wherein said glucose rate of appearance code module models Ra(t) according to the equations:

24. A computer-executable program product as set forth in claim 19, wherein said glucose utilization code module models U(t) as the sum of insulin-independent utilization U_ii(t)=F_cns, and insulin-dependent utilization

25. A computer-executable program product as set forth in claim 24, wherein Vm(X(t)) is assumed to be linearly dependent from a remote insulin, X(t):

V_m(X(t))=V_m0+V_mx·

X(t).

26. A computer-executable program product as set forth in claim 25, wherein X (pmol/L) is insulin in the interstitial fluid described by:

{dot over (X)}((t)=−

p_2U·

X(t)+p_2U[I(t)−

I_b] X(0)=0.

27. A computer-executable program product as set forth in claim 18, wherein said renal excretion code module models renal excretion of glucose E(t) as:

28. A computer-executable program product as set forth in claim 18, wherein said insulin concentration subsystem code models T2DM or prediabetic insulin concentration I(t) in accordance with the following equations:

29. A computer-executable program product as set forth in claim 28, wherein said insulin secretion code module models insulin secretion S(t) as:

S(t)=γ

·

I_po(t), wherein

30. A computer-executable program product as set forth in claim 18, wherein a prediabetic subject is a subject with impaired fasting glucose (IFG).

31. A computer-executable program product as set forth in claim 18, wherein a prediabetic subject is a subject with impaired glucose tolerance (IGT).

32. A computer-executable program product as set forth in claim 18, wherein said plurality of metabolic parameters for each virtual subject includes at least one of the following parameters:

k_abs=rate constant of glucose absorption by the intestine,

k_max=maximum rate constant of gastric emptying,

k_min=minimum rate constant of gastric emptying,

b=percentage of the dose for which k_empt decreases at (k_max−

k_min)/2,

c=percentage of the dose for which k_empt is back to (k_max−

k_min)/2,

k_i=rate parameter accounting for delay between insulin signal and insulin action on the liver,

k_p2=liver glucose effectiveness,

k_p3=parameter governing amplitude of insulin action on the liver,

k_p4=parameter governing amplitude of portal insulin action on the liver,

V_g=distribution volume of glucose,

V_mx=parameter governing amplitude of insulin action on glucose utilization,

k_m0=parameter governing glucose control on glucose utilization,

K₂=rate parameter accounting for glucose transit from tissue to plasma,

K₁=rate parameter accounting for glucose transit from plasma to tissue,

p_2U=rate parameter accounting for delay between insulin signal and insulin action on glucose utilization,

V_i=distribution volume of insulin,

K=beta-cell responsivity to glucose rate of change,

β

=beta-cell responsivity to glucose level,

α

=rate parameter accounting for delay between glucose signal and insulin secretion,

m₁=rate parameter of insulin kinetics,

m_s=coefficient linking insulin hepatic extraction to insulin secretion rate,

G_b=basal plasma glucose concentration,

EGP_b=basal endogenous glucose production,

BW=body weight,

I_b=basal plasma insulin concentration, and

SR_b=basal insulin secretion rate.