and simulation initiatives at cdrh - amazon s3 · 7 fda has identified an important role for...

Presented by the ORS Industry Engagement Committee

FDA: Modeling and Simulation Initiatives at CDRH

Tina Morrison, PhDFDA/CDRH

Chris Roche, MSE, MBAExactechORS Industry Engagement Committee Member

Speaker: Moderator:

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Modeling and Simulation Initiatives at CDRH

Tina Morrison, PhDFDA/CDRHDeputy DirectorDivision of Applied Mechanics, Office of Science and Engineering Laboratories


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FDA PROTECTS AND PROMOTES PUBLIC HEALTH


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Ways FDA Accomplishes its Mission

• New product review and pre‐market approval/clearance• Monitor

– Safe manufacturing– Safe handling– New risks

• Enforcement and Compliance• Research

– Guiding working principle is that we make sound science‐based decision making


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FDA also Advances Public Health

• Help speed innovations that make products safer, more effective, and more affordable

• Help the public get accurate, science based information about the products we regulate– The key for FDA is regulatory science

Regulatory science is the science of developing new tools, standards, and approaches to assess the safety, efficacy, quality, and performance of FDA‐regulate products.

http://www.fda.gov/AboutFDA/CentersOffices/OfficeofMedicalProductsandTobacco/CDRH/CDRHReports/ucm274152.htm

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FDA’s Strategic Plan for Regulatory Science

Of the 8 science priority areas, 4 have a specific call for M&S1. Modernize Toxicology to Enhance Safety

2. Stimulate Innovation in Clinical Evaluations and Personalized Medicine to Improve Product Development and Patient Outcomes

4. Ensure FDA Readiness to Evaluate Innovative Emerging Technologies

5. Harness Diverse Data through Information Sciences to Improve Health Outcomes

FDA has identified an important role for modeling and simulation (in silico methods) in its strategic priorities.

http://www.fda.gov/downloads/ScienceResearch/SpecialTopics/RegulatoryScience/UCM268225.pdf

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FDA has identified an important role for modeling and simulation (in silico methods) in its strategic priorities.

Proposed Methods/Approaches• (Q)SARmodels to predict human risk• Computer models of cells, organs, and systems

to better predict product safety and efficacy• Virtual physiologic patients for testing medical

products• Clinical trial simulations that reveal

interactions between therapeutic effects, patient characteristics, and disease variables

• Knowledge building tools: data mining, visualization, knowledge bases,high throughput methods

• Mechanism for sharing and reuse of data/models/algorithms

Virtual Population – IT’IS Foundationhigh‐end virtual models, digital phantoms, for in silico biomedical applications

FDA’s Strategic Plan for Regulatory Science

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FDA Centers

CBER: Center for Biologics Evaluation and ResearchCDER: Center for Drug Evaluation and ResearchCDRH: Center for Devices and Radiological HealthCFSAN: Center for Food Safety and Applied NutritionCTP: Center for Tobacco ProductsCVM: Center for Veterinary MedicineNCTR: National Center for Toxicological Research

OC: Office of the CommissionerORA: Office of Regulatory Affairs

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CDRH Organization

Office of the Center Director

Jeffrey Shuren, MD, JDOffice of In Vitro Diagnostic and Radiation Health

Office of Surveillance and Biometrics

Office of Compliance

Office of Communication and Education

Office of Management Operations

Office of Science and Engineering Laboratories

Office of Device Evaluation

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Center for Devices and Radiological Health

“The mission of CDRH is to protect and promotethe public health. …We facilitate medicaldevice innovation by advancing regulatoryscience, providing industry with predictable, consistent,transparent, and efficient regulatory pathways, andassuring consumer confidence in devicesmarketed in the U.S.”

