This document provides an overview of clinical science for medical devices aimed at entrepreneurs. It discusses the importance of clinical studies to prove a device is safe, effective, and provides value. Key elements that are always part of clinical trial design are the patients in the study, the treatment being evaluated, and the outcomes being measured. The presenter emphasizes minimizing bias in studies and having an a priori analysis plan. Other topics covered include informed consent, oversight boards, executing studies properly, interpreting results, and lessons from experience. The goal is to help entrepreneurs appreciate the value and complexities of clinical research.

1. Clinical Science for Medical Devices:
A Guide for Entrepreneurs
20 October 2017
Jim Gustafson
Former Senior Vice President
Clinical Science and Regulatory Affairs
MEDRAD Interventional / Possis

2. Outline for Today
1. Purpose and Planning
2. Elements of Trial Design
3. Add in the Science!
4. Patient Rights
5. Trial Execution
6. Finishing Well
7. Clinical Science Wisdom
8. Q&A

4. 35+ Years Doing Medical Device Clinical Science
• Class III cardiovascular and ophthalmic implants and therapies
• Always on the Manufacturer’s Side.
• Career path: Clinical Monitor → Sr. Clinical Scientist → Manager →
Director → VP → Sr VP, Clinical and Regulatory Affairs.
• ~ 10 IDE trials, each with 100’s of patients enrolled at dozens of sites
• 1 original PMA approval, based on 6 protocols enrolling 1,100 pts.
• 4 510(k)s involving IDE clinical trials (each > 100 pts and > 10 sites).
• ~ 10 PMS studies (each > 200 pts and > 10 sites).
• ~ 7 large marketing clinical studies.
• Many negotiations with FDA on study design, outcomes, and proofs.
• 3 live presentations to FDA Advisory Panels.
• Watched a bad clinical trial almost kill my company, then led the
successful effort to revive it with new and better clinical trials.

5. What Won’t Happen Today:
• Tell you if your medical device needs
a clinical study.
• Design a clinical study for you, or
give you a template for doing so.
• Explain everything about clinical
studies for medical devices.
• Make you an expert in clinical
studies for medical devices.
What I Hope Will Happen:
• Appreciate the importance and value
of clinical studies.
• Respect their complexity, yet know
they can be successfully managed.
• Learn the basic elements of clinical
science for medical devices.
• Know what questions to ask to be a
successful medical device
entrepreneur when clinical science is
involved.

6. 1. PURPOSE AND PLANNING

7. Why Do Medical Device
Clinical Science?
To prove that the device
• Is safe.
• Is effective in a clinically meaningful way.
• Has desirable health economic characteristics.
• Has other desirable features: convenient, easy to use,
compatible with other equipment, devices, and treatments in
the use environment, etc.

8. What Do We Do with This Proof
• Get regulatory approval.
• Obtain favorable 3rd-party reimbursement.
• Show advantages compared to other treatment options.
• Change health care decisions.
• Other?

9. Types of Medical Device Clinical Science
• First-in-Human (FIH) to confirm the
device works in humans.
• Feasibility study to confirm target
patients and endpoints.
• Pivotal trial to prove safety and
effectiveness.
• Post-marketing surveillance study for
long-term effects and rare events.
• Marketing study: preference, pricing,
use characteristics, etc.

10. 2. ELEMENTS OF CLINICAL TRIAL DESIGN

11. Clinical Trials are Always About 3 Things
Patients
Treatment
Outcomes

12. 1. Patients
• Which patients will most
likely benefit?
• How can you describe
them objectively?
• Which patients should be
excluded?
• How can you find the
patients you want?

13. 2. Treatment
• What treatment will be
applied?
• Can it be applied
consistently applied to all
enrolled patients?
• Can it be made the only
variable to drive
outcomes?

14. 3. Outcomes
• Effectiveness
• Safety
• Clinical Utility (value)
• Health Economics
• Other?

