Making Models Publicly Available: Successes and Challenges

Transcription

1 Making Models Publicly Available: Successes and Challenges Tina Morrison PhD Office of Device Evaluation Center for Devices and Radiological Health U.S. Food and Drug Administration

2 Modeling & Simulation for Medical Products Workshop Workshop Objectives Integrated approaches to modeling & simulation (M&S) for developing medical products and regulatory review. Drug development and regulatory review has become increasingly challenging and resource intensive. An integrated strategic approach to developing and applying M&S tools in drug development will enhance decisionmaking processes. This workshop will examine: Novel tools and approaches to accelerate the development of efficacious medicines with optimal benefit/risk profiles Successes and lessons learned in the use of M&S by FDA, industry, and public private partnerships Challenges & opportunities for these innovative approaches 2

3 Advancing Regulatory Science at FDA FDA has identified an important role for CM&S in its strategic priorities. 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 opics/regulatoryscience/ucm pdf 3

4 Session III: Future Perspectives for M&S Tool Development & Applications Future of M&S for medical device product development and evaluation Digital Patients: Designers download anatomic and physiologic computer models of (dozens, hundreds, thousands, ) of patients with a given disease. Virtual Clinical Trials: New device concepts are deployed in digital diseased patients and performance is simulated leading to more effective bench testing, animal studies and (actual) clinical trials. Discover Soft Failures Personalized Medicine: Physicians use simulation to predict safety and effectiveness of a given medical product for an individual patient. 4

5 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

6 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

7 Medical Device Evaluation Comprehensive evaluation of a marketing application for a therapeutic medical device typically supported by a combination of 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

8 Models and Their Advantages Adapted from Victor Krauthamer * M&S in medical devices, as compared to other industries, is nascent and is the one model with the most potential for refinement/improvement because the other models are fairly mature. 8

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

10 Areas of Active Research Computational Solid Mechanics Stents, Heart Valve Frames, Occluders, Vena Cava Filters Spine & Joint Implants Computational Fluid Dynamics and Acoustics Blood Pumps, Heart Valves, Endovascular Grafts Drug Eluting Stents, Virus and Aerosol Transport Ultrasound Propagation Heat Transfer and Thermal Bioeffects Computational Toxicology Computational Electromagnetics Virtual Clinical Trials 10

11 Virtual Family FDA/CDRH, IT IS Foundation, Mobile Manufacturer Forum FDA PI: Wolfgang Kainz (OSEL/DP) 9 different models available, more than 200 organs and 43 tissues, direct import and automatic material assignment, voxel import of models obese adult, 1.78m, 120kg male adult, 1.74m, 70kg female adult 1.60m, 58kg 11 y girl 1.46m, 36kg 6 y boy 1.17m, 20kg 14 y boy 1.65m, 50kg 8 year old boy 1.40m, 26kg 8 y girl 1.35m, 30kg 5 y girl 1.09m, 16kg

12 Human Head Models FDA/CDRH, IT IS Foundation Kainz, Angelone, Cohen, Iacono, Akinnagbe, Majdi (OSEL/DP) A functional high resolution human head model for analysis of efficacy of medical devices

13 MRI RF Coil Models FDA/CDRH, IT IS Foundation Kainz, Angelone, Iacono, Lucano, Mendoza, Bassen(OSEL/DP) Development and distribution of validated MRI RF Coil Models

14 FDA Digital Library Modeling and Simulation It will be a mechanism for curating a public open use repository of 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 M&S and data related to medical products Mechanism for FDA to transparently communicate utility and expectations of M&S in a regulatory setting. Being a space for companies to share their smaller datasets, e.g., pediatric population, to create a larger datasets 14

15 FDA Digital Library Modeling and Simulation 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 they ll curate DATA for creating models and validating simulations, and reference problems Prototype is underway with sights on pilot in 2014 Contact: 15

16 CHARGE: Discuss Success and Challenges with Making Models Publicly Available 16

17 Lots of Model Repositories

18 Making Models Publicly Available Who is making models publicly available? Who as in the authority o Hosting institution/information system administrators Who is maintains stewardship? o Addresses the ethical questions of care, advocacy, preservation? What is their motivation? Who is tracking the currency and accuracy? o E.g., verification of source, version control 18

19 Making Models Publicly Available A model is a simplified representation of a real system There are many types of models: o Mathematical models of physics, biology, chemistry o Behavioral models o Animal models o Statistical models o Solid (geometrical) models What about the data to make the model? Are metadata provided to fully describe the model? 19

20 Making Models Publicly Available Who is the public (i.e., user community, stakeholders)? Academicians Industry/Manufacturers Other government agencies Clinicians Patient advocate groups How is it made publicly available? Does public = open? Do some pay a fee, or contribute to the community? What are the sources of sponsorship? 20

21 Making Models Publicly Available What does it mean for the models to be available? To view the model To download and manipulate To share with others To modify and evolve To upload modified version 21

22 Success What defines success? That models are shared? That models are curated? That models are downloaded and used? That models evolve based on broad use? That publicly available models can minimize (development) resources? 22

23 Challenges Interoperability Lack of common terminology, common platforms Discoverability Policy/Governance Sponsorship (e.g., for start up, sustainability) What about credibility? Credibility of the source? The model? The data? The validation? the context of use? 23

24 Credible Practice of M&S in Healthcare Credible: dependable with a desired certainty level to guide research or support decision making within a prescribed application domain and intended use; establishing reproducibility & accountability. Practice: any activity involving development, solution, interpretation and application of computational representation of biological, environmental and man made systems and their interaction thereof. Modeling: specifically computational modeling; virtual representation of system(s) of interest in a usable form in order to provide descriptive and predictive metrics for timely and systematic exploration of the system(s). Simulation: computational solution of models to quantify descriptive and predictive metrics of system(s) of interest; including related post processing efforts to calculate these metrics from raw analysis results. Healthcare: any activity involving development, maintenance, advancement, or administration of medical care; including research, diagnosis, risk assessment, prevention, therapy, rehabilitation, surgery, intervention design, and regulation. 24

25 Objectives of CPMS 1. Unify M&S vocabulary and terminology 2. Develop guidelines and credibility principles 3. Define and Demonstrate translational workflows 4. Promote good practice through outreach 5. Establish model certification process 6. Identify new areas of research to improve 2 &

26 FDA is thinking about Credibility In conjunction with one of our standards organization, ASME, CDRH has developed a risk based Strategy to Assess Credibility of M&S. The level of credibility should be commensurate with the context of use. The goal is to utilize this strategy to assess whether models are credible (valid scientific evidence) for regulatory decision making. Implementing the strategy in a pilot program in early 2014 for M&S in pre market submissions. Aiming to qualify the Credibility Strategy as a Medical Device Development Tool. 26

27 Message Think about Credibility Need to clearly define the type model Describe how was it created Identify how it can be used Define the domain of validity Or the domain of invalidity Enable reproducibility Provide the references for input data Provide data for validation Meta data for accurate and appropriate use 1 [1] Erdemir, Guess, Halloran, Tadepalli, Morrison J Biomech February 23; 45(4):

28 Acknowledgements FDA NIH IMAG/MSM CDRH M&S Working Group Virtual Family Leonardo Angelone Wolfgang Kainz FDA Library Team James Coburn Jessica Hernandez* Donna Lochner FDA Credible M&S Working Group CPMS Ahmet Erdemir Lealem Mulugeta Data/Model Sharing Team Contact Information Office of Device Evaluation Center for Devices and Radiological Health