Enabling Faster, Better Medical Device Development and Evaluation with Modeling and Simulation Tina Morrison PhD

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1 Enabling Faster, Better Medical Device Development and Evaluation with Modeling and Simulation Tina Morrison PhD Office of Device Evaluation Center for Devices and Radiological Health U.S. Food and Drug Administration

2 Overview CDRH s Role in Public Health Advancing Regulatory Science with Modeling and Simulation Moving Forward: Computational Modeling at CDRH

3 What we do CDRH is responsible for regulating firms who manufacture, repackage, re-label, and/or import medical devices sold in the U.S.

4 CDRH Mission The mission of the Center for Devices and Radiological Health (CDRH) is to protect and promote the public health. We facilitate medical device innovation by advancing regulatory science, providing industry with predictable, consistent, transparent, and efficient regulatory pathways, and assuring consumer confidence in devices marketed in the U.S.

5 Safety and Effectiveness There is reasonable assurance that a device is safe when it can be determined, based upon valid scientific evidence, that the probable benefits to health from use of the device for its intended uses and conditions of use, when accompanied by adequate directions and warnings against unsafe use, outweigh any probable risks There is reasonable assurance that a device is effective when it can be determined, based upon valid scientific evidence, that in a significant portion of the target population, the use of the device for its intended uses and conditions of use, when accompanied by adequate directions for use and warnings against unsafe use, will provide clinically significant results.

6 Medical Device Evaluation Comprehensive evaluation of a marketing application for a therapeutic medical device typically includes valid scientific evidence from four types of models: animal, bench, computational, and human. Each model has its strengths and limitations for predicting clinical outcomes.

7 Models and Their Advantages *Computer modeling in medical devices, as compared to other industries, is nascent and is the one model with the most potential for refinement/improvement because the others are fairly mature.

8 Medical Device Evaluation CDRH believes that, when appropriate, the most balanced evaluation strategy includes scientific evidence from all four models.

9 Medical Device Development with Modeling and Simulation VIRTUAL PROTOTYPING The Total Product Life Cycle DESIGN IDEATION DESIGN OPTIMIZATION PREDICT SUCCESS? REDESIGNS PREDICT FAILURES? ROOT CAUSE

10 Current Uses of Modeling in Medical Device Applications Computational Solid Mechanics Stents / Heart Valve Frames / Occluders / Vena Cava Filters / Annuloplasty Rings / Dental Implants / Spine & Joint Implants / Bone Plates & Screws / Surgical Tools Determine the implant size in a device family that is expected to perform the worst under simulated in vivo conditions o Reduces the amount of physical testing o Calculate Safety Factors for static and cyclic loads Evaluate the effect of manufacturing tolerances Predicate Comparison Demonstrate a modification (e.g., dimensional) is minor and has minimal affect on performance

11 Current Uses of Modeling in Medical Device Applications Computational Fluid Dynamics Ventricular Assist Devices / Total Artificial Heart / Blood pumps / Heart Valves / Endovascular Grafts / Drug Eluting Devices Characterize the flow field by identifying regions of high shear stress, wall shear stress, or areas of low flow or flow stagnation o especially in regions that cannot be visualized on the bench Determine blood damage, thrombosis potential, and drug transport using fluid flow properties

12 Current Uses of Modeling in Medical Device Applications Computational Electromagnetism Passive and Active Cardiology Implants / Peripheral Implants / Joint and Spinal Implants / Deep Brain Stimulators / MR-guided Interventional Devices Simulate the radiofrequency energy absorbed by patients undergoing magnetic resonance imaging (MRI) o Especially worst-case conditions that cannot be replicated in an animal model and cannot be tested ethically in humans Radiofrequency-induced currents and heating of (external) devices for electrophysiological recordings Simulate the electric/magnetic field generated by a device during use to provide evidence of effectiveness

13 Current Uses of Modeling in Medical Device Applications Physiological Closed-Loop Controllers & Algorithms Anesthesiology Devices / Artificial Pancreas / Neurodiagnostic Tools Use the simulation as an alternative validation method to demonstrate device performance and robustness In silico simulation model (control algorithm) of diabetes replaces in vivo animal testing for evaluating artificial pancreas Signal modeling (EEG source localizing software) for brain activity analysis

14 Computational Thermal Mapping Ablation Devices Current Uses of Modeling in Medical Device Applications Determine the thermal field distributions generated by tissue ablation devices (e.g., High Intensity Ultrasound, radiofrequency) Assess potential damage to surrounding tissue, organs and bones

15 Some Challenges with current practice Reports typically (might) lack sufficient details for adequate assessment Analyses lack sensitivity and uncertainty analyses for crucial input parameters adequate validation to support the use of the modeling and simulation elicitation of the consequence of the computational model being incorrect In biomechanics, lack of complete understanding of the physiological loads, relevant device-tissue interactions, and variations in patient populations