15. Audience Participation
What three things
are clinical studies
always about?

16. 3. BUT TO THESE
THREE, ADD IN THE

17. Essential Scientific Elements
1. Define Endpoints
2. Minimize Bias
3. Commit to an A Priori
Analysis Plan

18. Study Endpoints
Endpoint: any clinical effect potentially due to the
treatment under study. Good study endpoints are:
• Objective and quantifiable.
• Meaningful to the patient and the doctor.
Primary Endpoint : the single most important
outcome measured after treatment. Used to
• Formulate the formal hypothesis.
• Calculate the sample size.
• Interpret the outcomes.

19. Clinical Endpoint
Directly measures how a patient feels,
functions, or survives. Examples:
• Heart-attack free survival at 1 year.
• No repeat surgery to 6 months.
• In-hospital mortality.
• Limb loss.
Surrogate Endpoint
Measures something that robustly
predicts a clinical outcome, even if the
patient does not feel it. Examples:
• PSA for prostate cancer.
• Reduced blood cholesterol.
• A1C for diabetes.
• Imaging results, e.g. CT, MRI, angio

20. Bias in Clinical Science Comes in Threes
• Selection bias: selecting the wrong kind of patient, or
only a narrow subset of the right kind. Minimize by:
• Defined, objective enrollment criteria.
• Non-enrollment logs.
• Treatment randomization or other active controls.
• Treatment bias: giving different treatments to different
groups of study patients. Minimize by:
• Protocol-defined treatment that follows standard care.
• Site training and monitoring.
• Observation bias: scoring patient outcomes differently
based on treatment received. Minimize by:
• Objectively defined endpoints.
• Blinding the observer.

21. Types of Study Control Groups
Active Controls:
• Randomized cohort.
• Cross-over control.
• Non-randomized concurrent prospective
reference group.
Passive Controls:
• Matched case samples.
• Site history.
• Literature controls.

23. Parables of an A Priori
Analysis Plan
• It’s not fair to shoot your arrow, and then
paint your target around where it sticks.
• It’s also not fair to move the target while
the arrow is in flight.
• “3 out of 5?” and “4 out of 7?” aren't
acceptable in clinical science.

24. Statistics

25. Wisdom for Clinical Study Design
• Prospective beats retrospective.
• Controlled beats uncontrolled.
• Randomized is the best kind of control.
• Superiority beats non-inferiority.
• Clinical endpoints beat surrogate endpoints.
• Death is the best clinical endpoint:
• Once per patient.
• Cheap and easy to measure.
• No arguments about whether the patient is really dead.
• Bonus: In-hospital death is the hardest endpoint: if you
die in a hospital, you have to really work at it.

26. 4. PATIENT RIGHTS

27. Benches have no rights.
Animals have some.
Human patients have many.
Your clinical study design must be
reasonably certain to produce
scientifically valid outcomes about your
device, but never at the expense of
patient rights, welfare, or safety.

28. Informed Consent
• Requirements found in 21 CFR 50.
• Equivalent to the Declaration of Helsinki (1975).
• Before study enrollment, signed by patient or
patient’s representative.
• There is a difference between consent to be treated
and consent to participate in a clinical study!

29. Elements for Study Informed Consent
1. The consent is for
research.
2. List foreseeable risks
and discomforts.
3. Possible benefit to
patient or others.
4. Degree of confidentiality.
5. Compensation or
treatment for injury.
6. Who to contact with
questions.
7. Participation is voluntary;
patient may quit.
8. Alternative tx available.
9. Additional costs, if any, to
patient.
10.Investigational consent is
separate from treatment
consent.

30. Institutional Review Board
• Requirements found in 21 CFR 58.
• Represents local standards of hospital
and community.
• Review and approve protocol, patient
consent, and any changes to them over
time.
• Increasingly, IRBs also review grants,
CRFs, etc.
• Must receive minimum yearly reports
from investigator and sponsor.
• EU equivalent is Ethics Committee.

