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Series: Precision Medicine for the Patient–Consumer

ICON Views
Series: Precision Medicine for the Patient–Consumer
Part Two: Beyond Biomarker-based Patient Stratification

By Vicki Anastasi

Precision medicines can command premiums, in part due to the preferences of providers, opportunities afforded to payers, and the rising influence of the patient–consumer.

This series is dedicated to assessing a gamut of strategies for bringing precision drugs, devices, and diagnostics to market. In the first instalment, we explored emerging biomarker-based approaches, from genomics to wearable sensors.

In this instalment, we will explore the potential of stratifying patient populations through an alternative strategy: patient preference information. These data may be more valuable than they first appear, in part due to emerging regulatory precedent.

New precision paths to approval

A remarkable evolution in the recent past has been the U.S. Food and Drug Administration’s decision to consider patient–consumer preferences for product approval and labelling.

The FDA set a new precedent in January 2015 by approving EnteroMedics’ Maestro® Rechargeable System, an implantable device for weight loss. The device missed its weight loss endpoint in its pivotal trial; the experimental group needed to lose 10% more excess weight than the control, but lost only 8.5%. However, the device was approved in part because a patient preference survey indicated that a subset of eligible patients were willing to accept the risks of the device in exchange for prolonged weight loss. For this device, the patient preference survey instrument became means to not only obtain approval, but to also generate a precise label with risk-benefit information for a well-defined stratum of patients.

Later in 2015, as part of its Patient Preference Initiative, the CDRH formed its first ever Patient Engagement Advisory Committee and issued a draft guidance on patient preference information (PPI). PPI is defined by CDRH as “qualitative or quantitative assessments of the relative desirability or acceptability of attributes that differ among alternative or diagnostic therapeutic strategies.” [For a discussion of patient preference methods and how they differ from patient-reported outcomes, read this ISPOR paper.]

Through this guidance, the agency encourages voluntary submissions of PPI with PMAs, HDE applications, and de novo requests, as well as the inclusion of PPI in device labelling. The guidance also provides considerations for the design of scientifically rigorous PPI collection tools, as well as examples illustrating how PPI aids in the FDA’s assessment of a device’s risk-benefit profile.

Patient preferences in protocol design and product development

Patient preferences may also provide an alternative vehicle to stratify patient populations and thereby enhance the efficiency of a product’s development lifecycle, from prototyping to trial design.

Currently, the Medical Device Innovation Consortium (MDIC), a public-private partnership between the FDA, NIH, CMS, industry, and patient advocacy groups, has adopted this philosophy and is developing standards for defining PPI and employing the data in clinical trials. MDIC has catalogued methods for collecting PPI through the entire product lifecycle and created a framework, called the Patient Centered Benefit-Risk Assessment Framework, that guides the incorporation of those methods into protocol designs and regulatory submissions.

MDIC’s research operates under the principle that incorporating PPI into clinical trial design enhances not only the appeal, but also the benefit of trials to the patient-consumer. PPI-focused trials offer more value to the patient-consumer because they incorporate the patient-consumer’s own opinions into the trial design and therefore give the patient-consumer more control over their own treatment and overall lifestyle.

Based on their research, MDIC has outlined several benefits to collecting and utilising PPI in clinical development:

First, MDIC argues that PPI can be useful in maximising the efficiency of a protocol’s design.  Personal risk tolerance and benefit evaluations can identify potential heterogeneity among patient perspectives, as well as subpopulations that would be more willing to accept a risk-benefit trade-off. This information can provide grounds for certain trial enrolment criteria and help to refine primary and secondary endpoints, thereby enhancing a trial’s utility for building a case for why certain patients may benefit from a technology over alternatives.

Another key application of PPI, according to MDIC, is to inform investigators of design limitations that affect a target population, providing an opportunity to refine and improve the product before a first-in-human application. Patient feedback can inform, for example, patient-sensitive design controls in early prototyping, pre-clinical design verification testing, and the design of user instructions, thereby enhancing the product’s benefit and appeal to the consumer.

MDIC also suggests that more products will reach the market if patients’ willingness to use the product is factored into the final assessment of the product’s regulatory burden.  Information regarding a patient’s willingness to trade a certain level of risk for certain benefits, in particular, can help reviewers frame decisions based on a the patients’ needs. Ultimately, this information can be used as evidence in support of a product’s approval.

Finally, MDIC’s standards aim to clarify how PPI can supplement clinical data during reimbursement discussions.  PPI can elucidate how patients process risk-benefit information, providing manufacturers and regulators insight into how to best to relay that information back to patients and to payers. The data can also enhance a developer’s decisions about the scope of product launches and reimbursement.

While the use of PPI in clinical trials is still in early stages, the MDIC’s extensive patient preference data initiative indicates a range of PPI applications can enhance the development of a precision medicine or device.

Patient-centric trials

The impetus behind collecting patient preference information is to produce medical devices that better meet patients’ needs, as well as to collect data that build a case for regulatory approval and reimbursement. Patient engagement continues to be a strategic priority of CDRH and ultimately reflects the industry’s shift toward patient-centric trials.

The next instalment of this series will focus on apps and other technologies that interact directly with patients not only to personalize their experience of healthcare and clinical trials, but also to catalyse new relationships with device manufacturers.

 

Vicki Anastasi
Vice President and Global Head
Medical Device and Diagnostics Research, ICON plc