FY2017Big DataBiocompatibilityReal‐World EvidenceClinical Trial DesignComputational ModelingDigital Health and CybersecurityInfection ControlPatient InputPredicting Clinical Performance Precision Medicine and BiomarkersCDRH

Regulatory Science Priorities

http://www.fda.gov/downloads/MedicalDevices/ScienceandResearch/UCM521503.pdf

Donaldson

padtinc.com

diabetesforecast.org

Heartflow

HaddadSimonyan

Iacono

of anatomy

to predict treatment effects

is the device

of physiology

M&S

PathmanathanMedical Devices

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M&S as a medical Device

heartflow.com

M&S is the medical device

e.g., clinical decision support

Heartflow.com

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M&S as scientific evidence

Kelm, Int J of Med Sci 2009Bluestein, PLOS ‐ 2012

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Medical Device Evaluation

Comprehensive evaluation of a premarket submission for a therapeutic medical device is typically supported by a combination of valid scientific evidence from four types of models: animal, bench, computational, and human.

Because each model has different strengths and limitations for predicting real‐world clinical outcomes, the data portfolio for different use‐conditions will vary.


16Morrison T.M., et al., The Role of Computational Modeling and Simulation in the Total Product Life Cycle of Peripheral Vascular Devices, accepted J Med Dev, in press in 2017

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M&S Disciplines @ CDRH

• Control Systems

• Electromagnetics and Optics

• Fluid Dynamics and Mass Transport

• Heat Transfer

• Physiology

• Solid Mechanics

• Ultrasound and X-ray


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Different PerspectivesSome CDRH scientists develop M&S for regulatory science and decision‐making

Some scientists review M&S submitted to CDRH in regulatory submissions

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Computational Solid MechanicsStents / Heart Valve Frames / Occluders / Vena Cava Filters / AnnuloplastyRings / 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 testingo 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

Current Uses of Modeling in Medical Device Applications

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Computational Fluid DynamicsVentricular 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


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Computational ElectromagnetismPassive 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


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Physiological Closed‐Loop Controllers & AlgorithmsAnesthesiology 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


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Computational Thermal MappingAblation Devices

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


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Orthopaedic Standards with FEA

ASTM F2996 – 13: Standard Practice for Finite Element Analysis (FEA) of Non‐Modular Metallic Orthopaedic Hip Femoral Stems

Recognized in 2014 by FDA: https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfstandards/detail.cfm?standard__identification_no=32390

ASTM F3161 – 16: Standard Test Method for Finite Element Analysis (FEA) of Metallic Orthopaedic Total Knee Femoral Components under Closing Conditions

FDA recognized in June 2016: https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfstandards/detail.cfm?standard__identification_no=34076

Technical Expert: [email protected]


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CDRH’s Role in Advancing M&S

• Need better communication of M&S studies

• Need continued research to address scientific challenges

• Need frameworks and approaches for determining the level of evidence needed to support M&S

ApplicabilityFramework

FDA Guidance Medical

DeviceDevelopment

Tools

MedicalDevice

InnovationConsortium

ASME V&V40

OSELResearch

To advance the use and increase the acceptance of M&S for regulatory decision making …


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MEDICAL DEVICE INNOVATION CONSORTIUM



DeviceDevelopment

Tools

MedicalDevice


ASME V&V40

OSELResearch

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Medical Device Innovation Consortium

Increase Evaluation Confidence

Faster Market Clearance

Decrease Cost

Quick and Predictable access for Patients to Innovative technologies enabled by

Computation Modeling and Simulation asEvidence of safety and performance

501(c)3 Public‐Private PartnershipMembers include FDA/CDRH, CMS, NIH, and Medical Device Industry

Computer Modeling and Simulation Project Vision

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MDIC ‐M&S Project Goals

1. Advance medical device innovation, and evaluate new and emerging technologies

2. Develop state of the art preclinical methods for assessing device safety and performance

3. Develop novel ways to use clinical data in evaluating medical devices4. Define, standardize and educate the medical device community on

validation requirements for the use of M&S in device development and regulatory submission

Heart & Vasculature

Orthopedics

Blood Damage

NeuroStimulation

MR InducedHeating

Library ofModels/Data

Clinical TrialsPowered by

M&S

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Virtual Patientwith the Medical Device Innovation Consortium

Physical Modeling

Probabilistic Modeling

Clinically Relevant

Predictions

Credit: MDIC Modeling and Simulation Project

30at http://mdic.org/mdicx/To learn more, see the webcast:

