Precision Medicine Will Digitize Humans, But Who Pays?

In a serendipitous confluence of events, I was finishing the 2013 edition of Eric Topol’s book, The Creative Destruction of Medicine: How the Digital Revolution will Create Better Health Care,1 while attending the NoSQL NOW! conference on modern technology in database engineering (August 20–22, San Jose, CA). Both have an impact on bioinformatics and science-based medicine. Topol’s book lays out the tremendous investment in infrastructure, primarily information technology, that will be required for next-generation medicine. For clarity, I’ll refer to this as “new medicine” since “precision medicine” has another, more focused, meaning and is only part of Topol’s thesis. “Old medicine” is the current state of the art and predecessors.

Just a year ago, at NoSQL NOW! 2012 in San Jose, I left the symposium with the impression that new medicine was a vision that would be difficult to reduce to practice, since the sheer scale of the data files and their dynamic structure were beyond the capability of existing IT. Well, Ed Snowden’s release of the humongous scope of NSA’s data gathering showed that I’d naively sampled the wrong technology segment. According to a speaker from Objectivity, Inc. (San Jose, CA), one client in the U.S. government has at least one system capable of adding 450 TB of information per day. The server farm has half a million multicore servers. Cloud-based commercial firms also claim limitless scaleability. There are still choke points, including transmission of very large data files such as genomes to and from the cloud. However, IT seems to be much less of a constraint in 2013. The last sentence in Topol’s book advises, “Think big and act bigger!” He does think big.

Science is a third essential required element for new medicine. Topol gives numerous examples of how the various “’omics” initiatives are starting to unravel the mechanisms of life on the molecular level. Many of our subscribers are involved in the genomics, proteomics, lipidomics, microbiomics, etc. ’Omics, including systems biology, should improve health by providing the science supporting the prognostic, presymptomatic personalized health plans. These should avoid many diseases.

Illnesses will arise and accidents will happen, but the response should be precision medicines prescribed on the basis of matching the drug to the disease, consistent with the idiosyncrasies of each patient. The results from research labs will trickle in over many decades, perhaps centuries. Informatics systems and health-care providers will need to accommodate and respond to daily updates.

So what could new medicine look like? Eric Topol, MD, describes a nirvana for new medicine. Anticipatory: Patients and health-care providers would work as a team to assess future risks. The patient will often know more about his/her history, family history, and conditions than the provider. Predictive: Costs can be reduced and health can be improved if each patient’s genome and transcriptome are digitized and analyzed. New correlations would be added as they are made. These can lead to anticipation and informed avoidance of developing conditions as above. Personal: The patient will be treated as an individual in contrast to mass screenings and blockbuster drug business models. Precise: Based upon the patient’s history, including genomic sequences, the patient would qualify for certain drugs that target the disease as rifleshot, compared to today’s shotgun, approach. The mantra is: “Deliver the right drug in the right dose at the right time.”

The 2012 edition of the book stiches together a large collection of anecdotal information describing the current state of health care, along with the author’s vision for improvements. For example, whole genome sequencing will be utilized to classify cancers by the mutations rather than the original site. The 2013 paradigm is, “It’s the mutation, stupid!” Plus, sequencing will identify genetic diseases. Guided by sequencing DNA and RNA, therapies will be based upon targeting mutations such as BRAF and ALK rather than the location of the primary tumor. This has been effective in several recent cases.

Dr. Topol expects that one’s genome will show predisposition to many diseases, including diabetes, arthritis, and hypertension. Two problems occurred to me: First, there is no reference human genome. Each is different. At the Mayo Clinic, they are sequencing 200,000 people to create a composite reference. One can expect to compare patients with the annotated composite. The second problem is that each annotated genome is about 1 GB. Scaling linearly, 100 million people would require 100 PB. Is this practical?

In the 2013 postscript, the author provides a more complete picture of the power of predictive health care. The example was completion of the “Snyderome,” the first study that integrated DNA and RNA sequencing with transcriptomes, plus metabolomes. A team led by Prof. Michael Snyder examined all of his ’omics data, which revealed that he was predisposed to diabetes. Heeding the warning, he modified his diet and lifestyle.

Focusing a group of 20 highly trained scientists on just one individual is not a viable model for health care, but it shows that ’omics information can lead to better outcomes. Predictive health will need IT for implementation. At NoSQL NOW! 2013, graph computing appeared to be particularly useful for sorting through and identifying correlations and markers from huge databases.

Topol’s 2013 postscript provides several direction-setting signposts. One was publication of 35 manuscripts for ENCODE in September 2012. The aggregate shows that 62% of the human genome produces transcripts in some type of cell. The 20,000 genes are regulated by over 4 million regulators. With such a complex regulatory system, it is not surprising that a mutation could disable the stop signal. Ineffective stop signals are implicated in autoimmune diseases and cancer.

In a related topic, Topol notes that sperm produced by humans appears to add two mutations per year of age for fathers. This shows up as increasing risk of autism and schizophrenia in progeny. Another facet is emergence of the microbiome as a hot topic in 2012. Our gut bacterial profile correlates with obesity and diabetes (I & II). But is this cause or effect?

