Tina M. Morrison, Ph.D. - Amazon S3 · Tina M. Morrison, Ph.D. Advisor, Computational Modeling...
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2014 Tina M. Morrison, Ph.D. Advisor, Computational Modeling Office of Device Evaluation CDRH/U.S. FDA 2014
Transcript of Tina M. Morrison, Ph.D. - Amazon S3 · Tina M. Morrison, Ph.D. Advisor, Computational Modeling...
2014
Tina M. Morrison, Ph.D.Advisor, Computational Modeling
Office of Device Evaluation
CDRH/U.S. FDA
2014
2014
Regulatory Science
Regulatory Science is the science of developing new tools, standards, and approaches to assess the safety, efficacy, quality, and performance of all FDA‐regulated products.
Computational modeling and simulation (CM&S) is not a new tool but can be leveraged in a new way to greatly impact premarket submissions of medical products.
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Advancing Regulatory Science
Science Priority Areas
#1 Modernize Toxicology
#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
(Q)SAR models 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 Methods to verify, store, share
1, http://www.fda.gov/downloads/ScienceResearch/SpecialTopics/RegulatoryScience/UCM268225.pdf
FDA has identified an important role for CM&S in its strategic priorities1.
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CM&S as valid scientific evidence
e.g., fatigue safety factors
CM&S is the medical device
e.g., clinical decision support
The Role of CM&S at CDRH
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CM&S embedded in a medical device e.g., physiological
model in a control system
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The Role of CM&S at CDRH
medicalnewstoday.com
CM&S embedded in a medical
device e.g., logical algorithm in a control system
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The Role of CM&S at CDRH
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heartflow.com
CM&S is the medical device
e.g., clinical decision support
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The Role of CM&S at CDRH
7Kelm, Int J of Med Sci 2009
Bluestein, PLOS ‐ 2012
CM&S as valid scientific evidence
e.g., fatigue safety factors
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Medical Device Evaluation
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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.
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Medical Device Development with CM&S
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The Total Product Life Cycle
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CM&S are typically Relative• Design Optimization• Virtual Prototyping• Rationale for Pre‐Clinical Evaluation• Root Cause Investigations + Redesigns• Next Generation Designs
Medical Device Development with CM&S
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CMS REIMBURSEMENT
POSTMARKET
MONITORING
CMSEVALUATION
CMSREIMBURSEDECISION
REAL‐WORLDPRODUCT
PERFORMANCE
FDAREGULATORYDECISION
PRODUCTLAUNCHCLINICAL
PRE‐CLINICALINVENTION
+PROTOTYPING
DISCOVERY+
IDEATION
NEXT GENERATIONPRODUCT
DEVELOPMENT
The Total Product Life Cycle - Updated
2014
CM&S OpportunityPredict Product Success/Failure to support:
Regulatory decisionsReimbursement decisions
Medical Device Development with CM&S
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CMS REIMBURSEMENT
POSTMARKET
MONITORING
CMSEVALUATION
CMSREIMBURSEDECISION
REAL‐WORLDPRODUCT
PERFORMANCE
FDAREGULATORYDECISION
PRODUCTLAUNCHCLINICAL
PRE‐CLINICALINVENTION
+PROTOTYPING
DISCOVERY+
IDEATION
NEXT GENERATIONPRODUCT
DEVELOPMENT
The Total Product Life Cycle - Updated
2014
Some of the challengeswith the current practice …
… have led us to address the need for:
guidance on documentation and reporting CM&S results in premarket submissions;• FDA DRAFT Guidance on Reporting of Computational Modeling
Studies in Medical Device Submissions – published Jan 20142
systematic assessment and understanding of device‐use conditions;• Critical Path Innitiative3
• FDA Library of Models and Simulation4
• Medical Device Innovation Consortium5
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2, http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/ucm371016.htm3, http://www.fda.gov/ScienceResearch/SpecialTopics/CriticalPathInitiative/default.htm4, http://www.fda.gov/MedicalDevices/NewsEvents/WorkshopsConferences/ucm346375.htm5, http://mdic.org/projects/computer‐modeling/
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FDA Digital Library of M&S
The vision is that the Library will be a mechanism for curating public open‐use models and simulations in a non‐competitive space to foster collaboration and advance research, development and evaluation of medical devices.