31. Data Safety Monitoring Board
• Medical and statistical experts
independent of the trial who review
blinded outcomes at pre-specified
intervals.
• Look for evidence trial continuation is
not safe or is unnecessary.
• Has authority to discontinue the trial,
or change it to improve safety or
scientific soundness.

32. 5. TRIAL EXECUTION

33. Executing Well
Best-laid plans are not enough.
Execution covers many areas that are not
required by regulation, where FDA does not
provide oversight. But inadequate execution
can wreck a clinical study!
• Protocol and CRF development.
• Site and investigator selection and training.
• Field monitoring.
• Standards for clinical data quality and
reporting.
• Data processing and analysis.

34. Data Integrity
When the study is over, all you have
to show for it is the data. Dataset
integrity is essential to a successful study!
• Source document audits.
• Completion and correction tracking forms.
• Computerized data checks.
• Double data entry.
• Database validations.

35. Bonus Round: Why is
Pt Enrollment So Slow?
• Study selection criteria are too narrow.
• Investigator is involved in competing trials.
• Investigator hates the control (or the device!).
• Grant is too small.
• Study coordinator has other priorities.
The surest way to cure a
disease is to start a study of it!

36. Myths of Study Time and Cost
Time: often patient enrollment is not the biggest calendar
time cost for a study. Consider instead:
• 6 months for site selection, approval, training, etc.
• 12 months for follow-up on the last patient enrolled.
• 6 months for dataset prep and report writing.
Cost: grants for patients enrolled is often not most of a
study’s budget. Instead, most of the costs are study-wide,
not patient dependent: database design, protocol
development, site monitoring, etc.

37. 6. FINISHING WELL

38. Interpreting a Clinical Study is Still
Always About the Same 3 Things
Patients:
• What patients were actually enrolled?
• Do the results apply to a more general
population?
Treatment:
• Was the treatment received the only
significant variable?
• Did the treatment drive the outcomes?
Outcomes:
• Were the endpoints clinically meaningful?
• Are the outcomes compelling?

39. Interpretation
The right study design and
interpretation lets you say something
like “a multi-centered observer-blinded
randomized trial of early-presenting
STEMI patients with large-thrombus
lesions showed reduced MACE at 30
days in the treatment arm as compared
to the control arm.”
And what could be
more fun than that?

40. Some Key Interpretive Questions
• Is the enrolled patient sample a fair
representation of the target population?
• Are the treatment and control cohorts well-
matched at baseline?
• Are the endpoints really susceptible to the
treatment received?
• Are the treatment group outcomes really
different?
• What else besides treatment received could
affect outcome?
• Do the primary and secondary endpoint
outcomes conflict?

41. Have a Plan for Going Public!
Presentations:
• Medical congresses
• Late-breaking results
• State-of-the-arts
• Sponsored sessions
Publications:
• Academic or professional or business?
• Peer-reviewed or other?
• High-level, mid-level, or low-level?
• Sponsored supplements?

42. Actionable Interpretation
“I recommend the meatloaf.
It’s just received FDA approval.”

43. 7. CLINICAL SCIENCE WISDOM (?)

44. 1. Clinical studies are done by teams, not individuals:
clinical science, statistics, regulatory, medical,
device. etc.
2. Your clinical science project is just the last, longest,
most expensive, and most fraught step in your
design validation process.
3. Unlike bench testing, clinical science is done not by
sponsor employees, but by contractors (doctors
and hospital staff). They have many other priorities
higher than your study, and you can’t change that.
4. Just as you can’t inspect quality into a product, you
can’t wash the dataset from a compromised clinical
study to make it better. Clean trash is still trash.

45. 5. More medical devices have been shown to work
than have been proven to work.
6. The surest way to cure a disease is to start a
study of a new treatment for it – suddenly all the
patients disappear!
7. Medical device clinical studies are designed by
optimists, and interpreted by pessimists.