A Virtual Glucose Homeostasis Model for Verification, Simulation and Clinical Trials

Transcription

1 A Virtual Glucose Homeostasis Model for Verification, Simulation and Clinical Trials Neeraj Kumar Singh INPT-ENSEEIHT/IRIT University of Toulouse, France September 14, 2016 Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

2 Outline 1 Critical Systems 2 Context and Problems 3 Glucose Homeostasis Models 4 Formalization of GH 5 GH Simulator Framework 6 Hardware Implementation of GH 7 Conclusion & Future Work Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

3 Critical Systems Definition A system whose failure may result in injury, loss of life, economical loss or serious environmental damage. These systems require interaction between computational and physical elements. Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

4 System Failures System Failures Therac-25 ( ): six people overexposed to radiation. Pacemaker and ICD ( ): 17,323 pacemakers and ICDs were explanted that includes 61 deaths. Insulin Infusion Pump (IIP) (2010): 5000 adverse events that includes 30 deaths. Missing Malaysian Plane MH370 (8 March, 2014): Unknown. Satellite Failure:+150: Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

5 Context and Problems Context Development of virtual model for verification, simulation and clinical trials that can be used in the development process of medical devices. Current Challenges Increasing complexity of the critical medical systems. Lack of biological simulation/environment for medical devices. Better techniques for requirement analysis. Needs some sound techniques to meet regulators, and certification standards. Modelling critical medical systems using human-in-loop architecture. Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

6 Insulin Infusion Pump Insulin Infusion Pump An insulin pump is a small, complex, software-intensive medical device that allows controllable, continuous subcutaneous infusion of insulin to patients. Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

7 IIP Requirements REQ1: The device must undergo a power-on-self-test (POST) whenever device power is turned on. REQ2: The device must suspend all active basal delivery or bolus deliver during pump refilling and in the case of system failure. REQ3: The device shall allow the user to manage system functionalities related to: stopping insulin delivery; validating basal profiles parameters; reminder management; and validating bolus preset parameters. REQ4: The device shall allow the user to define a basal profile that consists of an ordered set of basal rates, ordered over a 24 hour day, as well as a temporary basal, that consists of a basal rate for a specified duration of time within a 24 hour day. REQ5: The device can contain several basal profiles, but only one basal profile can be active at any single point in time. REQ6: The device must allow the user to override an active basal profile with a temporary basal, without changing the existing basal profile. REQ7: The device shall resume the active basal profile after the temporary basal terminates. Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

8 IIP Requirements REQ8: The device shall enforce a maximum dosage for the normal bolus or extended bolus. REQ9: The user shall be able to stop the active normal or extended bolus. REQ10: The device must maintain an electronic log of every operation associated with an user alert, such as an audio alarm. REQ11: The device shall maintain a history of basal and bolus dosages over the past n days. n always differs among brands, though most store up to 90 days of data. REQ12: The device shall enable the user to create a food database that can be used to store food or meal descriptions and the carbs associated with them. REQ13: The device shall allow to the user to change parameter settings of basal profile, bolus preset, and temporary basal. REQ14: The device shall provide feedback to the user regarding system and delivery status. Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

9 Objectives To identify gaps or inconsistencies in the IIP requirements. Developing a closed-loop model for verification and validation of IIP. Analysing system interaction between the GH model and IIP. Developing a simulation model from the formal virtual GH model. Developing a test bench using the virtual GH model and simulation for clinical trials of IIPs. Generating test cases to test the functional correctness of IIP software. Developing patient specific model at various level of system development. The virtual environment model can be used by medical industries during the product development. The virtual GH environment model can be used by regulators for validating and certifying the medical devices. Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

10 Glucose Homeostasis Models Clinical Models Models for diagnostic tests control progression complications Non-Clinical Models Models for insulin-glucose, hepatic glucose, glucagon, and insulin receptor dynamics beta-cell insulin release brain glucose homeostasis Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

11 Glucose Homeostasis Models Use of the Models To present a simulation of the glucose homeostasis system to understand the actual behavior. To assist the medical experts for simulation purpose of the glucose dynamics. Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

12 Glucose Homeostasis Models Use of the Models To present a simulation of the glucose homeostasis system to understand the actual behavior. To assist the medical experts for simulation purpose of the glucose dynamics. Disadvantages Existing models are based on complex mathematics, therefore these models are difficult and make simulation very time-consuming. are not suitable for presenting an abstract behavior of GH. are not suitable for verification purpose. Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

13 Glucose Homeostasis System HighCPlasmaC GlucoseCLevel NormalCGlucoseC LevelCMaintainedC LowCPlasmaC GlucoseCLevel GlucoseC LevelCDrops GlucoseC LevelCRises GlucoseCUtilizationC andcstoragecincliverc ascglycogen β-cells Pancreas α-cells LiverCConvertsC GlycogenCtoC Glucose Insulin Release Glucagon Release Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

14 Glucose Homeostasis Automata Glucose Level Drops Hi No Lo Glucose Level Rises St Bc Ac Tr Insulin Release Glucagon Release Li Figure: The Glucose Homeostasis Automata Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

