FDA CDRH leading patient preferences in regulatory decisions – personalized medicine here?

Personalized medicine has been a vision for quite some time, but may be gaining momentum with Patient Preferences Information (PPI) guidance.

For years patients have served as non-voting advocates on panels and other FDA, NIH and CMS workgroups, to bring the patient perspective to decisions.  Even patient advocacy groups for AIDS and MS made significant efforts to push forth medical innovation for their unmet needs.  Yet with one patient representing the voice on a panel, it is still n=1.  Patients may clinically, demographically and culturally "look" the same, but they often have different preferences regarding the risks and benefits of their medical care and lifestyle.

This week FDA released a Draft Guidance on Patient Preference Information (PPI). Though a Draft Guidance, the principles have already been put use at FDA CDRH with the Maestro Rechargeable System approval. The patient preference study obtained quantitative patient preference information, which allowed the regulatory approval decision for certain obese adults.

 

Patient preference is not black and white, nor something that can be ranked on a scale for an absolute number.  Often it involves weighing contradicting factors or risk and benefit, and mapping out the range of preferences using tools such as a risk matrix.  For these reasons studies, as the one used in the obesity study for Maestro device, can assess target populations preferences. This can play a critical role in getting devices approved.

Historically FDA CDRH approved devices on the impact to the total patient population.  When the safety performance of the device relative to the risk was less precise (such as those that have a high benefit but also a high risk, or low benefit but also low risk), the devices were often not approved.

By adding PPI to the decision, there is the ability to segment the population and approve devices for those patients who prefer the high risk / high benefit options, or lower risk/low benefit options.  This also allows patients with unmet needs to have their voice formally added to the device approval.  Thus in many ways we can see the start of quantifiable and scientific methodology for personalized medical devices.

These PPI studies are not required by FDA CDRH, they are voluntary. But they are an opportunity for devices that had historically struggled for approval or not considered viable as only a small segment of patients desired the products.  Thus it opens the door to potentially more device approval, with constraints on the target population.

This also allows those devices that are approved, to collect devices performance information from real-life market data, to better tune the risk and safety profile.  If the evidence of the device lowers the risk profile, it then becomes possible to expand the indication.  This ultimately is what regulatory science is about.  Data driven decisions, information over time expanding our knowledge and allowing decisions to be re-evaluated based on facts. 

Many companies already embark on PPI to define their design and target their market segment.  To formalize the PPI becomes more valuable throughout the medical device lifecycle. During the early design /concept phase, PPI may be more qualitative data.  As the product matures with greater safety and effectiveness performance specificity, PPI becomes quantitate data, to complement the safety and effectiveness in the regulatory decision.

Keep in mind the studies may not be relevant to all devices, such as surgical tools for providers, or high risk / low benefit devices.  Thus FDA released the Draft Guidance.

The objectives of the Draft Guidance:

1) Voluntary submission of patient preference

2) Recommended qualities of PP studies which may be valid scientific evidence

3) Recommendations for collecting patient preference information

4) Recommendations for including patient preference information in labeling for patients and health care professionals.

While the Guidance identifies about a dozen qualities of Patient Preference Information studies, the following 5 were highlighted during the kick-off at The PEW:

1) Representativeness

2) Heterogeneity

3) Minimal cognitive bias

4) Effective Communication

5) Robustness of Analysis of results

Use ClearRoadmap Benefit/Risk Pathway, to learn more about the details of the Draft PPI Guidance, other FDA sponsored patient centered benefit risk framework information with resources, and patient advocacy information.  Register for an account, and first time users take advantage of the savings with our Introductory Offer.

-- Vizma Carver, Founder and CEO, Carver Global Health Group

vizma.carver@cg-hg.com
www.clearroadmap.com