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Case Study: How Patient Preference Data Rescued a High-Risk Device

Imagine you are running a pivotal clinical trial for a novel implant. The data comes back, and it is rough: 80% of your patients have suffered a serious adverse event, and 40% have developed acute kidney injury.

If you are sitting in the regulatory or risk management seat, you are likely drafting the project’s post-mortem. In a traditional risk management paradigm, you are preparing to tell the executive team that the device failed to meet any traditional safety threshold.

But what if the FDA didn’t just approve this device, but approved it specifically because the sponsors mathematically…

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