Serve as a reference for access to state‐of‐the‐art CM&S and data related to medical products
Mechanism for FDA to transparently communicate utility and expectations of CM&S in a regulatory setting
Being a space for companies to share their “smaller datasets”, e.g., pediatric population, to create a “larger datasets”
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FDA Digital Library of M&S
Hosted public workshop in June 2013 to introduce concept and openly discuss the Library
Developed key aspects of the infrastructure and framework for use of the Library
Anticipate initially that the Library will be used for curating DATA for creating models and validating simulations, and reference problems
Prototype is underway with sights on pilot in 2014
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Some of the challengeswith the current practice …
… have led us to address the need for:
methodologies to experimentally validate CM&S; sensitivity analyses and uncertainty quantification; and
• CDRH is actively engaged with the ASME Verification & Validation Standards Committee
o ASME V&V 10 – Subcommittee on Solid Mechanicso ASME V&V 20 – Subcommittee on Fluid Dynamics and Heat Transfer
ASME V&V 40 – Subcommittee on CM&S for Medical Devices
better elicitation of the consequence of the CM&S being incorrect.• CDRH is getting ready to launch a pilot program to expand the
current uses of CM&S in premarket submissions and to implement the Credibility Strategy
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Credibility Strategy Overview
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Risk Assessment
Establish Context of Use
CM&S Risk: combination of decision influence and consequence Decision Influence: contribution of
CM&S outcome to the decision being made
Consequence: impact if the CM&S outcomes prove incorrect
Risk assessment• Directs/guides V&V activities• Defines model credibility thresholds
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LOW
MEDIUM
HIGH
CONSEQUENCE
INFLUEN
CE
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Framework to Assess Credibility
Ensuring that the credibility of the CM&S is commensurate with the associated risk provides the confidence that the CM&S is appropriate for the intended COU
Multiple factors contribute to CM&S credibility:
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Code Verification Sample Characterization
Solution Verification Control Over Test Conditions
System Configuration Measurement Uncertainty
System Properties Discrepancy of Inputs/Outputs
Boundary Conditions Rigor of Output Comparison
Governing Equations Applicability to Context of Use
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Applicability of V&V Activities
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Pilot Program at CDRH
CDRH is launching a pilot program this Spring to implement and evaluate the Credibility Strategy in the review of CM&S in premarket submissions• Collaboration with OSEL and ODE• Focus on Cardiovascular and Orthopaedic Devices
The Credibility Strategy will also be evaluated as part of the qualification process for the Medical Device Development Tool6 program
It will also be used to help determine which CM&S can be a part of the FDA Library of Models and Simulation
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6, http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/ucm374427.htm
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Future Directions
Digital Patients Virtual Clinical Trials Personalized Medicine
FDANIH
INDUSTRY
ACADEMIA M&S
NSF
NIST
NASA
DARPA
MDIC
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are being realized
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Acknowledgments
FDA Library of M&SDonna Lochner, OSELJames Coburn, OSELLeonardo Angelone, OSELJessica Hernandez, OSEL
Credibility Strategy Pilot TeamTina Morrison, ODEJames Coburn, OSELMaureen Dreher, OSELFinn Donaldson, OSELNandini Duraiswamy, OSELCasey Hanley, ODENicole Ibrahim, ODEMatt Myers, OSELSrin Nagaraja, OSELKatie O’Callaghan, OCDDavid Pudwill, ODEChangfu Wu, ODEZane Wyatt, ODE
Contact Information
Office of Device Evaluation, CDRH
ASME V&V40: Verification and Validation in Computational Modeling of Medical Devices
