Is the Precision Medicine Initiative really necessary?

President Obama introduced the Precision Medicine Initiative during his State of the Union address in January. The goals of the initiative are to harness not only the power of advanced genomic sequencing but also of a million-patient cohort and to develop new methods for managing and analyzing large data sets that could accelerate biomedical discovery.

National Institutes of Health Director Francis Collins wrote in the New England Journal of Medicine in February, “What is needed now is a broad research program to encourage creative approaches to precision medicine, test them rigorously and ultimately use them to build the evidence base needed to guide clinical practice”.

But launching such an ambitious initiative will not be straightforward.

Critics of the initiative point to several significant barriers. First are the strict privacy rules guarding individual health information. To conduct the large-scale genomic studies required for achieving the initiative’s goals, information about patients and their genomic data sets must be encrypted and anonymized. A second obstacle is lack of communication between scientists and hospitals. Robust mechanisms for scientists to share big data with doctors do not exist, and there even remain major barriers to sharing electronic patient health records among medical doctors. Finally, finding a million volunteers willing to relinquish their genetic information could be challenging.

Obama's fiscal 2016 budget sought $215 million for the initiative. In response, the U.S. House of Representatives and the U.S. Senate proposed $200 million in their appropriations bills. Under the austerity of the Budget Control Act, these funds will need to be taken from other programs. This could jeopardize critical research in other important fields.

Is it really necessary to have the PMI to advance methods for managing and analyzing large data?

Independent investigators can propose and pursue big-data research questions through already existing funding mechanisms. For example, Wladek Minor at the University of Virginia received an NIH Big Data to Knowledge grant to develop a management strategy for the archiving of X-ray diffraction raw data and an online portal to gain access to it. Minor was concerned about the massive amount of raw data generated in his field that goes unpublished. His lab and others in the field generate so much data that they simply cannot keep up with publishing it all.

“What we propose is to build the system to keep all diffraction data (and) structural data. People are saying to do that would cost millions of dollars in equipment. And our request for equipment was $20,000. Why? Because we use the newest technology, and we are building computers by ourselves quite often. Not because it’s cheaper, but because we can create something (that) is better than what you can buy” (Augusta Free Press).

Creating a resource for preserving this raw data will allow other scientists to gain insight from experiments that otherwise might have gone unpublished, and developing a management strategy for wrangling massive data sets advances the field of big data.

While the NIH grapples with privacy laws, communication strategies between scientists and doctors, and securing funds for the PMI, Alphabet’s Life Sciences (formerly a part of Google X) has waltzed casually into the conversation and announced its intention to explore the promise of precision medicine. In addition to developing a glucose-sensing contact lens for diabetic patients, the Life Sciences team has been working with a committee of scientists from Duke University and Stanford University to design what they're calling the Baseline Study. The Baseline Study will collect anonymous genetic information from 10,000 people to create a baseline picture of what a healthy human looks like on a molecular level. The study is unlikely to face many of the privacy and interoperability challenges of the PMI. If participants buy in, Life Sciences could provide both the medical and technological advances of processing and utilizing genomic data from a large patient cohort, and the Baseline Study could deliver the type of technological advances sought by the Precision Medicine Initiative without additional federal investment.

The NIH’s Big Data to Knowledge program already is delivering advances in data management. Life Science’s Baseline Study appears poised to leverage advanced genome sequencing to enhance our understanding of health. Bogged down in privacy laws and funding battles, the PMI may not even be necessary.

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