In the 2012 edition, Topol predicted that personal electronics such as smartphones and tablets would be an ideal interface for connecting biosensors to the digital world. In 2013, he cited several examples: The iBGStar®app for the iPhone (https://itunes.apple.com/us/app/ibgstar-diabetes-manager/id506018173?mt=8) (Sanofi Aventis US, Bridgewater, NJ) continuously monitors glucose levels. Other add-ons in development include sensors for hemoglobin, oxygen, breath, and mood; a smart stethoscope for cloud-based diagnosis of pneumonia; and a smart electrocardiogram (ECG).

Topol reports that he prescribes about as many apps as medications, especially for patients with hypertension. Poor drug adherence to the prescription plan is a major problem in schizophrenia, malaria, and tuberculosis. The FDA has approved pills embedded with radiofrequency identification (RFI) chips that are activated by stomach acid. This provides a time stamp for ingestion.

New medicine will be personal by including social media. Facebook solicited additions to the organ donor registry and 300,000 signed up, greatly increasing the pool of potential donors. Dr. Topol participated in a managed competition designed to increase awareness of our lifestyle. Body weight was recorded with a wireless scale, and walking activity was recorded with a wireless accelerometer. Peer pressure within the group via smartphones motivated some individuals to decrease weight by as much as 15% and increase walking to over 30,000 steps per day. Topol concludes that managed competition enabled by social media increases motivation. He expects that this will soon extend to groups with chronic conditions such as hypertension and diabetes.

Electronic health records are essential to the digitized patient. The enormous size and complexity of issues make progress frustratingly slow. Topol’s postscript cites several significant developments. Privacy is one facet in which records were leaked, despite good protection. Computerization of electronic health records, with checklists and prompts, has led to more complete recording of visits and higher bills, since it is easy to check the box. Kaiser Permanente (Oakland, CA), one of America’s leading health-care providers, introduced a smartphone app that allows patients to access test results and visit reports.

The medical profession will emerge into a new role as partner of the patient. Doctors will be responsible for bringing the best available information to the patient so that together they can manage the patient’s health.

For example, according to Topol, a patient diagnosed with cancer should request that a portion of the biopsy be frozen for sequencing, rather than have the entire sample formalin fixed. In addition, the patient should inquire about whole genome sequencing.

Topol is skeptical of the value of population medicine with mass screening and blockbuster drug models. They are expensive and not very effective. For example, prostate specific antigen (PSA) screening for prostate cancer showed that there is no difference in the death rate between cohorts that were screened and those that were not. Another report on Vitamin E found it was not effective in reducing cancer, including prostate, but actually increases the risk.

Other examples: A critical review of screening for breast and ovarian cancer showed that screening saved one life out of every 2500, but at a cost of hurting six to eight women from unnecessary treatment such as radiation, chemotherapy, or surgery. Worse, this and other anecdotes demonstrate that physicians are slow to incorporate these findings into their practice. A survey on physicians’ practices reported that about a third of the physicians did not plan to change their MO on screening.

Topol also advises actively managing one’s cumulative radioactivity exposure. He recommends a “no nuke” policy. The public will need to understand which techniques involve ionizing radiation and opt for ultrasound or nuclear magnetic resonance, which, despite having “nuclear” in the name, is not radioactive.

Dr. Topol’s review of the events of 2012 present a compelling list of advances made in a single, otherwise average, year. It will be interesting to see if he invests the time and energy to prepare an analogous review for 2013. I hope that he does.

Some items that are not covered: Regulators will need to respond to these new MOs. One should expect difficulty since some will try to protect their turf, while others leap ahead, perhaps ahead of the science. I expect that direct-to-consumer selling of monitoring apps for smartphones will be one example. How would I feel about a medication that is being withheld pending protracted regulatory review? If my choice were certain agonizing death, I’d opt for any ray of hope. If it worked, great, but if not, my statistic would help others to explore different therapies.

Dr. Topol’s treatment of new medicine is fascinating reading for scientists. Our training provides a base with which to appreciate his analysis and prognostications.

However, there is a fourth factor not mentioned by Dr. Topol: What is the business model? What does it cost? And who pays?

In 2011, server farms around the world consumed 2% of the global energy diet. This is comparable to the energy used to power the world’s airlines. However, the doubling time is only about two years. Thus, in a decade, the energy diet could be over 10 times larger. Is this sustainable? I doubt it.

In summary, Dr. Topol presents a thoughtful thesis on the future of medicine. He points out how it can be achieved technically. Again, what about the cost? And who pays? Unless we see some way to pay for it, one should anticipate a modest rate of adoption. Change takes money to implement. NoSQL Now! is commended for providing a forum that addresses the needs and solutions in managing big data.

Reference

  1. Topol, E. The Creative Destruction of Medicine. How the Digital Revolution will Create Better Health Care. Basic Books: New York, NY, 2013. ISBN 978-0-465-06183-9.

Robert L. Stevenson, Ph.D., is Editor, American Laboratory; e-mail: rlsteven@yahoo.com.

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