Precision Medicine at one year: A soaring White House summit and the potholes ahead (report)
We’re pleased to publish the following guest post by Dr. Michael Joyner, a medical researcher at the Mayo Clinic who recently joined our team as a contributor. These views are his own. You can follow him on twitter @DrMJoyner.
Last week there was a big shindig at the White House reviewing progress from the first year of the million-person Precision Medicine Initiative (PMI).
As you might imagine, an event of this magnitude drew considerable (mostly glowing) coverage from major US health news media:
- Washington Post: White House to mark a year of effort on precision medicine initiative. Excerpt: In a briefing with reporters Thursday, NIH Director Francis S. Collins called the effort “the largest, most ambitious research project of this sort ever undertaken.”
This is an exciting scientific undertaking — one that merits the attention these outlets have devoted to it. But the coverage sounded mostly like cheerleading, and none of these stories included a skeptical word about the many challenges ahead and how they could thwart the initiative’s lofty objectives. I watched the webcast of the event with a critical eye and took notes as I was watching. Here are a six of the things that I thought journalists should have been thinking about and writing about as they covered the event:
1) A number of new partnerships and pilot programs related to enrollment of participants, data sharing, analytics, biobanks and privacy were announced. There are no real results yet, so it is simply too soon to tell what elements of what was announced will succeed, partially succeed, or stall.
2) Francis Collins, the director of the National Institutes of Health and a prime mover in Precision Medicine, clearly stated that it should take three to four years to meet the one million person enrollment goal of the program. This is an ambitious timeline. The last time that something like this was tried in the National Children’s Study, enrollment goals were never met and the program was ultimately cancelled. As STAT has previously reported, experts in population health have observed similarities between the PMI and the National Children’s Study and the comments by Dr. Collins are a clear marker for evaluating the success of PMI going forward.
3) There were a number of interesting presentations of patient and family vignettes at the meeting. While PMI is supposed to transform health and healthcare for all Americans, three of the four stories were about extremely rare diseases that have nothing to do with the big killers like diabetes, cancer, and heart disease. There is no argument by PMI skeptics about the role of gene sequencing in rare diseases, but dealing more effectively with those diseases has nothing to do with the prediction, prevention, and improved treatment of the major causes of death. The fourth presentation was about breast cancer and it was unclear to me exactly what elements of precision medicine were involved in the care of this patient (who happened to be a surgeon). In the absence of big transformative population findings for common diseases, some might argue that the rare disease community is being leveraged to generate support for a much larger and perhaps misdirected program.
4) There was no mention of some of the potholes that are out there or that have emerged in the last year. For example, the National Cancer Institute’s MATCH trial, designed to match the genetic signatures of tumors with targeted therapy, is having trouble “matching” (subscription required). And a study from Europe has cast at least some doubt on just how effective broad-based used of “targeted therapy” will be. There is also plenty of room to question the idea that data mining electronic health records is going to be transformative. The barriers to actually getting this done are significant and range from the quality of the data in electronic health records, issues related to who owns the data, protocols for data sharing, and a host of technical and statistical issues. Big data can certainly be helpful but it can also mislead.
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