The document discusses the advantages of using computational modeling and simulation in the development of medical devices, emphasizing time and cost savings along with enhanced product quality. It highlights critical design questions, the limitations of physical prototypes, and the regulatory implications of preclinical data requirements. The presentation concludes that effective modeling and simulation, augmented by cloud computing, can streamline the regulatory process and provide effective data visualization for better communication of complex concepts.

1. M O D E L I N G A N D S I M U L A T I O N
T O G E T T O M A R K E T F A S T E R
10X MEDICAL DEVICE/MDTX CONFERENCE
SECAUCUS, NJ
APRIL 5, 2018
ARLEN K. WARD, PHD, PE

2. W H Y A R E W E
H E R E ?
Leveraging computational
modeling and simulation
will save time, save money,
and result in a
demonstrably better
product.

3. A L I T T L E A B O U T M E
A R L E N W A R D
15 years in Medical Device R&D [Valleylab/Covidien/Medtronic]
BS and MS degrees in Mechanical Engineering from University
of Colorado
PhD in Mechanical Engineering from Colorado State University
PHD, PE
Dissertation: “Improvements to Transurethral
Resection of Prostate (TURP) Electrosurgical
Devices through Finite Element Modeling”
Licensed PE in Colorado
17 US and 50+ Worldwide Patents

4. D E S I G N
Q U E S T I O N S
What power will provide the desired
surgical result for our new device
concept?
What are the performance expectations
in human trials for our device that has
been developed using animal models?
Is our sensor placement optimized?
If we change our design to improve the
device manufacturability, will it change
the surgical effect in unintended ways?

5. Physical prototypes are limited to how a technology is
implemented, not just what is being tested. The existing
DOE approach is also limited to what effects can be
discerned within the noisy results of tissue.
H o w d o w e t r a n s l a t e d e s i r e d
m e d i c a l e f f e c t b a c k t o e n g i n e e r i n g
r e q u i r e m e n t s ?
T H E P R O B L E M
E n g i n e e r i n g M e d i c a l E f f e c t
P o w e r
G e o m e t r y
T i m e
D i v i d e T i s s u e
H e m o s t a s i s
A b l a t e

6. W H A T A R E W E T R Y I N G T O A D D R E S S ?
Trying to optimize instrument design through in vivo
and in vitro tissue testing.
T I M E C O N S U M I N G E X P E N S I V E D I F F I C U L T
Studies suggest a 30% variation
between porcine renal artery sources

7. I N S I L I C O P R E C L I N I C A L D A T A
G O A L

8. S I N G L E P H Y S I C S F E A

9. M U L T I P H Y S I C S
Complicated real-world
problems
Interaction between
multiple physics
Complex material
behaviors
Multiphysics FEA

10. W H Y M O D E L I N G
A N D S I M U L A T I O N ?

11. SIMULATION
REDUCES
PROTOTYPING TIME
Multiple design parameters
+
Multiple options for each
=
Exponential number of
iterations

12. S E N S I T I V I T Y
A N A L Y S I S
Design tolerances for production
Design options
Troubleshooting
Cost saving
Product development space
Technology Evaluation
Optimization
Monte Carlo simulation
Assign distribution to inputs
Run hundreds or thousands of
iterations
Analyze impact on outputs

13. R E G U L A T O R Y I M P A C T
Increasing preclinical data
requirements
Equipment interoperability
Patient size
Increasing preclinical data
requirements
Field questions from FDA
subject matter experts (SMEs)
Address with simulation data
Cut preclinical testing
requirements
FDA Guidance- Reporting of Computational Modeling
Studies in Medical Device Submissions (Sept 2016)
ASME V&V 40- Verification and Validation in
Computational Modeling of Medical Devices (est. 2018)

14. R E G U L A T O R Y S I M U L A T I O N F R A M E W O R K

15. D A T A
V I S U A L I Z A T I O N
Customers or
Nontechnical Audience
Explain Device Function
Intuitive Grasp of
Concepts

16. C O M P U T A T I O N A L
R E Q U I R E M E N T S
Realistic simulations were
computationally expensive
Supercomputers
Clusters
...and financially expensive
In-house Experts
IT Overhead

17. C L O U D R E S O U R C E S

18. C A V E A T S F O R M O D E L I N G
A N D S I M U L A T I O N
Every simulation requires experimental validation and
convergence tests
Can’t model what we don’t understand

19. I M P A C T A N D O P P O R T U N I T Y

20. I M P A C T A N D O P P O R T U N I T Y

21. T H E T A K E A W A Y
Modeling and simulation
significantly reduces time to
market for medical device
development
01. 02.
Modeling and simulation
can reduce the regulatory
load required by the FDA
03. 04.
Data visualization is an
effective tool for
communicating complex
concepts
Data centers and cloud
computing puts computational
modeling and simulation within
reach of a company of any size

22. T H A N K Y O U !
A R L E N W A R D
arlen@sysinsighteng.com
720.744.0059
@sysinsight
WWW.SYSTEMINSIGHTENGINEERING.COM