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FDA GUIDANCE



DeviceDevelopment

Tools

MedicalDevice


ASME V&V40

OSELResearch

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CDRH’s Role in Advancing M&S

• 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 five subject specific appendiceso Fluid & Mass Transport, Solid Mechanics, Electromagnetism, Thermal Transport, and Ultrasound

• Does not address sufficiency of evidence

FDA Guidance on Reporting of Computational Modeling Studies in Medical Device Submissions – published September 2016

http://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/UCM381813.pdf

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Computational Modeling Studies

• FDA is actively drafting a guidance document on a credibility strategy that can be used to help sponsors determine the level of verification and validation needed to support the use of their M&S in regulatory submissions.

Assessing Credibility of Computational Models to support Medical Device Submissions• DRAFT scheduled for Summer 2017• How to implement the risk‐informed credibility assessment

framework in regulatory applications

In collaboration with the ASME V&V40 Committee

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Training on Guidance & Standards

• This year’s BMES/FDA Frontiers in Medical Devices Conference• FDA Training Session on

– Reporting for Computational Modeling Studies– Risk‐informed Credibility Assessment Framework

See http://bmes.org/meddeviceconference for more information on the conference, and details about the abstract submission process –open until January 23, 2017.

May 16‐18, 2017

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ASME V&V 40STANDARDS SUBCOMMITTEE



DeviceDevelopment

Tools

MedicalDevice


ASME V&V40

OSELResearch

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In order to more fully leverage computational modeling and simulations for medical products and clinical care, we need a methodology to ensure appropriate credibility.

Credibility: trust in the predictive capability of a computational model

Adequate reporting, verification, validation and uncertainty quantification are necessary to foster confidence and wider acceptance of in silico methods.

The Need for Credibility

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Parameters

Verification:Does the computational model accurately solve the underlying mathematical model?

Validation:How well does the computational model approximate ‘reality’?

Uncertainty Quantification: How much does uncertainty in parameters affect the simulation results?

Establishing Credibility

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ASME Verification &Validation Committee

CHARTERCoordinate, promote, and foster the development of standards that provide procedures for assessing and quantifying the accuracy and credibility of computational models and simulations.

V&V 10 Computational Solid Mechanics

V&V 20 Computational Fluid Dynamics and Heat Transfer

V&V 30 Computational Simulation of Nuclear System Thermal Fluids Behavior

V&V 40 Computational Modeling of Medical Devices

V&V 50 Computational Modeling for Advanced Manufacturing

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Assessing Credibility of Computational Modeling and through Verification and Validation: Application to Medical Devices

• Not how to do V&V but how to determine the level of evidence needed to support using a computational model for a specific context of use

• Key aspects – new concepts regarding context of use, model risk and credibility

goals– risk‐informed credibility assessment framework

• rigor of V&V is commensurate with model risk– Emphasize documentation and reporting

Verification and Validation of Computational Modeling and Simulation ‐ A community effort. • https://dx.doi.org/10.6084/m9.figshare.3468962.v1POSTER: Risk‐informed Credibility Assessment Method.• https://dx.doi.org/10.6084/m9.figshare.3409291.v1

Verification & ValidationComputational Modeling of Medical Devices

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Verification & ValidationComputational Modeling of Medical Devices

• Main body that describes the details of the framework

• Currently, 6 medical device specific examples

Example Device type Governing physics1 Centrifugal blood pump Fluid mechanics2 Aneurysm flow diverter Fluid mechanics3 Hospital bed Rigid body mechanics4 Deep brain stimulation leads Electromagnetics5 Total knee replacement Solid mechanics6 Interbody fusion device Solid mechanics

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ASME V&V 40 SUBCOMMITTEEVERIFICATION AND VALIDATION IN COMPUTATIONAL MODELING

OF MEDICAL DEVICES

T. M. Morrison, Chair, US Food and Drug Administration, [email protected]. Bischoff, Co-Vice Chair, Zimmer Biomet, Inc.M. Horner, Co-Vice Chair, ANSYS, Inc.R. L. Crane, Secretary, ASME [email protected]