16 Moving Forward: Modeling and Simulation at CDRH Initiatives Research Partnerships Guidance Future Directions

18 FDA Guidance 1. Reporting Computational Modeling Studies in Medical Device Regulatory Submissions (DRAFT) Main body discusses the purpose of computational modeling and simulation in regulatory submissions Main body presents recommendations for reporting different elements of the computational modeling study There are six subject matter appendices o Fluid & Mass Transport, Solid Mechanics, Electromagnetism, Control Loops, Thermal Transport, and Ultrasound DRAFT guidance is expected to be available for public comment summer 2013

20 Partnerships ASME V&V 40 Subcommittee of ASME V&V Committee More information in Track 11 (11-4) from 4:00-6:00 PM Charter: Provide procedures to standardize verification and validation (V&V) for computational modeling of medical devices Developing a general methodology for industry and academia for creating a V&V plan and to assess credibility of computational model in a particular context of use Subgroups working on general methodology, solid mechanics, fluid mechanics and some device specialties (e.g., cardiovascular, orthopedics)

21 DRAFT Credibility Strategy Risk Assessment Matrix Credibility Assessment Matrix

22 Upcoming FDA Public Workshop CDRH is leading the effort to make V&V40 applicable to regulatory submissions June 11-12, 2013 FDA will lead a workshop that will focus specifically on regulatory issues with computational modeling Day 1: Library of Models and Data Day 2: Strategy to Assess Credibility of Computational Modeling o [email protected] if you wish to participate

23 FDA Guidance 2. Strategy to Assess Credibility Computational Modeling Studies for Regulatory Submissions (DRAFT) Content is currently being drafted The strategy is intended to create a framework for determining the risk associated with using a computational model in a specific context of use to inform decision making and for determining how much V&V is necessary to support the model in that context of use. o Implement using the Pre-submission process

25 Initiatives The VPP Components of the Virtual Physiological Patient a) Develop computer models using radiological imaging data from healthy and diseased anatomy; b) Integrate with these models physiological, clinical and engineering data to promote development of complete physiological models and simulations that can be used in the development and evaluation of medical devices; and, c) create an open-source library of validated computer models and data easily accessible to industry developers, clinicians, and researchers.

26 Initiatives The VPP Components of the Virtual Physiological Patient 1. Virtual Human Heart Valves Ventricular Assist Devices 2. Complete Peripheral Vasculature Endovascular Grafts Stents 3. Bone Body Joint Replacements 4. Model Mind Neurosurgical Tools Revascularization Post-stroke M2S

27 Initiatives The VPP Library of Models and Data Components of the Virtual Physiological Patient Public compendium of anatomic and physiologic data A shared point of reference might improve understanding of the model attributes and limitations and will enable the model to evolve as data accumulates. Discrete computer models and simulations validated for regulatory evaluation Selective use of high value models will improve predictability and consistency in the regulatory review process. Peer-reviewed by experts in academia, government and industry Ensure robust verification and validation, including periodic assessment.

28 Research The VPP Rotor Design Tortuosity, Bending & Twisting Outlet Inlet

29 Partnerships The VPP

30 Partnerships MDIC

31 1 st ASME/FDA Frontiers in Medical Devices Applications of Computer Modeling and Simulation Call for Technical Papers and Posters September 11-13, 2103, Marriott Conference Center, University of Maryland Technical Papers and Posters will be presented in the following areas: The Role of Experiment in Modeling Computational Models as a Medical Device Consortium-Based Model Development and Validation How Good is Good Enough? Imaging in Modeling and Simulation Development Lessons From More Mature Industries (Aerospace, Automotive, etc.): How Did They Do It??? Novel Computational Methods Patient Specific Modeling Population Modeling Predictive Reliability Modeling Probabilistic Modeling Surgical Simulation Happy Hour in DC at the famous Get more information: Visit or contact Stephen Crane at [email protected]. Old Ebbitt Grill Visit the White House, the Capitol and numerous free museums The 2013 program is co-chaired by Walt Baxter of Medtronic, and by Donna Lochner of the FDA.

32 Future Directions Digital Patients Virtual Clinical Trials Personalized Medicine MDIC ACADEMIA NIH FDA CM NSF INDUSTRY MDIC Subcommittee on computational modeling NIST NASA DARPA

33 Enabling Faster, Better Medical Device Development and Evaluation via Modeling and Simulation: CDRH perspective Contact Information If you want to discuss how modeling and simulations fits into the device evaluation strategy for your product, your validation strategy to support your computational model, how to determine if your model/simulation is a medical device, or, if you want to get involved with ASME V&V 40 Send an to: [email protected] Office of Device Evaluation