15 The Glucose Homeostasis Definition Definition 1 (The Glucose Homeostasis System) Given a set of nodes N, a transition T is a pair (i, j), with i, j N. A transition is denoted by i j. The glucose homeostasis system is a tuple GHS = (N, T, N 0 ) where: N = { Hi, No, Lo, Ac, Bc, Li, St, Tr } is a finite set of landmark nodes in the glucose homeostasis network; T N N = {No Hi, Hi No, No Lo, Lo No, Hi Hi, No No, Lo Lo, Hi Bc, Lo Ac, Bc Li, Ac Li, Li St, Li Tr, St No, Tr No, St Hi, Tr Lo, Tr Hi} is a set of transitions to present data flow between two landmark nodes; N 0 = No is the initial landmark node (normal glucose level); Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

16 Abnormal Glucose Homeostasis System Hyperglyoemia-induced DiabetesbComplications HighbPlasmab GlucosebLevel NormalbGlucoseb LevelbMaintainedb LowbPlasmab GlucosebLevel Persistent HighbPlasmab GlucosebLevel Persistent LowbPlasmab GlucosebLevel Persistent HighbPlasmab GlucosebLevel InsulinbResistance inbcellsb Beta-CellsbDefect; Insufficientborbno InsulinbSecretion β-cells Pancreas α-cells Insufficientborb nobglucagonb Secretion ExcessbInsulinb orbextreamb Exercise Excessb Glucagonb Secretion Insulin Release Alpha-CellsbDefect; Abnormalb GlucagonbRelease Figure: Abnormal Glucose Homeostasis System Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

17 Blood Glucose Level Property 1 (Blood Glucose Level) The blood glucose level defines different stages, such as hyper- glycemia, hypoglycemia and normal. The glucose level is low (hypoglycemia) if FPG [0,70) or OGTT [0,70), and the glucose level is high (hyperglycemia) if FPG 125 or OGTT 200, and the glucose level is normal if FPG [70,100) or OGTT [70,140). We classify pre-diabetes to be the range where FPG [100,125) or OGTT [140,200). Blood Sugar Level Fasting Plasma Glucose (FPG) Oral Glucose Tolerance Test (mg/dl) (mg/dl) Normal Pre-Diabetes High glucose 126 or above 200 or above Low glucose Table: FPG and OGTT Test Values for Glucose Level Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

18 Abstract Model Context axm1 : Glucose level, {Normal}, {High}, {Low}) axm2 : partition(ghs, {OK}, {KO}) Hi No Lo Figure: Automata of an Abstract Model Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

19 Abstract Machine inv1 : Current Glucose Level Glucose level inv2 : Diabetic Condition GHS inv3 : Diabetic Condition = KO Current Glucose Level = High Current Glucose Level = Low inv4 : Current Glucose Level = Normal Diabetic Condition = OK EVENT Normal Glucose WHEN grd1 : Current Glucose Level = Normal Current Glucose Level = Low Current Glucose Level = High THEN act1 : Current Glucose Level := Normal act2 : Diabetic Condition := OK END Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

20 Abstract Machine EVENT High Glucose WHEN grd1 : Current Glucose Level = Normal Current Glucose Level = High THEN act1 : Current Glucose Level := High act2 : Diabetic Condition := KO END EVENT Low Glucose WHEN grd1 : Current Glucose Level = Normal Current Glucose Level = Low THEN act1 : Current Glucose Level := Low act2 : Diabetic Condition := KO END N. K. Singh, Hao Wang, Mark Lawford, Thomas S. E. Maibaum, and Alan Wassyng Formalizing the Glucose Homeostasis Mechanism, 16th International Conference on Human-Computer Interaction (HCI 2014), LNCS, Springer International Publishing, pp , Vol-8529, Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

21 Progressive Refinements Refinement Gradually introduce details and complexity to the specification by removing non-determinism and by adding more events. Refinement 1 : To introduce the α-cells and β-cells of Pancreas including their releasing functions and defects. Refinement 2 : To define the liver behaviour for converting or storing the glucose in the body. Refinement 3 : To add the abnormal conditions of Pancreas, diabetic conditions, and diabetes complications. Refinement 4 : To introduce the Blood Sugar Concentration for assessing the Diabetes and Pre-diabetes. Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

22 GH Simulator Framework Modeling Tools and Computation Tools Finite elements, Finite differences, Lumped elements, etc. Physiology of GH Physiology of the Pancreas Formal Specification of GH Physiology of the Liver Insulin-glucose Dynamics Glucagon-glucose Dynamics Simulation Kernel User Interface and Visualization of GH GH Abnormality Physiology of pancreatic alpha-cells and beta-cell Required Parameters Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

23 Hardware Implementation of GH Hardware Platform FPGA, Arduino, Snickerdoodle, etc Formal Specification of GH GH Simulation Modeling and Implementation of GH Model Matlab or LabVIEW User Interface and Visualization of GH Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

24 Usage Scenarios of Environment Model Behavioural Requirements To Discover Essential Safety Properties Patient Safety in Closed-loop To Generate Automatic Test Cases Test Bench for Clinical Trials of IIPs Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

25 Conclusion & Future Work Conclusion Logic based mathematical modelling of the GH (Normal and Abnormal) Developed a stepwise formal model of GH environment model Applying model checking and theorem prover to prove safety properties. Proposed Simulation framework Proposed Hardware Implementation framework To meet the V&V requirements of certification standards like FDA etc. Future Work Integration of GH model and IIP for developing the closed-loop model Development of GH simulator Test bench for IIPs through developing the hardware platform of GH Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25

26 Neeraj Kumar Singh A Perspective on Environment Modelling September 14, / 25