Scientific data, homegrown or from published literature, is essential to your regulatory strategy…be it establishing substantial equivalence in FDA 510(k) applications, qualifying a device as a legitimate predecessor in the context of a Technical File for CE Mark, predicting the performance of a device in development, judging a new device in verification and validation testing and, with proper planning, expanding indications for use and identifying new marketable claims of performance (or mitigation of risk and liability). In this session, participants will be exposed to various vital data sources and obtain practical examples for putting them to meaningful use.
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Leveraging Data to Develop, Execute and Exceed the Expectations of Your Regulatory Strategy - OMTEC 2018
1.
2. Leveraging Data to Develop, Execute,
and Exceed Expectations of Your
Regulatory Strategy
OMTEC 2018, Chicago, IL USA
Robert A Poggie, PhD
President, BioVera Inc.
Notre-Dame-de-L’Ile-Perrot
Quebec, Canada
3. About the Instructor…(Robert A Poggie, PhD)
3
BE mechanical Engineering, MS and PhD in Materials
Science & Engineering, Vanderbilt University
Tribology, surface chemistry, metallurgy, mechanical testing…
Employers, large and small companies in orthopaedics
S&N, Zimmer, Implex, Pipeline Orthopaedics
Self employed since 2009, BioVera Inc.
FDA regulatory work dominates time, including development
and management of testing; biomaterials expertise
Current clients include Bodycad, AmorChem, NextStep
Arthropedix, Biedermann-Motech, Bio-Gate, Acuitive
Technologies, AGelity (HSS)…
BioVera, Inc.
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4. Introduction
4
Leveraging Regulatorily Required Data (homegrown and published)
Maximizing claims / statements in marketing application
Scientific and conference publications
Feedback for improved and new products
Develop Regulatory Strategy
Rough to detailed plans, metrics, target criteria (‘success’)
Execute Regulatory Strategy
Supporting application through to clearance / approval
Exceed Expectations = Leveraging as above
BioVera, Inc.
Integrity Expertise Results
5. Outline
5
Background
Identifying and using data in FDA submissions
FDA and ISO data requirements for new devices
Industry white papers, top journals, conference abstracts
Establishing substantial equivalence with data
Predicate and reference devices; IFU is ‘king’
Case examples
Reducing risks and increasing efficiency to market
Q&A, discussion, open-forum
BioVera, Inc.
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6. Regulatory Trend, 25 Years
6
Continuously increasing regulations of all devices
Continuously increasing number of required tests
Dramatic increase in consensus standards for pre-clinical tests
Increasing demand for clinical data; especially Europe in 2017
Increasing sophistication of test methods (FEA, sims, wear…)
And in turn cost of regulatory testing has sky rocketed…
Validations of processes and performance
W/r to design specifications and planned surgery
Sterility, cleaning of reusable insts, endotoxins, biocompatibility…
Statistical significance (more devices tested; higher cost of test)
BioVera, Inc.
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7. Regulatory Trend, Today’s News
7
April 2017: European Union issues new medical device
regulations (MDRs); 10-fold increase in text
Class 2b required to have significantly more clinical evidence
to obtain and maintain CE Mark
Clinical = published scientific data on similar devices, company’s
own clinical data, or new clinical trial data
Class 2b products often treated as class 3 products
Rigorous requirements for post market surveillance
Clinical outcomes and AEs
Significantly higher barrier (cost and time) to market for new
devices and devices with minor differences
Fewer ‘me-too’ products = higher cost, fewer new products
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8. Cause and Effect
8
NewCo desires CE Mark for cementless hip in EU
< 2017, Technical file + clinical literature data for safety
2017 / 2020, Clinical data required, 1 or 2 years fu for
between 30 and 60 patients; RSA possible
Effect – Fewer NewCo class 2 products in Europe
NewCo wants CE Mark for resorbable ACL device
< 2017 and currently, class 3 high risk device requires
clinical trial; 60 to 65 patients, RCT, 2 year fu, PMS
Effect – No change in EU and USA companies strategy
for class 3 devices; lower cost barrier to large marketBioVera, Inc.
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9. Test Plan (for data for pre-sub and application)
9
First-Order Items to Define and Search
Identify the FDA regulation # and product code
Identify and obtain FDA Guidance Documents (if any) – and
draft list of data required for regulatory application.