P. Afshari, Depuy-Synthes SpineB. P. Baillargeon, Dassault Systemes Simulia CorpD. Bardot, Medical Device Innovation ConsortiumA. Bestelmeyer, BD TechnologiesJ. P. Bodner, Medtronic CorpS. Cheng, Integra Life SciencesB. D. Choules, MED InstituteR. Chow, ConsultantJ. C. Coburn, US Food and Drug Administration C. Corrales, Baxter Healthcare CorporationK. K. Debus, Cd-adapcoM. Dharia, Zimmer BiometS. Eswaran, Abbott VascularC. Funkhouser, Baxter Healthcare CorporationK. Genc, Simpleware Inc.M. Goodin, Simutech GroupI. Guler, Boston Scientific CorporationA. Gupta, Google Inc.P. Hariharan, US Food and Drug AdministrationW. Hary, HeartflowH. Jin, Medtronic, Inc.A. Kiapour, 4WEB Medical Inc.

W. A. Olson, Ethicon Endo-surgeryC. Popelar, Southwest Research InstituteA. C. Rau, Vice-Chair, Exponent, Inc.T. L. Rossman, Mayo ClinicP. Saffari, EndologixC. Scotti, W.L. GoreR. Swift, Cook Research Inc.P. Tomaszewski, Depuy Orthopaedics IncT. Zhao, Edwards LifesciencesA. U. Nair, Alternate, BD TechnologiesN. R. Rebelo, Alternate, SIMULIA Western Region

L. Knudsen, SyncronessS. Kulkarni, VEXTEC CorporationD. Levine, Zimmer Biomet, Inc.X.M. Li, ConsultantX Liu, Stryker OrthopaedicsB. A. Lurie, W.L. Gore R. Marinescu, Smith & NephewJ. Mast, Hill-Rom, Inc.L. Mulugeta, Independent

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APPLICABILITY FRAMEWORK



DeviceDevelopment

Tools

MedicalDevice


ASME V&V40

OSELResearch

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Develop a model

Perform validation

Alter model in some way

Run COU simulations

Common Approach to “Model Validation”

Pathmanathan P, Gray R, Angelone L, Morrison T, “Demonstrating applicability of validation evidence for biomedical computational models, submitted to JVVUQ Fall 2016

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Schematic Representation of Applicability

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Applicability FrameworkLead PIs: Drs. Pras Pathmanathan and Tina Morrison

• The context of use of M&S for medical products usually involves the clinical setting and/or patients

• The inability to perform direct validation hinders the broader acceptance and reliability of computational modeling.

• Our aim is to develop a systematic approach to answering this question.• The proposed framework is used to break down the above question into

a series of tractable questions• These questions can then be addressed using supporting evidence or

subject matter expertise.

Direct validation study is conducted with a comparator that has been closely designed to match to the COU.

An indirect validation study is conducted with a comparator for which there are significant differences to the setting of the COU.

Problem:How applicable is the model, and the validation results, to the COU?

Demonstrating applicability of validation evidence for biomedical computational models. https://dx.doi.org/10.6084/m9.figshare.3409294.v2

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OSEL RESERCH



DeviceDevelopment

Tools

MedicalDevice


ASME V&V40

OSELResearch

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OSEL Research Efforts in M&S

Applicability Framework Ultrasound Enhanced Drug Delivery

Dynamics of Cardiac Fibrillation Computational Patient Models for Closed‐Loop Medical Devices

Credibility of Computational Models of the Heart Computational Risk Assessment

Simulations of Electrocardiogram Biomarkers for Allergic Risks

Deformation of Bioprosthetic Aortic Valves Ganglion Cell Model for Epiretinal Electrode Stimulation

Patient‐specific Modeling of Inferior Vena Cava Filters

Fretting of Total Hip Arthroplasty

Aerosol Leakage of Respirators Constitutive Model for Absorbable Materials

Benchmarks for Computational Fluid Dynamics Virtual imaging clinical trial for regulatory evaluation

Multimodal Imaging‐Based Model of the Human Head and Neck

In silico Breast Phantom

Electromagnetic Exposure Maps Lesion Insertion into Clinical Images

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VICTREVirtual Imaging Clinical Trials for Regulatory EvaluationLead PI: Dr. Aldo Badano

• Definition: Set of computational models and tools that mimic relevant properties of patients, devices, and practitioners for establishing the safety and effectiveness of new products.

