The future of pediatric precision medicine: opportunities, barriers

“Precision medicine” looks to be heading down the same path as “big data” and “innovation”: The term is becoming so widely used that it threatens to detract from the real impact it is already having in patients’ lives.

But for children, who are still developing and have the most to gain, precision medicine is more than a bumper sticker. On the micro scale, early genetic testing—perhaps routinely, someday, in newborns—can help guide medical care, targeted therapies and preventive strategies based on a child’s genetic makeup. On a macro scale, big data from the larger population becomes a predictive tool, guiding medical decisions that could be life-altering in a still-malleable child.

“If you can make an early diagnosis, you can amplify the effects of what you do, rather than try to change the highways once they’re built,” said Wendy Chung, MD, PhD, of Columbia University Medical Center during a panel discussion last week at Boston Children’s Hospital’s Global Pediatric Innovation Summit + Awards (#PedInno15).

Precision target-shutterstock_267343580The panelists cited many potential and emerging applications of precision medicine:

  • A subtype of medulloblastoma, the most common malignant childhood brain tumor, has a genetic fingerprint predicting a milder course; in children with this pattern of gene expression, less chemotherapy could be more.
  • Rare disease: “I think if there is a low hanging fruit in medicine, it’s definitely in rare genetic disorders, because they’re just one gene at a time,” said panelist Matthew Might, PhD, a parent and citizen scientist who considers his son Bertrand to be one of the first precision medicine patients.
  • Autism is estimated to have more than 500 different genetic causes, with more still being discovered. “There’s probably more than one neural mechanism, and it’s likely there’s going be more than one therapy,” said Chung.
  • Sore throat: Population health data can help predict whether a child’s sort throat represents a strep infection. “In a project with Minute Clinic, looking at millions of cases, we found that if you adjusted therapies for whether there is strep in the area, you could save hundreds of thousands of antibiotic courses per year,” said Kenneth Mandl, MD, MPH, director of the Boston Children’s Computational Health Informatics Program.

The panel also took on the many challenges in realizing precision medicine’s full potential and scaling it to whole populations. Among the barriers they cited:

Cost concerns

Is there enough money in the pool if everyone has their genome sequenced and tries to act on the findings? asked Gregory Steinberg, MD, head of clinical innovation at Aetna, Inc.

“There is a real threat that if this is not handled properly, you fiscally blow up the health care system,” Steinberg said. “It’s $350 billion straight off to have everyone’s genome sequenced, and then many people will want subsequent add-on testing and downstream treatment. Until that process is understood and shepherded intelligently, you’ve created a real potential problem.”

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From left: Nicole Fisher (moderator), Might, Chung, Mandl, Church, Verhelle, Steinberg (Katherine Cohen photo)

But other panelists argued that routine genomic sequencing would save money, avoiding unnecessary biopsies and other tests and allowing patients to take disease-preventing measures.

“The payment models are going to have to vary,” noted Mandl. “The medical system is reimbursed handsomely for every diagnostic test and procedure; sequencing is something you do just once.”

George Church, PhD, of Harvard Medical School & MIT argued that costs — and inappropriate use of genomic data — are easily contained through regulation. “Every newborn screening includes testing for PKU and 40 other things,” he says. “The results have to be actionable. You don’t test for Alzheimer’s. You can get your money back right away as long as you’re tough about drawing that line.”

The cost of developing new drugs to hit the precision targets — and their pricing — was another concern. In diseases like cystic fibrosis, each mutation causing a disease may need a separate drug. Of course, the pricing must be weighed against the lifelong cost burden of the disease, panelists noted.

Might called for more effort around repurposing existing medications. “If the cost of developing a new drug stays around $1 billion, we’ll never get a cure for all these diseases. In the short term, we have to look at leveraging the drugs that have already been approved.”

Data sharing

Making genetic associations requires large data sets. “The more we know, the more we understand the mechanism, the faster we can develop a drug,” said Dominique Verhelle, PhD, MBA, strategic advisor at Third Rock Ventures.

barriers to precision medicineHowever, as Might noted, there are academic incentives against data sharing: researchers hoard and silo their data so they can be the ones to publish it.

Privacy regulations are another barrier that can be convenient for institutions to hide behind.I’m still denied access to my own exome, which means we can’t do studies to look for modifiers of [my son’s] phenotype,” said Might.

Mandl pointed out that who “owns” a patient’s exome remains unclear. “This is definitely a barrier to sharing,” he said. “It’s why you see patients sharing data completely independently of the health care system, and they’re getting things done that way.”

A pediatric orthopedic surgeon in the audience commented that privacy regulations limit his ability to guide families of patients with complex deformities. “The information often comes from other families; it’s not available to me,” he said. “Yet the information is out there on the internet, for everyone else to look at.”

Moreover, there’s a divide between research and clinical care that can be difficult to breach. “When we have a new outcome related to a therapy, or an adverse event, there’s an assumption among the public that the health system is learning from that and the next patient treated will get treated differently,” noted Mandl. Too often, that isn’t the case.

Data interpretation

While many of the technical issues in sequencing the genome have been solved, there are still no standard practices for interpreting the results and highlighting clinically relevant findings for patients and physicians.

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“We can’t interpret all those genomes — we get some information, but I can’t squeeze everything out of it,” said Chung. ” I’m good at the genetics of patients of European heritage, but I suck right now, to be honest, if you’re one of my Dominican or African American families. We are still in a learning phase.

“This is a cyclical, iterative process,” she added. “Your genome hasn’t necessarily changed over time, but our interpretation is going to change.”

A particular challenge is characterizing phenotypes — the clinical characteristics of a disease — in a standardized way to draw appropriate gene–disease correlations. This challenge is going to require big data, Chung said.

Audience members also noted the need for more genetic counselors trained in genomics to keep up with patient interest in sequencing. “There are not enough genetic counselors now because they don’t get paid well,” said a medical geneticist. “It’s a labor of love.”

In many ways, genomic precision medicine is already happening successfully, as in the highly successful newborn screening program and challenges like CLARITY Undiagnosed. Church noted that much of the value from precision medicine will come through counseling and prevention rather than new drug therapies, and that might be a better allocation for spending.

“Breakthroughs in cancer have been more in prevention than treatment,” he said. “Medicine is about what we can do, not what we can’t do.”

Watch video highlights of the 2015 Global Pediatric Innovation Summit + Awards.