Identify and obtain consensus test standards (e.g. ASTM,
ISO) that govern performance testing
Identify predicate devices and obtain 510k) summaries
or PMA documents
Scientific literature using key words regarding your
product and performance tests of interest
Company websites for technical / white papers
BioVera, Inc.
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14. 510(k) Summary Examples
14
Arthrex – Vitamin E UHMWPE, using existing data
for new products with common materials.
Zimmer – Vivacit UHMWPE and control data; data
aids in planning tests, supporting ‘control’ data for
similar products (and IFU).
PorOsteon – Functional animal data for cervical
fusion in sheep; data useful for planning tests and
for control data (PEEK and porous metal devices)
BioVera, Inc.
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15. Leveraging Data: Arthrex Example
15
Applicability of data for x-linked, vit. E tibial
insert for TKR to subsequent uni tibial insert
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Tens of thousands / 100K $$ and
months saved in using poly insert
data from TKR to UKR systems.
16. How Was This Possible?
16
UKA and TKA have similar kinematics for a given
compartment (lateral, medial)
Arthrex likely has same or very similar articulation
design for the femoral and tibial surfaces
Therefore, contact mechanics about the same
Tribology about the same
FDA may have required proof via additional
contact area and stress maps for both products
BioVera, Inc.
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17. Leveraging Data: Zimmer K120370
17
BioVera, Inc.
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11 performance claims (Vivacit poly) with supporting data!
Mechanical properties (tensile, small punch, lzod, Crack Propagation),
physical and chemical characterization (Oxidation Index, Compressive
Modulus, Poisson's Ratio, Surface Roughness, Density, Melting Temperature,
Degree of Crystallinity, Crosslink Density, Swell Ratio, Molecular Weight,
Free Radicals, Vitamin E Elution and Extraction, Trans-vinylene Index…
From Claim #8 of 11: Predicate and subject data statements…
18. Leveraging Data: PorOsteon K142041
18
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Histology, micro-CT, in-life radiography, CT, biomechanical evaluation
of Phusion Metal Cervical Cage devices in the ovine model showed…
100% rate of fusion at 6 months (4 sheep, 2 devices/sheep),
Statistically equivalent fusion at 6 months to the control
Statistically significant, higher percentage of bone contact of the
superior and inferior surfaces of devices at 4 and 6 months for
Phusion Metal devices as compared to PEEK control devices
(23.90% vs. 9.94% at 4 months; 56.09% vs. 27.31% at 6 months).
Claims allowed in marketing literature.
Claims useful for predicting and planning outcomes of
functional modeling of cervical devices.
19. Scientific Literature Links
19
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/
Google Scholar
https://scholar.google.ca/
ClinicalTrials.gov
https://clinicaltrials.gov/
Useful for planning clinical studies / trials
Limited amount of data; sparse BioVera, Inc.
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20. Orthopaedic Journal Links
20
www.jbjs.org
https://www.arthroplastyjournal.org
http://tools.clinorthop.org/
https://www.arthroscopyjournal.org/
https://www.thespinejournalonline.com/
https://www.orthoworld.com/; https://ryortho.com/
Recommend that one or more people in your
organization subscribe to the ‘best’ scientific
journals, and at least one trade journal. BioVera, Inc.
Integrity Expertise Results
21. Scientific Literature Examples
21
Peck et. al. (FDA)
Data gold mine for cervical fusion devices, no
predicate testing needed for strength
Micheli et. al.
Data for wear, oxidation, strength of tibial
inserts; likely eliminates need for control
Mazzocca et. al.
Data for tendon-ligament interference screws;
four devices, methods, results; covers predicate
BioVera, Inc.
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24. BioVera, Inc.
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Arthroscopy: The Journal of Arthroscopic and Related Surgery, Vol 21, No 11 (November), 2005: pp 1296-1306
25. Judging Quality & Utility of Data
25
Is IFU statement for your product similar to that of
the device with published data?
Methods and materials described in sufficient detail
to replicate and/or explain differences?
Statistical significance of the data, or same sample
numbers in 510(k) summaries or FDA guidance dox?
Consensus standards used? Where none exist,
industry ‘norms’ for test methods?
Source from reputable journal or society conf.?
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26. For years, device companies used the Central Limit Theorem (CLT) and its rule of thumb of 30 parts tested. Increasing
tolerances and regulatory oversight are two reasons that CLT is no longer relative. For example, FDA now seeks a more
analytical approach—justification—for choosing sample size.
