Optimizing Device Interoperability Through Model-Based Systems Engineering

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Optimizing Device Interoperability Through Model-Based Systems Engineering Presenter: Brett Malone, Ph.D. Sept 8, 2011 Summary: This presentation focuses on applying the concepts of systems engineering to the modeling and simulation of medical devices and their critical system interfaces.

1 Optimizing Device Interoperability Through Model-Based Systems Engineering Presenter: Brett Malone, Ph.D. Sept 8, 2011 Summary: This presentation focuses on applying the concepts of systems engineering to the modeling and simulation of medical devices and their critical system interfaces. Device development is a multidisciplinary effort and the use of model-based analysis and simulation in the early stages of the design strategy allows clinicians and engineers to understand the risk, cost, and complexity of proposed systems. In particular the interfaces between components, subsystems, and ultimately patient and device are critical to define and optimize. This presentation describes the use of integrated functional analysis coupled with requirements for system interface design to improve the way complex clinical systems operate.

2 Overview Drivers and Opportunity Introduction to MBSE Application Areas Q&A

3 Summary in Advance Model-Based SE is a simple concept Use MBSE to understand risk earlier Simulating functionality highlights gaps A well documented model supports compliance efforts

4 Systems are More Complex Stakes Remain High Photo courtesy Thomas Group.

5 Drivers: R&D Performance Low success rate Costly process Compensation risk Regulatory hurdles

6 Financial Risk/Reward Opportunity and Risk

7 Safety QA/QC plan must address critical functions of the system

8 Partner/Vendor Risk Endpoints Represented by PM/REG Must be Consistent with SE Plan

9 Compliance Managing Regulatory Means Providing Insight, not Pushing Paper

10 How to IMPACT?

11 Overview of MBSE Model-Centric vs. Document Centric Relationships: Thoughtful Traceability Representations: Meaningful Output Simulation: Dynamic Decision Making

12 MBSE is a SIMPLE Concept Entities and relationships Start anywhere and iterate Documentation is output

13 Example CodeBlue: Wireless Sensors for Medical Care Accelerometer, gyroscope, and electromyogram (EMG) sensor for stroke patient monitoring.

14 Concept 1: Entity (Things, Objects, Items) ie. Sensor

15 Concept 2: Attributes Description of Entity properties ie. The sensor has a sensitivity and cost

16 Concept 3: Relationships Description of linkage (The sensor is built in the monitoring pod)

17 Build Value Models for Greater Insight

18 Model-Based Methodology Decompose Requirements Define Behavior Define Architecture Design Verification and Validation Execute Trade Studies

The Power of the Centralized Model Requirements Management Behavioral Analysis Architecture Synthesis Verification Data Data Data Data Source

19 The Power of the Centralized Model Requirements Management Behavioral Analysis Architecture Synthesis Verification Data Data Data Data Source Material Data Design Specifications, DoDAF, SysML Data views Integrated, Consistent Analysis: Complete Specifications, Project Documentation, Queries & Models

20 Approach Integrates Domains Source Requirements Domain Originating requirements trace to behavior Behavior Domain Data Data verified by V&V Domain Data System Engineering Repository Data Behavior is allocated to physical components Architecture Domain Data verified by verified by Originating requirements trace to physical components

21 Compliance documents are automatically generated based on the data in the repository.

22 Value of Methodology Formal system specifications Comprehensive risk analysis Trade studies captured as part of the model Single repository for maintenance Versioning records and database metrics Work Products are by-products of the disciplined approach employed by the R&D team. Focus on design and insight, not document production

23 Application Areas Devices Software and Informatics Companion Diagnostics Regulatory Planning Healthcare Processes

24 Devices Requirements Engineering Cost analysis Regulatory Planning GMP / QA-QC / ISO Vendor/supplier Management

low cost functional assay SE Solution: Proper function decomposition and modeling analysis

25 Example: Companion Diagnostics Biomarkers are emerging as key for personalized medicine Opportunity: Targeted therapies deliver higher efficacy in patient populations Issue: Develop low cost functional assay SE Solution: Proper function decomposition and modeling analysis pipeline Impact: Effective analysis software coupled with exiting data sources lead to innovative signatures

26 Example: Computational Toxicity Opportunity: Use biomarkers for early detection of toxicity exposure for screening and drug development. Issue: Develop functionally accurate models for gene signatures. SE Solution: Leverage existing datasets from microarray and proteomics. Impact: Reduce $6b in testing to $500M

27 System Modeling for Computational Toxicity

28 Requirements Development

29 Simulation

30 Applications Risk Simulation reveals risks and weaknesses Mitigation plans now feed program element Mitigation: New Threshold Fail Pass Cost of mitigation plans are tracked

31 Summary Model-Based SE is a simple concept Use MBSE to understand risk earlier Simulating functionality highlights gaps A well documented model supports compliance efforts

32 About Vitech Model Based Systems Engineering (MBSE) solutions Successfully delivering MBSE products and services to military and government agencies, private and public businesses, Fortune 500 firms and universities across the globe since Software and Support Professional Engineering Services Model-Based System Engineering Training Research and Development

33 Continue the Conversation Join us at community.vitechcorp.com to continue the conversation. In the MBSE part of the forum you ll find a topic for discussions related to this webinar.

34 Brief Title - 34

NDIA Test and Evaluation Conference

NDIA Test and Evaluation Conference Model Based Systems Engineering (MBSE) and Modeling and Simulation (M&S) adding value to Test and Evaluation (T&E) March 16, 2011 Larry Grello High Performance Technologies,