We first walked through the doors of UNC Children’s Hospital in 2009, scared parents who flew several states away to see an expert on our son’s rare disease.

Our son Case was two years old.

To him, the hospital wasn’t as cool as the Ronald McDonald House that we’d left. It had snacks, a playground, and a Ronald McDonald sitting out front.

As he would soon learn, the hospital, and a clinical trial, wasn’t nearly as fun either.

And as a clinical trial for a rare disease like Hunter Syndrome (also known as Mucopolysaccharidosis II), which affects only a few thousand patients worldwide, it would take a lot of work to gather the information someone would need to show whether the drug works.

He stood on scales over 100 times, had his blood pressure taken at least 300 times. He’s had over 80 spinal taps and 6 spinal port surgeries. He’s flown over 100 times and knows every nook and cranny of two airports, two hotels, and two hospitals. He knows hospital check-in staff better than his extended family.

I analyze all of his data, from the first blood pressure check at his first ERT infusion, to the differential diagnosis for each port failure, to every cognitive test he’s ever taken. It is the data set of n=1.

But for many years now, consultants, scientists, and media have been hawking the importance of big data. They’ve pronounced that we’ve finally entered the “era of big data.”

I contend that big data is all we’ve ever known.

This may be the era of bigger data, but it’s always been about big data. But we have yet to understand how to accurately gather, measure, analyze, and evaluate small data.

In the process of drug development and approval, it’s always been about the statistics, the p-values, the analytical models. Whether it’s drug companies or the FDA, or maybe it’s drug companies because of the FDA, a case-by-case approach has been shunned as not scientifically valid and too subject to bias.

It is systems and perspectives like that which allow clinical trials for complex, heterogeneous, rare diseases to not reach their endpoints, irrespective of whether a drug actually works. (See Shire Announces Top-Line Results for Phase II/III Clinical Trial in Children with Hunter Syndrome and Cognitive Impairment). But this system has been asking companies to prospectively imagine how to measure a world that has never existed, especially in the case of progressive and neurodegenerative diseases like Hunter Syndrome.

But if small data matters too, if the answer is truly does a drug work for a particular rare disease, then we have to focus on better science on how to measure, capture, and analyze small data.

Is it individual patient controls? Is it matched external controls? And what happens when we all recognize that rare disease trials must be designed differently mid-stream in a nine-year drug development program?

At Project Alive, we’re working with all of the relevant constituencies – patients, industry, scientists, and regulators – to answer those questions and to find better ways to look at data in Hunter Syndrome clinical trials.

Small data matters. How to measure, capture, and analyze small data matters too.

Because my son’s life depends on it.

Melissa Hogan is president of Project Alive, a rare disease writer, speaker, and advocate.


March 28, 2018
Photo: Case Hogan and his growth chart

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