However, calculating an appropriate minimum sample size is one of the most difficult things to do and is an ongoing
challenge for many of us. To complicate things further, a large number of journal articles are devoted to this subject, and
their advice is often case-specific or discusses a new and unique way to determine a sample size, leaving us more confused
than ever. I am not a statistician, and after reading a dozen or more articles, I’ve come to the conclusion that “everything
depends on everything” when it comes to statistics. There are no simple answers.
As an example, let’s say you want to determine the sample size if the standard deviation over time has been σ = 0.02 inches from the desired perfect length, but you’re
willing to accept an error of 0.005 inches from that number for any given sample mean. Since we’re assuming normal distribution and we know probabilities vary from 0
to 1, the center of your bell curve is 0.5. Thus, you take 0.5 – 0.025 = 0.475 and look up Z = 1.96. Rearranging your equation to solve for n:
Thus, for this one measurement, your sample size should be 62. The formula is very sensitive to E, and this is something that you have to decide based on your
experience. Note that it’s not necessary to do this calculation for every variable. In fact, you should choose your worst case, most important variables and set the
sample size based on them, as all of the other variables will require fewer samples.
Practical Information
Examining Methods to Determine Sample Sizes
Posted in Legal, Clinical & Regulatory | December 05, 2017 | Comments (0)
Tags: Editor's Choice, fda, validation, verification, testing, quality management, FDA
By: Deborah Munro
Reader Question: Larger companies have statisticians on staff to determine the minimum number of samples for given validation and verification (V&V) activities, but for
folks who don’t use Minitab and don’t have an extensive stats background, are there guidelines to know the right amount of parts to test?
27. Consensus Standards
27
ISO standards
https://www.iso.org/standard/44908.html
ISO stds findable via www search and purchase
ASTM
https://www.astm.org/industry/health-care-and-
medical-devices-standards.html
Same story as ISO stds; lower cost w/r to ISO
BioVera, Inc.
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28. Company Websites
28
www.arthrex.com
Example: https://www.arthrex.com/knee/biocomposite-
interference-screws
One of the white papers: BioComposite™ Interference Screws
- A Stronger Turn in ACL/PCL Reconstruction
Data to be used for planning regulatory path and tests; i.e. the
strategy and tactics for FDA pre-sub and/or 510(k):
2 years animal data for Arthrex and DePuy screws
Torque in / out, strength of screws, Arthrex and DePuy
Solubility and cell tests for two materials… and more…
BioVera, Inc.
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29. BioVera, Inc.
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Page 3 of BioComposite™ Interference Screws
- A Stronger Turn in ACL/PCL Reconstruction
Arthrex white paper
Page 1 of Arthrex 7 mm x 23 mm BioComposite
Interference Screw vs. DePuy Mitek 7 mm x 23
mm Milagro Screw. Arthrex white paper
31. Case Example: Ankle Replacement
31
Many 510(k)s
FDA website for PMA dox (includes clinicals)
for several products cleared since the early
2000s
Robust literature
Well described tests finable on www
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32. FDA Resources for Ankle Devices
32
FDA website and Google to start searches as...
https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/p
mnsimplesearch.cfm
Type in “ankle”, order results from most recent, review 510(k)
summary (class 2) for K171004.
On Google, type in “PMA for ankle replacement”
https://www.fda.gov/ohrms/dockets/ac/07/slides/2007-
4299s1-01.pdf
https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfPMA/p
ma.cfm?id=P050050
https://www.accessdata.fda.gov/cdrh_docs/pdf5/P050050B.p
df
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33. Ankle Devices
33
Top Level Info of Importance…
2-part device is class 2
3-part device is class 3 (cementless and
mobile bearing (STAR, p050050)
510(k) summary lists performance tests
applicable to both class 2 and 3 devices
FDA guidance documents
ASTM and ISO consensus standards listed
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34. From K171004…
34
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ASTM F2665-09
https://www.astm.org/Standards/F2665.htm
FDA Guidance for plasma sprayed coatings…
https://www.fda.gov/downloads/medicaldevices/
deviceregulationandguidance/guidancedocuments
/ucm107699.pdf
And more…
35. From slide deck & p050050 doc.
35
BioVera, Inc.
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• Pre clinical testing information, wear testing
details, and more...