•

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MEDICAL DEVICE DEVELOPMENT TOOLS



DeviceDevelopment

Tools

MedicalDevice


ASME V&V40

OSELResearch

50

Medical Device Development Tools

Why are we qualifying tools?

Tools considered and evaluated on a case-by-case basis

Qualified for regulatory purposes, within a defined context of use

TODAY FUTURE

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MDDT Types

Clinical Outcome Assessment (COA) Patient selection Clinical study outcomes

• Objective and subjective

Non‐clinical Assessment Method (NAM) New method to measure or predict a

parameter of interest Replace/ reduce animal testing

Biomarker Test (BIO) Objective measure of biologic process or

response to an intervention Patient selection Predict or identify outcomes

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What is a MDDT Context of Use?

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Device or Product Area

Specific Role of the MDDT

Regulatory Evaluation

Context of use defines the boundaries within which evidence & justification supports tool use Stage of

Development

POSTER: Medical Device Development Tools Program. https://dx.doi.org/10.6084/m9.figshare.3409288.v1

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For medical devices, we envision a future of

Digital Patients: Designers download anatomic and physiologic computer models of (dozens, hundreds, thousands, …) of patients with a given disease.Virtual Clinical Trials: New product concepts are “deployed/tested” in virtual patients and performance is simulated leading to more effective bench testing, animal studies and (actual) clinical trials, possibly augmenting real‐world clinical trials.

Discover “Soft Failures”Personalized Medicine: Physicians use simulation to predict safety and effectiveness of a given medical product for an individual patient.


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To realize that future, we need

• to raise awareness regarding the capability and limitations;• a systematic assessment and understanding of use conditions;• methodologies for verification, validation, sensitivity analyses and

uncertainty quantification for medical applications; • methodologies for credibility assessment;• framework(s) for determining the level of evidence needed to

support the use of M&S; and• to continue to advance the science.


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Success through collaboration• CDRH is in the unique position to stimulate and advance device

innovation through computer simulation and modeling efforts (for both evaluation and design).

• Collaboration is necessary because these projects are highly interdisciplinary, with numerous stakeholders.

Imaging specialists Clinicians Engineers Material scientists Computer scientists Regulatory scientists Government Agencies

Patients


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Join Us in March!ORS 2017 Annual MeetingMarch 19‐22, 2017 in San Diego, CaliforniaBasic, translational, and clinical research is presented at the ORS Annual Meeting each year, which is the world’s largest research forum dedicated to orthopaedics. Special programming related to industry such as additive manufacturing workshop, hands‐on 3D printing workshop, and FDA related topic session will provide opportunities to learn, engage, and network with a variety of professionals just like yourself from all over the world! This is one meeting you do not want to miss!

For details, please visit www.ors.org.

Join the ORS community and its Orthopaedic Implants Section! Apply Today! Visit www.ors.org Email [email protected]

Visit the Orthopaedic Implants Section at http://www.ors.org/ors‐orthopaedic‐implants‐section/


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FDA: Modeling and Simulation Initiatives at CDRH


Contact:[email protected]

Tina Morrison, PhDFDA/CDRHDeputy DirectorDivision of Applied Mechanics, Office of Science and Engineering Laboratories

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Additional informative websites

• FDA Pre‐submission Guidance– http://www.fda.gov/downloads/medicaldevices/deviceregulationandguidance/guidancedocuments/ucm311176.pdf

• FDA Medical Device Development Tools– http://www.fda.gov/MedicalDevices/ScienceandResearch/MedicalDeviceDevelopmentToolsMDDT/

• POSTER: Medical Device Development Tools Program.– https://dx.doi.org/10.6084/m9.figshare.3409288.v1