• Detailed information on clinical trial
• IFU
• Clinical measures, subjective, objective
• Patient pop, Statistical methods
https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfPMA/pma.c
fm?id=P050050
https://pdfs.semanticscholar.org/presentation/b473/7bec3f721e2
7f3e813589d1c6e6ea45dd82f.pdf (slide deck)
37. Case Example: Hedrocel (TM) Cup
37
Monoblock with UHMWPE direct-molded into
porous tantalum shell (K964509)
Unique design & material; regulatory consultant advised
that IDE-PMA was only path (R&D/we rejected advice)
Porous coated, metal backed, factory interference fit
monoblock used as predicate (K932923).
Testing / Data Planning for Regulatory & Marketing
ORL ‘push-out and lever-out’ test data (and subcontract)
U Iowa FEA of 3D stress state of cup & bone
Basis for metrics in clinical outcomes studies (BMD; lysis)
BioVera, Inc.
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38. BioVera, Inc.
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RA Poggie, R Cohen, RG Averill, "Characterization of Porous Tantalum Metal, Direct Compression
Molded UHMWPE Junction", 44th ORS, March 16-19, 1998, pp 777.
JD Bobyn, "UHMWPE: The Good, Bad, & Ugly; Fixation and Bearing Surfaces for the Next
Millennium", Orthopaedics, Sep, 1999, Vol. 22 No 9, pp 810-812.
DR Pedersen, TD Brown, RA Poggie, "Finite Element Analysis of Peri-Acetabular Stress of
Cemented, Metal-Backed, and Porous Tantalum-Backed Acetabular Components”, The 45th
Orthopaedic Research Society Meeting, Anaheim, CA, Feb 1-4, 1999.
Alan S. Litsky, “Elimination of Cup-Liner Micromotion in Acetabular Components”, 25th Annual
Transactions of the Society for Biomaterials Meeting, Providence, RI, 1999.
JB Stiehl, Kenneth St. John, Richard Affilitto, Robert Poggie, ”The Trabecular Metal Monoblock
Acetabular Cup Biomechanical Characterization & Hip Simulator Wear Results”, 68th Annual
Meeting of the AAOS, Scientific Exhibit, Feb 28-Mar 4, 2001.
David G. Lewallen, “Use of Porous Tantalum In Total Hip Arthroplasty”, Harvard Hip Course,
Boston, MA, September 8-10, 2003.
R Lewis, A Unger, TJ O’Keefe, “Monoblock Trabecular Metal Acetabulum: 2 to 5 Year Results”,
Abstract and Poster, 70th AAOS, "New Orleans, LA", Feb. 5-9, 2003, poster 45 .
T Gruen, A Hanssen, D Lewallen, et.al. “Radiographic Evaluation of a Monoblock Acetabular
Component – A Multi-Center Study With 2 To 5 Year Results”, The Journal of Arthroplasty, Vol.
20, No. 3, April 2005, pp 369-378.
George A. Macheras, et. al., “Survivorship of a Porous Tantalum Monoblock Acetabular
Component in Primary Hip Arthroplasty With a Mean Follow-Up of 18 Years”, The Journal of
Arthroplasty 32 (2017) 3680-3684.
40. Case Example: Bodycad Uni-Knee
40
Patient specific Uni-Knee w/unique features. FDA
deficiency letter stated clinical study likely necessary.
Unique Features: bone resection method; FEA-calculated contact
area/stress for each implant; ancillary fixation on femur…
Planning, Literature, Data to establish substantial equivalence
and in turn aid marketing
Bone Resection – Literature and homegrown data to establish SE
of method and performance relative to perf reqs
Screw Fixation and Bodycad Software – Literature + homegrown
data to establish similar or better accuracy of implant position
ORL + Biomechanics R&D for validation of Bodycad FEA of
articulation contact data (Fuji film), and relative to ZUK
BioVera, Inc.
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41. K163700, Summary
41
The results of testing showed:
The fatigue strength of the Bodycad UKS tibial and femoral components withstood worst case
physiological loading.
ROM testing showed the Bodycad UKS to possess substantially equivalent motion characteristics as the
predicate devices and reported in the scientific literature for UKA devices.
Comparison of the tibial and femoral articular surfaces of the Bodycad UKS to the predicate devices, and
analyses of constraint, ROM, and contact stress/area of the Bodycad UKS, established substantial
equivalence to the predicate devices.
The screw trajectories for the femur and tibia were within the envelope of bone and not at risk of
perforation of bony surfaces. Evaluation and testing of femoral and tibial ancillary fixation in cadaver
knees and Saw Bones demonstrated substantial equivalence to the predicate and reference devices.
The UHMWPE material used in the manufacture of the tibial inserts was found to be in conformance
with ASTM F648.
Cadaver laboratory testing and evaluation of surgical fit to the plan (surgeon input and software) showed
the implants to fit and surgery to be completed to the patient-specific, prescribed plan. The cadaver
studies performed for the Bodycad UKS showed without exception that the patient specific implants and
instruments to fit as planned by the surgeons and Bodycad software.
The single-use cutting guides met the performance criteria and were validated for their intended use.
42. Published Data Used for SE
42
References, precision and accuracy of UKR, TKR devices (robots, CAS)
Smith, J. and Philip E. Riches. 2013. Accuracy of a freehand sculpting tool for uni-condylar
knee replacement, Int. J Med Robotics Comput. Assist Surg.
Clarius, M., et al. 2009. Saw cuts in unicompartmental knee arthroplasty: An analysis of
sawbone preparations. The Knee. 16: 314 -316.
Otani, T, et al. 1993. Cutting errors in preparation of femoral components in total knee
arthroplasty. J Arthroplasty. 8, (5): 503-10.
Ohmori, T., et al. 2015. The Accuracy of Initial Bone Cutting in Total Knee Arthroplasty.
Open Journal of Orthopedics. 5: 297 -304.
Mason, B. J., et al. 2007. Meta-analysis of alignment outcomes in computer assisted total
knee arthroplasty surgery. The Journal of Arthroplasty. 22, (8): 1097-1106.
Martinez-Carranza, N. et al. 2012. Deviation between navigated and final 3-dimensional
implant position in mini-invasive unicompartmental knee arthroplasty: a pilot study in 13
patients. Acta Orthopaedica. 83, (6): 625-628.
Karia M. et al. 2013. Robotic Assistance Enables Inexperienced Surgeons to Perform
Unicompartmental Knee Arthroplasties on Dry Bone Models with Accuracy Superior to
Conventional Methods. Advances in orthopedics.
43. Published Data Used for SE
43
S&N Visionaire White Paper …
Salehi, A. and C. Moore. 2011. Debris Testing of Visionaire Patient
Matched Cutting Blocs. Bone & Joint Science. 02, (9).
From Bodycad test report used for SE of this performance metric:
“A similar study was conducted on S&N’s Visionaire
instrumentation [1]. The Visionaire instrumentation is also
patient-specific are made of the same material as the Bodycad
Knee cutting guides, and are manufactured using the same
equipment and raw material (EOS system and medical grade
Nylon 12). The authors of the study reported an average
weight loss of 0.0062g, which is 34% more than that measured
with the Bodycad cutting guides. Salehi et al. concluded that a
weight loss of 0.0062g was negligible [1].”
47. Recap, Identify the ‘Data’
47
1. Identify same or similar devices to your product
2. FDA Website to ID 510(k) summaries, PMA dox, and
guidance documents as applicable
a. FDA website and search engines; FDA 510(k) summaries
w/data; scientific publications recap PMA data
b. Draft / list required data for your product
3. ISO and ASTM standards to define tests
4. Company Websites for papers and reference lists
5. Scientific Literature – PubMed, Google Scholar,
specialty-specific journals and websites
6. Homegrown plans and data; think beyond regulatory
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48. Recap, Judging Utility of Data
48
Methods and Materials clearly stated?
Based on consensus stds or industry / scientific norms?
Reputable journal or source? Publicly available?
Scientific publication of PMA data?
Product IFU and clinical function same or similar?
Statistical validity? In-synch with FDA-OK numbers?
White papers that appear obviously related to
regulatory testing to clear product?
Metrics / Performance – Did your product
outperform completion? W/statistical proof?
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49. Recap, Data Value to Your Work
49
Project Planning – Testing plans (cost & time) for:
Regulatory applications
Design and process validations
Scientific publications
Marketing
Published Data - Reducing cost and scope of testing
Alternative to testing predicate devices
Target values for device performance & regulatory
Marketing and Scientific Publicity
BioVera, Inc.
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